JP2022073745A - Inspection system, inspection method, and method for manufacturing inspection system - Google Patents

Abstract

To reduce the influence of an atmospheric temperature on a determination result of a state of an object.SOLUTION: An inspection system comprises: a generation unit that generates an object spectrum including information on the intensity of light reflected from or transmitted through an object; a processing unit that processes the object spectrum to calculate a plurality of parameter values at a plurality of wavelength points; and a determination unit that calculates, on the basis of a regression equation and the plurality of parameter values, the predicted molecular weight of a resin material of the object, so as to determine the state of the object. The regression equation is created on the basis of: a value obtained by processing a standard spectrum obtained by acquiring, at a predetermined atmospheric temperature, light reflected from or transmitted through a plurality of standard samples; and a value obtained by processing a duplicate standard spectrum generated by moving the standard spectrum in parallel to the wavelength direction.SELECTED DRAWING: Figure 24

Description

Embodiments of the present disclosure relate to inspection systems, inspection methods, and methods of manufacturing inspection systems.

A non-destructive method of inspecting an object has been proposed. For example, Patent Document 1 discloses a method of calculating a predicted molecular weight of a resin based on a spectrum obtained by irradiating a resin with light and inspecting the state of an object based on the predicted molecular weight.

Japanese Unexamined Patent Publication No. 2019-86499

The spectrum used to calculate the predicted molecular weight is affected by the temperature of the inspection system used to obtain the reflected light used to generate the spectrum and the ambient temperature in which the inspection system is located. As a result, the inspection result obtained by the inspection system is also affected by the temperature of the inspection system and the atmospheric temperature.

It is an object of the present disclosure to provide an inspection system, an inspection method, and a method for manufacturing an inspection system that can solve such a problem.

One embodiment of the present disclosure is an inspection system for inspecting the state of an object including a resin layer containing a resin material.
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
A cooling unit that cools the irradiation device and / or the detection device,
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, and a plurality of parameter values of the regression equation of the storage unit and the resin layer calculated by the processing apparatus. It is an inspection system including an analysis unit for calculating the predicted molecular weight of the resin material of the resin layer, and a determination unit for determining the state of the object based on the predicted molecular weight.

In the inspection system according to the embodiment of the present disclosure, the cooling unit may be a blower.

One embodiment of the present disclosure is an inspection system for inspecting the state of an object including a resin layer containing a resin material.
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, the regression equation of the storage unit, and a plurality of parameter values of the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating the predicted molecular weight of the resin material of the resin layer and a determination unit for determining the state of the object based on the predicted molecular weight is provided.
The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by applying the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. It is an inspection system created by.

In the inspection system according to one embodiment of the present disclosure, the duplicate standard spectrum may be generated by translating the standard spectrum in the range of −0.5 nm to +1.0 nm in the wavelength direction.

One embodiment of the present disclosure is an inspection system for inspecting the state of an object including a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, and a plurality of parameter values of the regression equation of the storage unit and the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating the predicted molecular weight of the resin material of the resin layer and a determination unit for determining the state of the object based on the predicted molecular weight is provided.
The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring a value obtained at a plurality of wavelength points by performing a process including a combination thereof and the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. , Peak shift correction, or a process including a combination thereof, which is an inspection system created based on the values obtained at a plurality of wavelength points.

In the inspection system according to the embodiment of the present disclosure.
The regression equation is a value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averaged, smoothed, normalized, differentiated, and scattered to the first standard spectrum. A value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmission at the plurality of wavelength points of the second standard spectrum. Multiple wavelengths by subjecting the second standard spectrum to a value of light intensity or processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at the point and the third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the third standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including a combination thereof.

One embodiment of the present disclosure is an inspection system for inspecting the state of an object including a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
A storage unit in which a plurality of regression equations including a first regression equation and a second regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material are stored in advance, and the first regression equation of the storage unit. And the resin material of the resin layer based on one regression equation selected from the plurality of regression equations including the second regression equation and a plurality of parameter values of the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating a predicted molecular weight, a determination unit for determining the state of the object based on the predicted molecular weight, and a determination device.
The first regression equation is obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of one standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, and peak to the first standard spectrum. It is created based on the values obtained at multiple wavelength points by performing shift correction or processing including a combination thereof.
The second regression equation is the said at a plurality of wavelength points of the second standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. Processing including standard reflected light or the value of the intensity of the standard transmitted light, or the second standard spectrum including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Is created based on the values obtained at multiple wavelength points.
The analysis unit includes the first regression equation and the second regression equation according to the atmospheric temperature measured by the temperature monitor when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations, and the prediction of the resin material of the resin layer is based on the selected regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. It is an inspection system that calculates the molecular weight.

In the inspection system according to the embodiment of the present disclosure.
The plurality of the regression equations include the first regression equation, the second regression equation, and a third regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material.
The third regression equation is a third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. Intensity value of the standard reflected light or the standard transmitted light at a plurality of wavelength points of, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, to the third standard spectrum. Or it is created based on the values obtained at multiple wavelength points by performing a process including a combination thereof.
The analysis unit has the first regression equation, the second regression equation, and the second regression equation according to the atmospheric temperature measured by the temperature monitor when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including the third regression equation, and the said regression equation is based on the selected regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. The predicted molecular weight of the resin material of the resin layer may be calculated.

One embodiment of the present disclosure is an inspection system for inspecting the state of an object including a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
A regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material, and a predicted molecular weight of the resin material of the resin layer calculated based on the regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. A storage unit in which a temperature-specific correction formula for correcting the above atmospheric temperature is stored in advance, and a corrected molecular weight obtained by calculating the predicted molecular weight and correcting the predicted molecular weight according to the atmospheric temperature by the temperature-based correction formula. It is an inspection system including an analysis unit for calculating the above, a determination unit for determining the state of the object based on the corrected molecular weight, and a determination device including the determination unit.

In the inspection system according to the embodiment of the present disclosure, the regression equation acquires standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the standard spectrum obtained by the above, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the standard spectrum. , Peak shift correction, or a process including a combination thereof, and the value obtained at a plurality of wavelength points, and the light represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction. Multiple values of intensity at multiple wavelength points, or by processing the duplicated standard spectrum to include averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. It may be created based on the value obtained at the wavelength point of.

In the inspection system according to the embodiment of the present disclosure, the regression equation is a standard reflected light or a standard transmitted light which is a reflected light or a transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum obtained by acquisition, or averaging, smoothing, normalizing, differentiating, and scattering to the first standard spectrum. The value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the reflected light or transmitted light of the standard sample are different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum obtained by acquiring at the second atmospheric temperature, or averaging and smoothing to the second standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof.

In the inspection system according to one embodiment of the present disclosure, the regression equation is the value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averages to the first standard spectrum. Values obtained at a plurality of wavelength points by performing a process including normalization, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof, and a plurality of the second standard spectra. The value of the intensity of the standard reflected light or the standard transmitted light at the wavelength point, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or their The value obtained at a plurality of wavelength points by performing the treatment including the combination, and the reflected light or the transmitted light of the standard sample at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the third standard spectrum obtained by acquisition, or averaging, smoothing, normalizing, differentiating, and scattering to the third standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof.

The inspection system according to one embodiment of the present disclosure may further include a cooling unit for cooling the irradiation device and / or the detection device.

One embodiment of the present disclosure is an inspection method for inspecting the state of an object including a resin layer containing a resin material.
An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
An irradiation step of irradiating the object with irradiation light using an irradiation device, and
A detection step of detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light by a detection device.
A cooling step for cooling the irradiation device and / or the detection device, and
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. It is an inspection method including a determination step of determining the state of the object based on the molecular weight.

One embodiment of the present disclosure is an inspection method for inspecting the state of an object including a resin layer containing a resin material.
An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. A determination step of determining the state of the object based on the molecular weight is provided.
The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by applying the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. It is an inspection method created by.

In the inspection method according to one embodiment of the present disclosure, the duplicate standard spectrum may be generated by translating the standard spectrum in the range of −0.5 nm to +1.0 nm in the wavelength direction.

One embodiment of the present disclosure is an inspection method for inspecting the state of an object including a resin layer containing a resin material.
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. A determination step of determining the state of the object based on the molecular weight is provided.
The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring a value obtained at a plurality of wavelength points by performing a process including a combination thereof and the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. , Peak shift correction, or a process including a combination thereof, which is an inspection method created based on the values obtained at a plurality of wavelength points.

In the inspection method according to one embodiment of the present disclosure, the regression equation is the value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averages to the first standard spectrum. Values obtained at a plurality of wavelength points by performing a process including normalization, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof, and a plurality of the second standard spectra. The value of the intensity of the standard reflected light or the standard transmitted light at the wavelength point, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or their The value obtained at a plurality of wavelength points by performing the treatment including the combination, and the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the third standard spectrum obtained by acquisition, or averaging, smoothing, normalizing, differentiating, and scattering to the third standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof.

One embodiment of the present disclosure is an inspection method for inspecting the state of an object including a resin layer containing a resin material.
The temperature measurement process to measure the atmospheric temperature and
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
One regression equation selected from a plurality of regression equations including a first regression equation and a second regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material, and the calculation calculated in the processing step. A determination step of calculating the predicted molecular weight of the resin material of the resin layer based on a plurality of parameter values of the resin layer and determining the state of the object based on the predicted molecular weight is provided.
The first regression equation is obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, and peak shift to the first standard spectrum. Created based on values obtained at multiple wavelength points by correction or processing including combinations thereof.
The second regression equation is the said at a plurality of wavelength points of the second standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. Processing including standard reflected light or the value of the intensity of the standard transmitted light, or the second standard spectrum including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Is created based on the values obtained at multiple wavelength points.
In the determination step, the first regression equation and the second regression equation are performed according to the atmospheric temperature measured in the temperature measuring step when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including, and the predicted molecular weight of the resin material of the resin layer is predicted based on the selected regression equation and the plurality of parameter values calculated in the processing step. The inspection method to calculate.

In the inspection method according to the embodiment of the present disclosure, the plurality of the regression equations are the first regression equation, the second regression equation, and the third parameter showing the relationship between the plurality of parameter values and the molecular weight of the resin material. Including the regression equation of
The third regression equation is a third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. Intensity value of the standard reflected light or the standard transmitted light at a plurality of wavelength points of, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, to the second standard spectrum. Or it is created based on the values obtained at multiple wavelength points by performing a process including a combination thereof.
In the determination step, the first regression equation and the second regression equation are obtained according to the atmospheric temperature measured in the temperature measuring step when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including the third regression equation, and the resin is based on the selected regression equation and the plurality of parameter values calculated in the processing step. The predicted molecular weight of the resin material of the layer may be calculated.

One embodiment of the present disclosure is an inspection method for inspecting the state of an object including a resin layer containing a resin material.
The temperature measurement process to measure the atmospheric temperature and
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. The present invention comprises a determination step of calculating a corrected molecular weight by correcting the molecular weight by a temperature-based correction formula according to the atmospheric temperature measured in the temperature measuring step and determining the state of the object based on the corrected molecular weight. , Inspection method.

In the inspection method according to the embodiment of the present disclosure, the regression equation acquires standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the standard spectrum obtained by the above, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the standard spectrum. , Peak shift correction, or a process including a combination thereof, and the value obtained at a plurality of wavelength points, and the light represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction. Multiple by applying a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof to the values at a plurality of wavelength points of the intensity or the duplicated standard spectrum. It may be created based on the value obtained at the wavelength point of.

In the inspection method according to the embodiment of the present disclosure, the regression equation is a standard reflected light or a standard transmitted light which is a reflected light or a transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum obtained by acquisition, or averaging, smoothing, normalizing, differentiating, and scattering to the first standard spectrum. The value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmitted light are different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum obtained by acquiring at the second atmospheric temperature, or averaging and smoothing to the second standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof.

In the inspection method according to one embodiment of the present disclosure, the regression equation is the value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averages to the first standard spectrum. Values obtained at a plurality of wavelength points by performing a process including normalization, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof, and a plurality of the second standard spectra. The value of the intensity of the standard reflected light or the standard transmitted light at the wavelength point, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or their The value obtained at a plurality of wavelength points by performing the treatment including the combination, and the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the third standard spectrum obtained by acquisition, or averaging, smoothing, normalizing, differentiating, and scattering to the second standard spectrum. It may be created based on the values obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof.

In the inspection method according to the embodiment of the present disclosure,
The irradiation light is irradiated by an irradiation device and
The intensity of the reflected light or the transmitted light is detected by the detection device, and the intensity is detected.
The inspection method may further include a cooling step of cooling the irradiation device and / or the detection device.

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A standard sample irradiation step of irradiating a plurality of standard samples containing a resin material having a known molecular weight with irradiation light, and
A standard sample detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating a plurality of the standard samples with the irradiation light, and a standard sample detection step.
A standard spectrum generation step of acquiring a plurality of standard spectra, each containing information regarding the intensity of the reflected light or the transmitted light at a plurality of wavelength points.
Intensity values of the reflected light or transmitted light at multiple wavelength points of the plurality of standard spectra, or averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, for each of the plurality of standard spectra. A standard sample processing step in which values obtained at a plurality of wavelength points by performing a peak shift correction or a process including a combination thereof are calculated as a plurality of parameter values corresponding to each wavelength point.
It is a manufacturing method of an inspection system including an analysis step of creating a regression equation expressing a relationship between a plurality of parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A standard sample irradiation step of irradiating a plurality of standard samples containing a resin material having a known molecular weight with irradiation light, and
A standard sample detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating a plurality of the standard samples with the irradiation light, and a standard sample detection step.
A standard spectrum generation step of acquiring a plurality of standard spectra, each containing information regarding the intensity of the reflected light or the transmitted light at a plurality of wavelength points.
The value of the intensity of the reflected or transmitted light at a plurality of wavelength points of the intensity of the light represented by the standard spectrum and the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the above. It is obtained at a plurality of wavelength points by subjecting each of the standard spectrum and the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. A standard sample processing step in which values are calculated as multiple parameter values corresponding to each wavelength point, and
A method for manufacturing an inspection system, comprising an analysis step of creating a regression equation expressing the relationship between a plurality of the parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method. ..

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A first standard sample irradiation step of irradiating a plurality of standard samples with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
An analysis step for creating a regression equation expressing the relationship between a plurality of the first standard parameter values and a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample using a multivariate analysis method. It is a manufacturing method of an inspection system including.

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A first standard sample irradiation step of irradiating a plurality of standard samples with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A third standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature.
A third standard reflected light or a third standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the third atmospheric temperature with the irradiation light, is detected. 3 Standard sample detection process and
A third standard spectrum generation step of acquiring a plurality of third standard spectra, each containing information on the intensity of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points.
Intensity values of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points of the plurality of the third standard spectra, or averaged, smoothed, and normalized to each of the plurality of the third standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of third standard parameter values corresponding to each wavelength point. The third standard sample processing step to be calculated respectively, and
A regression equation expressing the relationship between the plurality of the first standard parameter values, the plurality of the second standard parameter values, and the plurality of the third standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample is multivariate. It is a manufacturing method of an inspection system including an analysis process created by using an analysis method.

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A first standard sample irradiation step of irradiating the standard sample with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A first analysis step of creating a first regression equation expressing the relationship between a plurality of the first standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A second analysis step of creating a second regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method is provided. , A method of manufacturing an inspection system.

One embodiment of the present disclosure is a method for manufacturing the above inspection system.
A first standard sample irradiation step of irradiating the standard sample with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A first analysis step of creating a first regression equation expressing the relationship between a plurality of the first standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A second analysis step of creating a second regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A third standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature.
A third standard reflected light or a third standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the third atmospheric temperature with the irradiation light, is detected. 3 Standard sample detection process and
A third standard spectrum generation step of acquiring a plurality of third standard spectra, each containing information on the intensity of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points.
Intensity values of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points of the plurality of the third standard spectra, or averaged, smoothed, and normalized to each of the plurality of the third standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of third standard parameter values corresponding to each wavelength point. The third standard sample processing step to be calculated respectively, and
A third analysis step of creating a third regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
It is a manufacturing method of an inspection system.

According to one embodiment of the present disclosure, it is possible to reduce the influence of the temperature of the inspection system and the atmospheric temperature on the inspection result.

It is sectional drawing which shows the object which concerns on one Embodiment. It is a block diagram which shows the inspection system which concerns on one Embodiment. It is a figure which shows typically the irradiation apparatus and the detection apparatus of the inspection system which concerns on one Embodiment. It is a perspective view which shows an example of the case which accommodates an irradiation apparatus and a detection apparatus. It is a figure which shows one use example of an inspection system. It is a flowchart which shows an example of an inspection process. It is a flowchart which shows an example of the calibration spectrum generation process for inspection. It is a figure which shows an example of the process of irradiating a calibration sample with irradiation light. It is a flowchart which shows an example of the target parameter value calculation process. It is a flowchart which shows an example of an inspection system manufacturing process. It is a flowchart which shows an example of the regression equation creation process. It is a flowchart which shows an example of the standard parameter value calculation process. It is a flowchart which shows an example of the 1st noise evaluation process. It is a figure which shows an example of the target spectrum. It is a figure which shows an example of the averaging spectrum. It is a figure which shows an example of the difference between a target spectrum and an averaged spectrum. It is a flowchart which shows an example of the 2nd noise evaluation process. It is a figure which shows an example of the calibration spectrum. It is a figure which shows the example of the target spectrum. It is a figure which shows the example of the target spectrum. It is a figure which shows the example of the target spectrum. It is a figure which shows the example of the predicted molecular weight. It is a figure which shows the example of the predicted molecular weight. It is a block diagram which shows the inspection system which concerns on one Embodiment. It is a figure which shows an example of a standard spectrum and a duplicate standard spectrum. It is a figure which shows an example of the relationship between the predicted molecular weight and the actual molecular weight of the resin material of an object. It is a figure which shows an example of the relationship between the predicted molecular weight and the actual molecular weight of the resin material of an object. It is a block diagram which shows the inspection system which concerns on one Embodiment. It is a figure which shows an example of the relationship between the predicted molecular weight and the actual molecular weight of the resin material of a standard sample. It is a figure which shows an example of the relationship between the corrected molecular weight of the resin material of an object, and the actual molecular weight. It is a block diagram which shows the inspection system which concerns on one Embodiment. It is a figure which shows an example of the relationship between the corrected molecular weight of the resin material of an object, and the actual molecular weight. It is a block diagram which shows the inspection system which concerns on one Embodiment. It is a perspective view which shows an example of a case. It is a perspective view which shows an example of a case.

The configuration of the object and the inspection system according to the embodiment of the present disclosure will be described in detail with reference to the drawings. It should be noted that the embodiments shown below are examples of the embodiments of the present disclosure, and the present disclosure is not construed as being limited to these embodiments. In the present invention, terms such as "base material" and "sheet" are not distinguished from each other based only on the difference in designation. For example, "base material" is a concept that includes members that may be called sheets or films.

The terms such as "parallel" and "orthogonal" and the values of length and angle used in the present specification to specify the shape and geometric conditions and their degrees are not bound by a strict meaning. , Interpret including the range where similar functions can be expected.

In the present specification, when a plurality of candidates for an upper limit value and a plurality of candidates for a lower limit value are listed for a certain parameter, the numerical range of the parameter is any one candidate for the upper limit value and any one lower limit value. It may be configured by combining with the candidates of. For example, "The parameter P may be, for example, Q1 or more, Q2 or more, or Q3 or more. The parameter P may be, for example, Q4 or less, Q5 or less, or Q6 or less. It may be. " In this case, the numerical range of the parameter P may be Q1 or more and Q4 or less, Q1 or more and Q5 or less, Q1 or more and Q6 or less, or Q2 or more and Q4 or less. It may be Q2 or more and Q5 or less, Q2 or more and Q6 or less, Q3 or more and Q4 or less, Q3 or more and Q5 or less, or Q3 or more and Q6 or less.

In the drawings referred to in the present embodiment, the same parts or parts having similar functions are designated by the same reference numerals or similar reference numerals, and the repeated description thereof may be omitted. Further, the dimensional ratio of the drawing may differ from the actual ratio for convenience of explanation, or a part of the configuration may be omitted from the drawing.

(First Embodiment)
FIG. 1 is a diagram showing an example of an object 10. The object 10 is, for example, a resin sheet. Resin sheets are used in various applications such as decorative sheets for building materials such as flooring materials, agricultural sheets, sealing sheets for semiconductor elements, and packaging sheets.

The object 10 includes a base sheet 11 and a resin layer 12 laminated on the base sheet 11. The resin layer 12 may be provided on the entire surface of the base sheet 11, or may be partially provided on the surface of the base sheet 11 so as to exhibit a pattern. In the following description, the surface of the object 10 located on the resin layer 12 side is referred to as a first surface 10x, and the surface of the object 10 located on the base sheet 11 side is referred to as a second surface 10y.

The base sheet 11 contains, for example, paper, synthetic resin, metal, ceramic, chemicals and the like. More specifically, the base sheet 11 may contain a cellulosic resin or may contain an olefin-based synthetic resin such as polypropylene. The basis weight of the base sheet 11 is, for example, 50 g / m ² or more. The basis weight of the base sheet 11 is, for example, 300 g / m ² or less, and may be 120 g / m ² or less.

The resin layer 12 contains a resin material. The resin material contained in the resin layer 12 is not particularly limited, but is, for example, a polymer resin. Examples of polymer resins include polyethylene resin, polyvinyl chloride resin (PVC), polyvinyl alcohol resin (PVA), polypropylene, polystyrene, polyvinyl acetate, acrylic resin, polyethylene terephthalate, polyester, polyamide, polycarbonate, polyurethane, and polyimide. And so on.
Examples of polyethylene-based resins include ethylene-vinyl acetate copolymer resin (EVA), ethylene-α-olefin copolymer, and other ethylene copolymers containing ethylene and components other than ethylene as monomers, in addition to polyethylene. Can be mentioned. Further, the resin layer 12 may contain rubber. Examples of the rubber include isoprene rubber, butadiene rubber, acrylonitrile-butadiene copolymer rubber, styrene-butadiene copolymer rubber and the like. The thickness of the resin layer 12 is, for example, 50 μm or more. The thickness of the resin layer 12 is, for example, 40 μm or more. The thickness of the resin layer 12 may be 700 μm or less.
As will be described later, the resin layer 12 may contain a foaming agent or a foaming aid in addition to the resin material. In this case, the thickness of the resin layer 12 before foaming is, for example, 40 μm or more and 100 μm or less. The thickness of the resin layer 12 after foaming is, for example, 300 μm or more and 700 μm or less.

The resin layer 12 may further contain a coloring material such as a pigment. The pigment may be an inorganic pigment or an organic pigment. Examples of inorganic pigments are titanium oxide, zinc flower, carbon black, black iron oxide, yellow iron oxide, yellow lead, molybdate orange, cadmium yellow, nickel titanium yellow, chrome titanium yellow, iron oxide (valve handle), cadmium. Examples thereof include red, ultramarine blue, dark blue, cobalt blue, chromium oxide, cobalt green, aluminum powder, bronze powder, mica titanium, zinc sulfide and the like. Examples of organic pigments include aniline black, perylene black, azo (azolake, insoluble azo, condensed azo), polycyclic (isoindoline, isoindoline, quinophthalone, perinone, flavantron, anthrapyrimidine, anthraquinone, etc.). Quinacridone, perylene, diketopyrrolopyrrole, dibrom anzantron, dioxazine, thioindigo, phthalocyanine, indantron, halogenated phthalocyanine) and the like can be mentioned. The content of the pigment in the resin layer 12 may be, for example, 5 parts by mass or more, or 15 parts by mass or more with respect to 100 parts by mass of the resin component. The content of the pigment in the resin layer 12 may be, for example, 50 parts by mass or less or 30 parts by mass or less with respect to 100 parts by mass of the resin component.

The resin layer 12 may contain a filler. Thereby, the strength, hardness and the like of the resin layer 12 can be increased. Fillers include, for example, inorganic materials such as calcium carbonate, aluminum hydroxide, magnesium hydroxide, antimony trioxide, zinc borate, molybdenum compounds, talc and the like. The content of the filler in the resin layer 12 may be, for example, 0.1 part by mass or more or 20 parts by mass or more with respect to 100 parts by mass of the resin material. The content of the filler in the resin layer 12 may be, for example, 100 parts by mass or less, or 70 parts by mass or less, based on 100 parts by mass of the resin material.

The resin layer 12 is an antifungal agent, an insect repellent, an antiseptic, an antibacterial agent, a deodorant, a polymerization initiator, a polymerization inhibitor, a sensitizer, a cross-linking agent, a plasticizer, a flame retardant, a charge control agent, and a heat stabilizer. It may contain additives such as a light stabilizer, a conductive agent, a defoaming agent, a rust preventive, an antioxidant, a foaming agent, a foaming aid, a near infrared absorber, an ultraviolet absorber, and an emulsifier.

[Inspection system]
FIG. 2 is a block diagram showing an inspection system 15 for inspecting an object 10. The inspection system 15 measures a spectrum representing the characteristics of the resin layer 12. The inspection system 15 calculates the predicted molecular weight of the material constituting the resin layer 12 based on the spectrum. Further, the inspection system 15 determines a state such as embrittlement of the object 10 based on the calculated predicted molecular weight. In this case, the information indicating the relationship between the state of the object 10 and the molecular weight of the resin material contained in the resin layer 12 is stored in advance in the inspection system 15. The state of the object 10 determined by the inspection system 15 is not limited to the state related to the embrittlement of the object 10.

The inspection system 15 includes an irradiation device 21, a detection device 24, a generation device 25, a processing device 27, a determination device 28, and a cooling unit 29. The irradiation device 21 and the detection device 24 constitute a spectroscopic module 20. The spectroscopic module 20 is housed in a case 40 described later. A part or all of the generation device 25, the processing device 27, the determination device 28, and the cooling unit 29 may be included in the spectroscopic module 20, or may be included in components other than the spectroscopic module 20. For example, a part or all of the generation device 25, the processing device 27, and the determination device 28 may be realized by a computer capable of communicating with the spectroscopic module 20.

[Irradiation device]
The irradiation device 21 irradiates the object 10 with irradiation light L1 such as near infrared rays. The irradiation device 21 includes an irradiation unit 211. The irradiation unit 211 irradiates the first surface 10x of the object 10 with the irradiation light L1. The wavelength of the irradiation light L1 is, for example, 800 nm or more, and may be 900 nm or more. The wavelength of the irradiation light L1 is, for example, 2500 nm or less, 2000 nm or less, or 1700 nm or less. As the irradiation device 21 for irradiating near infrared rays, for example, a deuterium halogen light source DH-2000 manufactured by Ocean Photonics can be used.

FIG. 3 is a diagram schematically showing an irradiation device 21 and a detection device 24.
The irradiation device 21 may include a diffusion unit 212. The diffusing unit 212 diffuses the irradiation light L1 emitted from the irradiation unit 211. As a result, the object 10 can be irradiated with the irradiation light L1 from various directions. Therefore, the inspection system 15 can obtain a reflection spectrum. The diffusion unit 212 is, for example, a diffusion plate arranged between the irradiation unit 211 and the object 10.

[Detector]
The detection device 24 receives the reflected light L2 reflected by the object 10. The detection device 24 can detect the intensity of the reflected light L2.

The detection device 24 includes a detection unit 241 that detects the reflected light L2 at a plurality of wavelength points. The number of wavelength points is determined according to the resolution of the detection unit 241. For example, when the detection unit 241 detects the intensity of the reflected light L2 with a resolution of 3 nm in the range of 900 nm or more and 1800 nm or less, the number of wavelength points is 301. As the detection unit 241, a near-infrared spectroscope, a near-infrared hyperspectral camera, or the like can be used.

The detection unit 241 detects the reflected light L2 that is specularly reflected by the object 10. The detection unit 241 may detect the reflected light L2 diffusely reflected by the object 10 in addition to the reflected light L2 specularly reflected by the object 10. This makes it possible to obtain more information about the resin material. Therefore, the accuracy of determining the composition of the resin layer 12 can be improved. In FIG. 3, the reference numeral H1 represents the distance between the detection unit 241 and the object 10, and the reference numeral W1 represents the width of the detection unit 241. The distance H1 and the width W1 are appropriately determined so that the reflected light L2 diffusely reflected by the object 10 is incident on the detection unit 241.

As the irradiation device 21 and the detection device 24, a spectroscope in which the irradiation function of the irradiation light L1 and the detection function of the reflected light L2 are integrated may be used. As such a spectroscope, for example, a near-infrared spectroscopic built-in reflection module M-R2 manufactured by innoSpectra can be used.

[Generator]
The generation device 25 includes a first generation unit 251 and a second generation unit 252. The first generation unit 251 generates a spectrum including information on the intensity of the reflected light L2 at a plurality of wavelength points. In the following description, a spectrum including information on the intensity of the reflected light L2 reflected by the object 10 is also referred to as an object spectrum.

As used herein, "spectrum" means a group of data corresponding to a wavelength point. When a group of data is illustrated, a graph as shown in FIG. 14, which will be described later, is generated. The data includes information about the intensity of the reflected light L2 at the wavelength point. The data may be the intensity of the reflected light L2 itself. The data may be calculated by applying some processing to the intensity of the reflected light L2 at the wavelength point. For example, the data may be absorbance. Absorbance is a dimensionless quantity indicating the degree to which the object 10 absorbs light. Absorbance Abs is calculated by, for example, the following formula.
Abs = -log ₁₀ (Itar / Iref)
Itar is the intensity of the reflected light reflected by the object 10. Iref is the intensity of the reflected light reflected by the calibration sample. The calibration sample is, for example, a standard reflector. The standard reflector is also referred to as a standard white plate, a white plate, or the like. As such a calibration sample, for example, Spectralon manufactured by Labsphere can be adopted.

The second generation unit 252 generates a spectrum containing information on the intensity of the reflected light reflected by the calibration sample at a plurality of wavelength points. In the following description, a spectrum containing information on the intensity of the reflected light reflected by the calibration sample is also referred to as a calibration spectrum. The first generation unit 251 may generate the target spectrum by using the calibration spectrum as a reference, as represented by the above equation.

As the detection device 24 and the generation device 25, a device in which the light receiving function of the reflected light and the acquisition function of the reflection spectrum are integrated may be used. As such a device, for example, manufactured by JFE Techno Research Co., Ltd. SWIR-2400, an imaging spectroscopic analyzer for near-infrared rays, Micro NIR Spectrometer manufactured by VIVA, and the like can be used.

[Processing equipment]
The processing device 27 includes a first processing unit 271 and a second processing unit 272. The first processing unit 271 performs some processing on the target spectrum. For example, the first processing unit 271 may perform local averaging to generate an averaging spectrum by locally averaging the target spectrum. The first processing unit 271 may carry out a first noise evaluation that calculates a first noise figure based on the difference between the target spectrum and the local averaged spectrum. The first processing unit 271 may perform the first recording for recording the target spectrum when the first noise figure is equal to or higher than the first threshold value TH1.

The first processing unit 271 may further perform some processing on the target spectrum recorded or generated by the first recording. For example, the first processing unit 271 may perform processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof on the target spectrum. As a result, the first processing unit 271 can calculate a plurality of parameter values corresponding to a plurality of wavelength points. Details of these processes are described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.

The second processing unit 272 may perform some processing on the calibration spectrum. For example, the second processing unit 272 may carry out a second derivative to generate a second derivative spectrum by secondarily differentiating the calibration spectrum. The second processing unit 272 may carry out a second noise evaluation that calculates a second noise figure based on the second derivative spectrum. The second processing unit 272 may perform a second recording of recording the calibration spectrum when the second noise figure is equal to or higher than the second threshold value TH2.

[Judgment device]
The determination device 28 determines the state of the object 10 by calculating the predicted molecular weight of the resin material of the resin layer 12 based on the information recorded or generated by the processing by the first processing unit 271. For example, the determination device 28 calculates the predicted molecular weight of the resin material of the resin layer 12 based on the parameter values calculated by the first processing unit 271. The determination device 28 may be integrated with the processing device 27. The determination device 28 includes a storage unit 281, an analysis unit 282, and a determination unit 283.

The storage unit 281 is a component in which a regression equation representing the relationship between a plurality of parameter values and the molecular weight of the resin material of the resin layer 12 is stored in advance. The storage unit 281 is, for example, a memory such as a ROM or a RAM. As will be described later, the regression equation is created based on the intensity of the reflected light that is irradiated from the irradiation unit 211 of the irradiation device 21 to the standard sample and detected by the detection unit 241 of the detection device 24. Details of the regression equation are described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.
In the example shown in FIG. 2, the regression equation is created based on the reflection intensity of the reflected light obtained from the standard sample placed in the storage unit 281 at a specific (single) atmospheric temperature (for example, 25 ° C.). In the following, it is also called the standard regression equation.

The analysis unit 282 applies the regression equation of the storage unit 281 (standard regression equation in the example shown in FIG. 2) to each of a plurality of parameter values. Thereby, the predicted molecular weight of the resin material of the resin layer 12 can be calculated. The analysis unit 282 is, for example, a CPU. Details of the method for calculating the predicted molecular weight are described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.

The determination unit 283 determines the state of the resin layer 12 based on the predicted molecular weight calculated by the analysis unit 282. The method of determining the state of the object 10 by the determination unit 283 is not particularly limited. For example, when determining whether or not an object 10 having a resin layer 12 containing a polyethylene-based resin as a resin material is brittle, the object 10 whose molecular weight of the resin material is calculated to be 80,000 or more is brittle. Therefore, it may be determined that the resin sheet 10 calculated to be less than 80,000 is brittle. The determination unit 283 is, for example, a CPU.

Although not shown, the determination device 28 may have a display unit for displaying the determination result. The method of displaying the determination result on the display unit is not particularly limited as long as the determination result can be understood from the display. For example, when determining whether or not the object 10 is brittle, the predicted molecular weight calculated by the analysis unit 282 may be displayed, and the determination unit 283 determines that the object 10 is not brittle. In that case, a symbol such as a circle may be displayed. Further, both the predicted molecular weight and the symbol such as a circle may be displayed. Further, different colors may be displayed on the display unit depending on the determination result.

[Cooling unit]
The cooling unit 29 cools the irradiation device 21 and / or the detection device 24. In the illustrated example, the cooling unit 29 is a blower including a fan, and the irradiation device 21 and / or the detection device 24 is cooled by blowing air to the spectroscopic module 20 by the fan, but the present invention is not limited to this. The cooling unit 29 may cool the irradiation device 21 and / or the detection device 24 by a Belche element or a heat sink.

By cooling the spectroscopic module 20 by the cooling unit 29, it is possible to prevent the temperature of the spectroscopic module 20 from rising due to the heat generated by the lamps, electronic circuits, etc. built in the inspection system 15 while the inspection system 15 is in operation. Will be done. Here, the present inventors have determined that the temperature of the irradiation device 21 or the detection device 24 affects the intensity of the reflected light detected by the detection device 24 (the peak position of the spectrum generated by the generation device 25). I found it. That is, even if the reflected light is reflected by the same object 10 or the same sample, the intensity of the reflected light detected by the detection device 24 depends on the temperature of the irradiation device 21 or the detection device 24 at the time of detecting the reflected light. Found different. Then, it has been found that by cooling the spectroscopic module 20 by the cooling unit 29 while the inspection system 15 is in operation, the temperature rise of the spectroscopic module 20 is suppressed and the intensity of the reflected light detected by the detection device 24 is stabilized. ..

Next, the specific structure of the inspection system 15 will be described. As shown in FIG. 4, the inspection system 15 may include a case 40 that houses the spectroscopic module 20 and the cooling unit 29. The spectroscopic module 20 includes an irradiation device 21 and a detection device 24. The case 40 preferably has a portable form. The weight of the case 40 in which the irradiation device 21 and the detection device 24 are housed is, for example, 5 kg or less, may be 2 kg or less, and is preferably 1 kg or less. By carrying the case 40, it is possible to inspect the objects 10 arranged in various places.

The case 40 may include a first surface 41, a second surface 42, and a side surface. The first surface 41 faces the object 10 when the inspection method using the inspection system 15 is carried out. The first surface 41 includes a window 48 through which light passes. The light is the light emitted from the irradiation device 21 or the reflected light received by the detection device 24. The window 48 may include an opening formed in the first surface 41. The second surface 42 faces the first surface 41. The side surface is located between the first surface 41 and the second surface 42. The side surface may include, for example, a first side surface 43, a second side surface 44, a third side surface 45, and a fourth side surface 46. The second surface 42 faces the first surface 41. The second side surface 44 faces the first side surface 43. The first side surface 43 and the second side surface 44 are located between the first surface 41 and the second surface 42.

The case 40 may include, for example, a first outer edge 411, a second outer edge 412, a third outer edge 413, and a fourth outer edge 414. The first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 constitute the outer edge of the portion of the case 40 facing the object 10.

A part or all of the first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 may be the outer edge of the first surface 41. Part or all of the first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 are the outer edges of the side surfaces such as the first side surface 43, the second side surface 44, the third side surface 45, and the fourth side surface 46. May be.

The dimension K1 of the first outer edge 411 is, for example, 500 mm or less, may be 400 mm or less, or may be 300 mm or less. The dimension K1 of the first outer edge 411 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.
The dimension K2 of the third outer edge 413 is, for example, 500 mm or less, 400 mm or less, or 300 mm or less. The dimension K2 of the third outer edge 413 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.
The distance K3 between the first surface 41 and the second surface 42 is, for example, 500 mm or less, may be 400 mm or less, or may be 300 mm or less. The distance K3 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.

FIG. 5 is a diagram showing an example of use of the inspection system 15. In the example shown in FIG. 5, the case 40 is held by a person's right hand 61 and left hand 62. The first surface 41 of the case 40 faces the object 10. When carrying out the inspection method using the inspection system 15, a part or all of the first outer edge 411, the second outer edge 412, the third outer edge 413 and the fourth outer edge 414 may be in contact with the object 10.

〔Inspection methods〕
Next, an example of a method of inspecting the state of the object 10 by using the above-mentioned inspection system 15 will be described. The inspection method includes an inspection step of carrying out an inspection of the state of the object 10.

[Inspection process]
The inspection process will be described. In the example shown in FIG. 6, the inspection step includes an inspection calibration spectrum recording step S1, a target parameter value calculation step S2, and a determination step S3.

First, the inspection calibration spectrum recording step S1 will be described. As shown in FIG. 7, the inspection calibration spectrum recording step S1 includes a calibration sample preparation step S11, a calibration sample irradiation step S12, a calibration sample detection step S13, a calibration spectrum generation step S14, and a second noise evaluation step S15. And the second recording step S16.
In the calibration sample preparation step S11, the calibration sample 51 is prepared.
In the calibration sample irradiation step S12, the irradiation device 21 irradiates the calibration sample 51 with light in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). Irradiate near infrared rays as.
In the calibration sample detection step S13, the detection device 25 is reflected by the calibration sample 51 in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). The intensity of the reflected light (referred to as "calibrated reflected light", the same shall apply hereinafter) is detected.
As shown in FIG. 8, the calibration sample irradiation step S12 and the calibration sample detection step S13 may be performed in a state where the calibration sample 51 is in contact with the first surface 41 so as to cover the window 48. In this case, the calibration sample 51 may be fixed to the case 40. For example, the calibration sample 51 may be pressed against the window 48 by the rubber band 52 wrapped around the case 40. Although not shown, the calibration sample 51 may be separated from the first surface 41. When the calibration sample 51 is separated from the first surface 41, it is preferable to make the surroundings a dark room. As a result, it is possible to suppress the inspection system 15 from detecting external light. Further, in the step of detecting the object 10, it is preferable that the distance between the object 10 and the first surface 41 is the same as the distance between the calibration sample 51 and the first surface 41.
Further, in the example shown in FIG. 2, the calibration sample irradiation step S12 and the calibration sample detection step S13 are performed on the calibration sample 51 placed at a specific (single) atmospheric temperature (for example, 25 ° C.).
In the calibration spectrum generation step S14, the second generation unit 252 of the generation device 25 generates the calibration spectrum. The calibration spectrum contains information about the intensity of the calibration reflected light at multiple wavelength points.
In the second noise evaluation step S15, the calibration spectrum is subjected to the second derivative to generate the second derivative spectrum, and the second noise index is calculated based on the second derivative spectrum. The second noise figure is an index of the degree of noise included in the calibration spectrum.
In the second recording step S16, the second processing unit 272 records the calibration spectrum in which the second noise figure is equal to or higher than the second threshold value TH2.

Next, the target parameter value calculation step S2 will be described. As shown in FIG. 9, the target parameter value calculation step S2 includes an object irradiation step S21, an object detection step S22, a target spectrum generation step S23, an object first noise evaluation step S24, and an object first. The recording step S25 and the object processing step S26 are included.
In the object irradiation step S21, the irradiation device 21 irradiates the object 10 with light in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). Irradiate near infrared rays as L1.
In the object detection step S22, the detection device 25 is reflected by the object 10 in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). The intensity of the reflected light (target reflected light) L2 is detected.
In the example shown in FIG. 2, the object irradiation step S21 and the object detection step S22 have substantially the same atmospheric temperature as the atmospheric temperature in which the calibration sample 51 was placed in the calibration sample irradiation step S12 and the calibration sample detection step S13 of FIG. It is desirable to do this for the placed object 10.
The target spectrum generation step S23 includes a first target spectrum generation step and a second target spectrum generation step. In the first target spectrum generation step, the first generation unit 251 of the generation device 25 generates the first target spectrum. The first target spectrum contains information regarding the intensity of the target reflected light L2 at a plurality of wavelength points. In the second target spectrum generation step, the absorbance at a plurality of wavelength points is calculated based on the first target spectrum and the calibration spectrum recorded in the second recording step S16, and the absorbance spectrum including the absorbance at the plurality of wavelength points (first). 2 Target spectrum) is calculated.
In the object first noise evaluation step S24, the first processing unit 271 locally averages the second target spectrum to generate a local averaging spectrum (local averaging target spectrum). Further, in the object first noise evaluation step S24, the first processing unit 271 calculates the first noise index (object first noise index) based on the difference between the second target spectrum and the local averaging target spectrum. The object first noise figure is an index of the degree of noise included in the target spectrum. The calculated object first noise figure may be displayed on the display of the computer constituting the processing device 27.
In the first object recording step S25, the first processing unit 271 records the second target spectrum in which the first noise figure is equal to or higher than the first threshold value TH1. The comparison result of the first noise index and the first threshold value TH1 may be displayed on the display of the computer constituting the processing device 27.
In the object processing step S26, each of the second object spectra recorded in the object first recording step S25 is averaged, smoothed, normalized, differentiated, scattered, baseline corrected, and peaked by the processing device 27. A plurality of parameter values corresponding to a plurality of wavelength points are calculated by performing a shift correction or a process including a combination thereof. Details of such processing are described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.

Next, the determination step S3 will be described.
In the determination step S3, the analysis unit 282 is based on the regression equation (standard regression equation in the example shown in FIG. 2) stored in the storage unit 281 of the determination device 28 and the parameter values calculated in the object treatment step S26. The predicted molecular weight of the resin material of the object 10 is calculated. Then, based on the calculated predicted molecular weight, the determination unit 283 determines the state of the object 10. Details of such a determination are described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.

By the above method, the state of the object 10 can be determined.

The inspection step may not include the inspection calibration spectrum recording step S1. In this case, the target spectrum generation step S23 of the target parameter calculation step S2 may not include the second target spectrum generation step. Further, in this case, in the object first noise evaluation step S24 of the target parameter calculation step S2, the first target spectrum is locally averaged to generate a local averaging target spectrum, and the first target spectrum and the local averaging are performed. The first noise index may be calculated based on the difference from the target spectrum. Further, in this case, in the object first recording step S25, the first processing unit 271 may record the first target spectrum in which the first noise figure is equal to or higher than the first threshold value TH1. Then, in the object processing step S26, each of the recorded first object spectra is subjected to processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Therefore, a plurality of target parameter values corresponding to a plurality of wavelength points may be calculated.

Further, the inspection calibration spectrum recording step S1 may not include the second noise evaluation step S15. In this case, in the second recording step S16, all the calibration spectra generated in the calibration spectrum generation step S14 may be recorded.

Further, the target parameter value calculation step S2 may not include the target object first noise evaluation step S24. In this case, in the object first recording step S25, all the first target spectra generated in the target spectrum generation step S23 may be recorded.

[Manufacturing method of inspection system]
Next, the manufacturing method of the above-mentioned inspection system 15 will be described. The manufacturing method of the inspection system 15 includes an inspection system manufacturing process. In the example shown in FIG. 10, the inspection system manufacturing step includes a preparation step S4 and a regression equation creating step S5.

In the preparation step S4, the spectroscopic module 20 (irradiation device 21 and detection device 24), the processing device 27, the determination device 28, and the cooling unit 29 as shown in FIG. 2 are prepared.

[Regression formula creation process]
Next, the regression equation creation step S5 will be described. As shown in FIG. 11, the regression equation creation step S5 includes a standard sample preparation step S51, a regression equation calibration spectrum recording step S52, a standard parameter value calculation step S53, an analysis step S54, and a regression equation recording step S55. including. Since the regression spectrum calibration spectrum recording step S52 is the same step as the inspection calibration spectrum recording step S1 described above, the description thereof is omitted here.

In the standard sample preparation step S51, a plurality of standard samples are prepared. Each standard sample is configured in the same manner as the object 10, and includes a resin layer containing a resin material. The molecular weight of the resin material is known. For example, the molecular weight of the resin material of each standard sample is measured in advance by a gel permeation chromatography (GPC) system attached to a liquid chromatograph. The molecular weight of each standard sample is, for example, 10,000 or more and 220,000 or less.

As shown in FIG. 12, the standard parameter value calculation step S53 includes a standard sample irradiation step S531, a standard sample detection step S532, a standard spectrum generation step S533, a standard sample first noise evaluation step S534, and a standard sample first. It includes a recording step S535 and a standard sample processing step S536.
In the standard sample irradiation step S531, the irradiation device 21 is in the standard sample preparation step S51 in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). Irradiate the prepared standard sample with near infrared rays as irradiation light.
In the standard sample detection step S532, the detection device 25 is reflected by the standard sample in a state where the spectroscopic module 20 is cooled by the cooling unit 29 (in the illustrated example, the spectroscopic module 20 is blown to the spectroscopic module 20 by the cooling unit 29). Detects the intensity of reflected light (standard reflected light).
The standard sample irradiation step S531 and the standard sample detection step S532 are placed at substantially the same atmospheric temperature as the atmospheric temperature at which the object 10 is placed when the object irradiation step S21 and the object detection step S22 shown in FIG. 9 are performed. It is desirable to do this for the standard sample that has been squeezed. In the example shown in FIG. 2, the standard sample irradiation step S531 and the standard sample detection step S532 are performed on a standard sample placed at a specific (single) atmospheric temperature (eg, 25 ° C.).
The standard spectrum generation step S533 includes a first standard spectrum generation step and a second standard spectrum generation step. In the first standard spectrum generation step, the first generation unit 251 of the generation device 25 generates a standard spectrum (first standard spectrum). The first standard spectrum contains information about the intensity of standard reflected light at multiple wavelength points. In the second target spectrum generation step, the absorbance at a plurality of wavelength points is calculated based on the first standard spectrum and the calibration spectrum recorded in the second recording step of the regression equation calibration spectrum recording step S52, and the plurality of wavelength points are calculated. The absorbance spectrum (second standard spectrum) including the absorbance in the above is calculated.
In the standard sample first noise evaluation step S534, the first processing unit 271 locally averages the second standard spectrum to generate a local averaging spectrum (local averaging standard spectrum). Further, in the standard sample first noise evaluation step S534, the first processing unit 271 calculates the first noise index (standard sample first noise index) based on the difference between the second standard spectrum and the locally averaged standard spectrum. The standard sample first noise figure is an index of the degree of noise contained in the standard spectrum. The calculated standard sample first noise figure may be displayed on the display of the computer constituting the processing device 27.
In the standard sample first recording step S535, the first processing unit 271 records the second standard spectrum in which the standard sample first noise figure is equal to or higher than the first threshold value TH1. The comparison result of the standard sample first noise index and the first threshold value TH1 may be displayed on the display of the computer constituting the processing device 27.
In the standard sample processing step S536, each of the second standard spectra recorded in the standard sample first recording step S535 is averaged, smoothed, normalized, differentiated, scattered, corrected, baseline corrected, and peaked by the processing device 27. A plurality of parameter values (standard parameter values) corresponding to a plurality of wavelength points are calculated by performing a shift correction or a process including a combination thereof.

In the analysis step S54, the analysis unit 282 of the determination device 28 expresses the relationship between the plurality of standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample (standard regression equation in the example shown in FIG. 2). Is created using a multivariate analysis method. The multivariate analysis can be performed by recording a program for multivariate analysis in the storage unit 281 and executing this program in the analysis unit 282.
As a multivariate analysis method, for example, PLS regression analysis can be performed. As software for performing PLS regression analysis, multivariate analysis software The Unscrambler X manufactured by Camo Software can be used.
In the analysis step S54, multivariate analysis other than PLS regression analysis may be adopted. For example, a multivariate analysis method such as CLS (Classical Regression square), ILS (Inverse rest sphere), MLR (Multiple liner regression), PCR (Principal Regression analysis) may be adopted.

In the regression equation recording step S55, the storage unit 281 of the determination device 28 records the regression equation created in the analysis step.

By the above method, the above-mentioned inspection system 15 can be manufactured.

The regression equation creation step S5 does not have to include the regression equation calibration spectrum recording step S52. In this case, the standard spectrum generation step S533 of the standard parameter value calculation step S53 may not include the second standard spectrum generation step. Further, in this case, in the standard sample first noise evaluation step S534 of the standard parameter value calculation step S53, the first standard spectrum is locally averaged to generate a locally averaged standard spectrum, and the first standard spectrum and the local average are generated. The standard sample first noise index may be calculated based on the difference from the standard spectrum. Further, in this case, in the standard sample first recording step S535, the first processing unit 271 may record the first standard spectrum in which the standard sample first noise figure is equal to or higher than the first threshold value TH1. Then, in the standard sample processing step S536, each of the recorded first standard spectra is subjected to processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Therefore, a plurality of standard parameter values corresponding to a plurality of wavelength points may be calculated.

Further, the standard parameter value calculation step S53 may not include the standard sample first noise evaluation step S534. In this case, in the standard sample first recording step S535, all the first standard spectra generated in the standard spectrum generation step S533 may be recorded.

Further, in the standard sample processing step S536 and the analysis step S54, the standard parameters obtained by subjecting the first standard spectrum (reflection spectrum) or the second standard spectrum (absorbance spectrum) generated by the generator 25 to processing such as differentiation. An example of performing a multivariate analysis based on the values is shown. However, it is not limited to this. For example, multivariate analysis may be performed based on the parameter values obtained by subjecting the absorption spectrum (standard absorption spectrum) obtained by inverting the first standard spectrum (reflection spectrum) to processing such as differentiation. .. In addition, multivariate analysis is performed based on the values of intensity, reflectance, absorptivity, etc. at each wavelength point included in the first standard spectrum (reflection spectrum), the second standard spectrum (absorbance spectrum), or the standard absorption spectrum. You may.

Further, the first threshold value TH1 used in the standard sample first recording step S535 may be the same as or different from the first threshold value TH1 used in the object first recording step S25.
Similarly, the second threshold TH2 used in the regression calibration spectrum recording step S52 may be the same as or different from the second threshold TH2 used in the inspection calibration spectrum recording step S1. ..

A specific example of the regression equation creating step S5 is described in, for example, Japanese Patent Application Laid-Open No. 2019-86499.

[Details of the first noise evaluation process]
Next, the first noise evaluation steps S24 and S534 will be described in detail. In the example shown in FIG. 13, the first noise evaluation steps S24 and S534 include a local averaging spectrum generation step S6 and a first noise figure calculation step S7. Here, the object first noise evaluation step S24 will be described as an example.

First, the local averaging spectrum generation step S6 will be described. In the local averaging spectrum generation step S6, a local averaging spectrum is generated. Here, a case where a local averaging target spectrum is generated as a local averaging spectrum will be described as an example. FIG. 14 is a diagram showing an example of the target spectrum A1.

First, the target spectrum A1 is locally averaged. For example, a step of calculating a local mean value at each wavelength point of the target spectrum A1 is carried out. The local average value is calculated by averaging the value of the target spectrum A1 at the target wavelength point and the value of the target spectrum A1 at a plurality of wavelength points located in the vicinity of the target wavelength point.

An example in which the value of the target spectrum A1 is the absorbance will be described. For example, the local mean value at the wavelength point of 1200 nm is calculated as follows.
First, the absorbance Abs (1200) at 1200 nm is obtained. Subsequently, the value of the target spectrum A1 at a plurality of wavelength points located in the vicinity of 1200 nm is acquired. When the resolution of the detection device 24 is 3 nm, for example, the absorbance Abs (1188) at 1188 nm, the absorbance Abs (1191) at 1191 nm, the absorbance Abs (1194) at 1194 nm, the absorbance Abs (1197) at 1197 nm, and the absorbance Abs at 1203 nm (1197). 1203) Obtain the absorbance Abs (1206) at 1206 nm, the absorbance Abs (1209) at 1209 nm, and the absorbance Abs (1212) at 1212 nm. Subsequently, the average value of the absorbances at these nine wavelength points is calculated. This average value is a local average value at a wavelength point of 1200 nm.

The local mean value is calculated at each wavelength point. As a result, as shown in FIG. 15, the local averaging spectrum A2 can be generated. In FIG. 15, the target spectrum A1 is represented by a alternate long and short dash line, and the averaged spectrum A2 is represented by a solid line.

The number of wavelength points when calculating the local mean value is not limited to the above-mentioned nine. The number of wavelength points is, for example, 5 or more, and may be 7 or more. The number of wavelength points is, for example, 15 or less, and may be 13 or less.

The local averaging standard spectrum is generated by locally averaging the standard spectrum and calculating the local averaging value at each wavelength point, as in the case of generating the local averaging target spectrum.

Next, the first noise figure calculation step S7 will be described. In the first noise figure calculation step S7, the first noise figure is calculated. Here, a case where the first noise figure of the object is calculated as the first noise figure will be described as an example.

In the first noise figure calculation step S7, the difference between the target spectrum A1 and the local averaging spectrum A2 is calculated. For example, at each wavelength point, the local mean value of the averaged spectrum A2 is subtracted from the absorbance of the target spectrum A1. The spectrum generated by this is also referred to as a difference spectrum. FIG. 16 is a diagram showing an example of the difference spectrum A3. In FIG. 16, the target spectrum A1 is represented by a alternate long and short dash line, the averaged spectrum A2 is represented by a alternate long and short dash line, and the difference spectrum A3 is represented by a solid line.

Subsequently, in the first noise figure calculation step S7, the standard deviation of the difference between the target spectrum A1 and the local averaging spectrum A2 is calculated. The standard deviation represents the degree of variation in the difference between the target spectrum A1 and the local averaged spectrum A2. If the target spectrum A1 does not contain noise, it is expected that the difference between the target spectrum A1 and the local averaging spectrum A2 will be almost zero. Therefore, a small standard deviation means that the noise contained in the target spectrum A1 is small. A large standard deviation means that there is a lot of noise contained in the target spectrum A1.

It should be noted that the difference between the target spectrum A1 and the local averaging spectrum A2 is large at the position of the peak of the target spectrum A1 regardless of the noise. In order to appropriately evaluate the noise contained in the target spectrum A1, it is preferable to calculate the standard deviation of the difference at a position away from the peak of the target spectrum A1. For example, as shown in FIG. 16, the standard deviation of the difference may be calculated in the stable region R1 away from the peak. Specifically, first, the value of the difference at a plurality of wavelength points included in the stable region R1 is acquired. Subsequently, the standard deviation of the values of the plurality of differences is calculated.

The stable region R1 may be predetermined based on the information of the material expected to be contained in the object 10. For example, if the object 10 is expected to contain polyethylene, the object spectrum A1 contains a peak that appears at about 1200 nm. In this case, the wavelength range of 970 nm or more and 1100 nm or less may be predetermined as the stable region R1.

Subsequently, in the first noise figure calculation step S7, the first noise figure is calculated based on the standard deviation. The first noise figure is an index of the degree of noise included in the target spectrum A1. The first noise figure is, for example, the reciprocal of the standard deviation. When the first noise figure is large, it means that the noise included in the target spectrum A1 is small. When the first noise figure is small, it means that there is a lot of noise contained in the target spectrum A1. The calculated first noise figure may be displayed on the display of the computer constituting the processing device 27.

The standard sample first noise figure is calculated based on the standard deviation of the difference between the standard spectrum and the local averaged spectrum thereof, as in the case of calculating the object first noise figure.

When the first noise figure of the object is less than the first threshold value TH1, the steps S21, S22, S23 and S24 may be performed again on the object 10 as shown in FIG. Similarly, if the standard sample first noise figure is less than the first threshold TH1, steps S531, S532, S533 and S534 may be performed again on the standard sample, as shown in FIG. As shown in FIG. 5, when the case 40 is held by hand, noise is generated in the target spectrum A1 or the standard spectrum due to the movement of the hand during the inspection process or the inspection system manufacturing process (regression formula creation step S5). It is possible that it will occur. According to the inspection process shown in FIG. 6 or the inspection system manufacturing process shown in FIG. 10, the target spectrum A1 or the standard spectrum containing a large amount of noise caused by the movement of the hand or the like can be excluded. For example, the target spectrum A1 or the standard spectrum containing a lot of noise caused by the vibration of the spectroscopic module 20 can be excluded. Further, for example, the reflected light of air is acquired in the object detection step S22 of FIG. 9 or the standard sample detection step S532 of FIG. 12, and the reflected light is used to generate the target spectrum A1 or the standard spectrum. The target spectrum A1 or the standard spectrum containing a large amount of generated noise can be excluded. Further, the inspection step or the regression equation creation step S5 can be repeated until the target spectrum A1 or the standard spectrum having the first noise figure having the first threshold value TH1 or more is obtained. Therefore, an appropriate target spectrum A1 or a standard spectrum can be recorded.

[Details of the second noise evaluation process]
Next, the second noise evaluation step S15 will be described in detail. In the example shown in FIG. 17, the second noise evaluation step S15 includes a second-order differential spectrum generation step S151 and a second noise figure calculation step S152.

First, the second derivative spectrum generation step S151 will be described. In the second derivative spectrum generation step S151, the calibration spectrum is secondarily differentiated. Generate a second derivative spectrum. A small value in the second derivative spectrum means less noise in the calibration spectrum.

In the second noise figure calculation step S152, the standard deviation is calculated based on the second derivative spectrum. For example, first, the standard deviation of the values of the second derivative spectra at a plurality of wavelength points is calculated. The standard deviation may be calculated based on the entire wavelength range of the second derivative spectrum, or the standard deviation may be calculated based on a part of the wavelength range of the second derivative spectrum. For example, as shown in FIG. 18, when the value of the calibration spectrum is expected to decrease in the wavelength range of 1600 nm or more, the standard deviation is calculated without considering the value of the second derivative spectrum in the wavelength range of 1600 nm or more. You may.

Subsequently, in the second noise figure calculation step S152, the second noise figure is calculated based on the standard deviation. The second noise figure is an index of the degree of noise included in the calibration spectrum. The second noise figure is, for example, the reciprocal of the standard deviation. A large second noise figure means that there is little noise contained in the calibration spectrum. A small second noise figure means that there is a lot of noise contained in the calibration spectrum.

When the second noise figure is less than the second threshold value TH2, it is considered that the whole or a part of the surface of the calibration sample 51 is contaminated. In this case, the calibration sample 51 may be changed to another one, or the measurement position in the calibration sample 51 may be changed. Then, as shown in FIG. 7, steps S12, S13, S14, and S15 may be performed again for the new calibration sample 51 or for the new measurement position of the calibration sample 51.
Alternatively, when the second noise index is less than the second threshold value TH2, it is considered that the spectroscopic module 20 has moved with respect to the calibration sample 51 due to the movement of the hand or the like while receiving the calibration reflected light. In this case, steps S12, S13, S14 and S15 may be performed again for the same measurement position of the same calibration sample 51 or for a new measurement position of the same calibration sample 51, as shown in FIG. good.
By performing the second noise evaluation step S15 as described above, it is possible to eliminate a calibration spectrum containing a large amount of noise generated due to stains on the surface of the calibration sample 51, hand movements, and the like. Further, the calibration step can be repeated until a calibration spectrum having a second noise figure having a second threshold value TH2 or higher is obtained. Therefore, an appropriate calibration spectrum can be recorded.

In the inspection calibration spectrum generation step S1, steps S12, S13, S14 and S15 may be repeated until N calibration spectra having a second noise index of the second threshold value TH2 or higher are obtained. For example, if the number of recorded calibration spectra is less than N, the measurement position in the calibration sample 51 may be changed. After that, S12, S13, S14 and S15 may be performed again for the new measurement position of the calibration sample 51. According to such an inspection calibration spectrum generation step S1, it is possible to obtain N calibration spectra having a second noise figure having a second threshold value TH2 or more. N is, for example, 2 or more, may be 3 or more, or may be 4 or more. N may be, for example, 10 or less.

In the inspection calibration spectrum generation step S1, the average of N recorded calibration spectra may be calculated. This makes it possible to generate an averaged calibration spectrum. The spectral value at each wavelength point of the averaged calibration spectrum is the average value of the spectrum values of the N calibration spectra. For example, the value of the averaged calibration spectrum at the wavelength point of 1200 nm is the average value of the values of the N calibration spectra at the wavelength point of 1200 nm.

The first generation unit 251 described above may generate an object spectrum by using the averaged calibration spectrum as a reference. As a result, it is possible to further suppress the influence of noise in the calibration spectrum from appearing in the target spectrum.

[Effect of noise on the target spectrum]
Next, with reference to FIGS. 19 to 23, the influence of the above-mentioned noise on the target spectrum and the predicted molecular weight will be described. Here, the influence of noise contained in the calibration spectrum on the target spectrum and the predicted molecular weight will be described.

FIG. 19 is a diagram showing a second target spectrum (absorbance spectrum) of the object 10 generated by using the first spectrum of the object 10 and the calibration spectrum with less noise. Specifically, in the example shown in FIG. 19, a calibration sample 51 having no surface stain was used, and the calibration reflected light was received in a state where the spectroscopic module 20 was firmly fixed to the calibration sample 51. Then, a calibration spectrum was generated based on the calibration reflected light received under such appropriate conditions.
FIG. 19 shows a second target spectrum generated in an inspection step performed on nine measurement positions of one object 10.
In the example shown in FIG. 19, the noise figures of the nine generated second target spectra are 9652.83, 142165, 10542.8, 12783.5, 12084.6, 10231.1, 13034.2, respectively. , 13440.5 and 11907.5.

FIG. 20 is a diagram showing a second target spectrum (absorbance spectrum) of the object 10 generated by using the first spectrum of the object 10 and the calibration spectrum having a lot of noise. In the example shown in FIG. 20, the same object 10 and the same calibration sample 51 as the object 10 and the calibration sample 51 used in the example shown in FIG. 19 were used. However, in the example shown in FIG. 20, the calibration spectrum was generated based on the calibration reflected light appropriately received from the calibration sample 51 and the reflected light from the air. It is probable that the reflected light from the air was received by the detection device 24 with the spectroscopic module 20 away from the calibration sample 51 due to the movement of the hand or the like.
FIG. 20 shows a second target spectrum generated in an inspection step performed on nine measurement positions of the object 10, similar to the example shown in FIG.
The noise figures of the nine second target spectra shown in FIG. 20 are 77.0739, 77.1067, 77.0010, 77.0618, 77.0862, 77.0764, 77.0791, 77.0143 and 77, respectively. It was .1123.

FIG. 21 is a diagram showing a second target spectrum (absorbance spectrum) of the object 10 generated by using the first spectrum of the object 10 and the calibration spectrum having a lot of noise. In the example shown in FIG. 21, the same object 10 and the same calibration sample 51 as the object 10 and the calibration sample 51 used in the example shown in FIG. 19 were used. However, in the example shown in FIG. 21, the spectroscopic module 20 vibrates with respect to the calibration sample 51 due to the movement of the hand or the like when receiving the calibration reflected light.
FIG. 21 shows a second target spectrum generated in an inspection step performed on nine measurement positions of the object 10, similar to the example shown in FIG.
The noise figures of the nine second target spectra shown in FIG. 21 are 376.256, 377.219, 381.004, 381.094, 377.306, 379.493, 377.383, 377.824 and 376, respectively. It was .819.

As can be seen from FIGS. 19-21, noise in the calibration spectrum affects the target spectrum generated using the calibration spectrum. Then, it affects the predicted molecular weight calculated based on the target spectrum.

In FIG. 22, for the object 10 containing the resin materials having molecular weights of 130000, 40,000 and 95000, the predicted molecular weight calculated under the same conditions as those shown in FIG. 19 and the predicted molecular weight calculated under the same conditions as those shown in FIG. 20 are shown. The predicted molecular weight is shown. In FIG. 22, the predicted molecular weight calculated under the conditions shown in FIG. 19 is indicated by a square symbol. Further, in FIG. 22, the predicted molecular weight calculated under the conditions shown in FIG. 20 is indicated by a triangular symbol. As can be seen from FIG. 22, it can be seen that the calculated predicted molecular weight is significantly different from the actual molecular weight.

In FIG. 23, for the object 10 containing the resin materials having molecular weights of 130000, 40,000 and 95000, the predicted molecular weight calculated under the same conditions as those shown in FIG. 19 and the predicted molecular weight calculated under the same conditions as those shown in FIG. 21 are shown. The predicted molecular weight is shown. In FIG. 23, the predicted molecular weight calculated under the conditions shown in FIG. 19 is indicated by a square symbol. Further, in FIG. 23, the predicted molecular weight calculated under the conditions shown in FIG. 21 is indicated by a circle symbol. As shown in FIG. 23, some of the calculated predicted molecular weights are negative values. This indicates that the predicted molecular weight could not be calculated properly.

In the illustrated example, the target spectrum, the calibration spectrum, and the standard spectrum are generated by using the reflected light of the object 10, the calibration sample 51, and the standard sample, but the present invention is not limited to this. The object spectrum, the calibration spectrum, and the standard spectrum may be generated by using the transmitted light of the object 10, the calibration sample 51, and the standard sample.
In this case, in the parameter value calculation steps S2 and S53, the value of the intensity of the transmitted light at the plurality of wavelength points may be calculated as a plurality of parameter values corresponding to each wavelength point.
Further, in this case, the absorbance Abs is calculated by, for example, the following formula.
Abs = -log ₁₀ (I / Io)
I is the intensity of the transmitted light transmitted through the object 10. Io is the intensity of transmitted light transmitted through the calibration sample.

Further, in the illustrated example, the regression equation shows the relationship between a plurality of parameter values obtained based on the reflected light or transmitted light of the object 10 and the molecular weight of the resin material, but is not limited thereto. The regression equation includes a plurality of parameter values obtained based on the reflected light or transmitted light of the object 10, and the breaking strength, linear expansion coefficient, elastic modulus, hardness, crystallinity, and other physical property values of the resin material of the object 10. It may indicate the relationship with. In other words, in the determination step S3, the breaking strength, linear expansion coefficient, elastic modulus, hardness, crystallinity, and other physical property values of the resin material of the object 10 may be calculated. Also in this case, the state of the object 10 can be determined based on the calculated physical property value.

[Effect of the first embodiment]
According to the first embodiment, the irradiation device 21 and / or the detection device 24 is cooled by the cooling unit 29, so that the intensity of the reflected light from the object 10, the calibration sample 51, or the standard sample is being detected. The temperature rise of the spectroscopic module 20 is suppressed. As a result, the intensity of the reflected light from the object 10, the calibration sample 51, or the standard sample can be stably detected, and a highly reliable inspection result can be obtained.

When the ambient temperature in which the detection system 15 is placed is low, there is little possibility that the temperature of the spectroscopic module 20 will rise to the extent that it affects the intensity of the reflected light detected by the spectroscopic module 20. In this case, it is not necessary to cool the irradiation device 21 and / or the detection device 24 by the cooling unit 29.

Further, when the ambient temperature in which the detection system 15 is placed is low and the ambient temperature affects the intensity of the reflected light detected by the spectroscopic module 20, the irradiation device 21 and / or the detection device 24 may be heat-insulated. It may be covered with a high material to prevent the temperature of the irradiation device 21 and / or the detection device 24 from dropping. In other words, the inspection system 15 may include a heat insulating material that covers the irradiation device 21 and / or the detection device 24. Alternatively, in this case, the irradiation device 21 and / or the detection device 24 may be heated by a heater or the like. In other words, the inspection system 15 may include a heating unit that heats the irradiation device 21 and / or the detection device 24.

Further, it is preferable that the intensity of the reflected light by the spectroscopic module 20 is detected after a certain amount of time has elapsed after the power of the spectroscopic module 20 is turned on. In other words, it is preferable to warm up the spectroscopic module 20 before detecting the reflected light. In this case, the temperature of the irradiation device 21 and / or the detection device 24 is stable during the warm-up operation, and the intensity of the reflected light can be stably detected.

Further, according to the first embodiment, the noise included in the target spectrum can be evaluated by carrying out the object first noise evaluation step S24 shown in FIG. Therefore, it is possible to eliminate the target spectrum containing a large amount of noise caused by the movement of the hand or the like. Further, the target parameter value calculation step S2 can be repeatedly performed until a target spectrum having a first noise figure of the first threshold value TH1 or higher is obtained. Therefore, an appropriate target spectrum can be recorded. Therefore, the state of the material constituting the resin layer 12 can be appropriately determined.

Further, according to the first embodiment, the noise included in the standard spectrum can be evaluated by carrying out the standard sample first noise evaluation step S534 shown in FIG. Therefore, it is possible to eliminate the standard spectrum containing a lot of noise caused by the movement of the hand or the like. Further, the standard parameter value calculation step S53 can be repeated until a standard spectrum having a first noise figure of the first threshold value TH1 or higher is obtained. Therefore, an appropriate standard spectrum can be recorded. Therefore, it is possible to create a regression equation that can appropriately calculate the predicted molecular weight of the material constituting the resin layer 12.

Further, by carrying out the second noise evaluation step S15, the noise included in the calibration spectrum can be evaluated. Therefore, it is possible to eliminate a calibration spectrum containing a large amount of noise generated due to the surface of the calibration sample 51 being dirty or the like. Further, the inspection calibration spectrum recording step S1 can be repeatedly performed until a calibration spectrum having a second noise figure having a second threshold value TH2 or higher is obtained. Therefore, an appropriate calibration spectrum can be recorded. Therefore, the composition of the material constituting the resin layer 12 can be appropriately determined.

The above-described embodiment can be changed in various ways. Hereinafter, other embodiments will be described with reference to the drawings as necessary. In the following description and the drawings used in the following description, the same reference numerals as those used for the corresponding portions in the above-described embodiment are used for the portions that can be configured in the same manner as in the above-described embodiment. Duplicate explanations will be omitted. Further, when it is clear that the action and effect obtained in one embodiment described above can be obtained in other embodiments, the description thereof may be omitted.

(Second embodiment)
Next, the inspection system according to the second embodiment will be described with reference to FIGS. 24 to 27. The inspection system according to the second embodiment has a regression equation used in the determination step S3 (that is, a method for creating a regression equation in the regression equation creation step S5) as compared with the inspection system 15 according to the first embodiment. It's different. Other points are the same as the inspection system 15 according to the first embodiment. In the second embodiment, the same parts as those of the inspection system 15 according to the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

FIG. 24 is a block diagram showing the inspection system 15 according to the second embodiment.
The regression equation used in the inspection system 15 shown in FIG. 24 is devised as follows. First, the inventors of the present invention have discovered that even if the object 10 is the same, the obtained reflection spectrum may change when the atmospheric temperature in which the object 10 is placed changes. This means that the predicted molecular weight of the resin material of the object 10 and the inspection result based on the predicted molecular weight are affected by the ambient temperature. Therefore, the regression equation of the second embodiment is devised to reduce the change in the predicted molecular weight due to the change in the atmospheric temperature in which the object 10 is placed.

As a cause of the change in the reflection spectrum generated by the generation device 25 when the ambient temperature at which the object 10 is placed changes, the present inventors have determined that the ambient temperature is the intensity of the reflected light detected by the detection device 24 ( It has been found that it affects the peak position of the reflection spectrum generated by the generator 25). That is, it has been found that even if the reflected light is reflected by the same object 10, the intensity of the reflected light detected by the detection device 24 differs depending on the atmospheric temperature in which the object 10 is placed.

In this regard, if the inventors create a regression equation based on the parameter values of the standard samples placed at various (plural) atmospheric temperatures, the difference in the atmospheric temperature at which the target reflected light L2 is acquired will be different. It was discovered that the effect on the predicted molecular weight can be suppressed. That is, conventionally, the regression equation was created based on the reflection spectrum of a standard sample placed at one atmospheric temperature (for example, 25 ° C.). On the other hand, the standard sample is placed at various atmospheric temperatures (for example, 5 ° C, 15 ° C, 25 ° C, 35 ° C) to obtain a standard spectrum, and the information of the standard spectrum at these various atmospheric temperatures is reflected in the regression equation. Therefore, it was discovered that the influence of the difference in the atmospheric temperature at which the target reflected light L2 is acquired on the predicted molecular weight can be suppressed.

Furthermore, the present inventors have found that the peak position of the standard spectrum changes almost only in the wavelength direction due to the difference in the atmospheric temperature in which the standard sample is placed. That is, by translating the standard spectrum generated based on the standard reflected light obtained from the standard sample placed at a certain atmospheric temperature (for example, 25 ° C.) in the wavelength direction, the atmospheric temperature different from the above atmospheric temperature (for example, 25 ° C.) For example, it has been discovered that it is possible to obtain a spectrum similar to the standard spectrum generated based on the standard reflected light obtained from a standard sample placed at 5 ° C, 15 ° C, 35 ° C). Therefore, even if the standard reflected light is not actually obtained from the standard sample placed at various ambient temperatures (eg 5 ° C, 15 ° C, 25 ° C, 35 ° C), it is placed at one ambient temperature (eg 25 ° C). Similar to the standard spectrum generated based on the standard reflected light obtained from the standard samples placed at the above multiple ambient temperatures from the standard spectrum generated based on the standard reflected light obtained from the standard sample. We have found that the spectrum can be easily generated.

In FIG. 25, the standard spectrum B1 generated based on the standard reflected light obtained from the standard sample placed at a certain atmospheric temperature (for example, 25 ° C.) is shown by a solid line. Further, FIG. 25 shows duplicate standard spectra B11, B12, B13, B14, B15, and B16 generated by translating the standard spectrum B1 in the wavelength direction (horizontal axis direction in FIG. 25). The first duplicate standard spectrum B11 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by -1 nm. The second duplicate standard spectrum B12 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by −0.5 nm. The third duplicate standard spectrum B13 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by +0.5 nm. The fourth duplicate standard spectrum B14 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by + 1 nm. The fifth duplicate standard spectrum B15 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by +1.5 nm. The sixth duplicate standard spectrum B16 is a spectrum generated by translating the standard spectrum B1 in the wavelength direction by +2 nm. The duplicated standard spectra B11, B12, B13, B14, B15, and B16 are standards generated from standard reflected light obtained by placing the standard sample obtained with the standard spectrum B1 at an atmospheric temperature of about -15 to about 45 ° C. Similar to the spectrum.

In consideration of the above points, the regression equation (general-purpose regression equation) used in the inspection system 15 shown in FIG. 24 is created as follows.
First, in the standard sample detection step S532 of FIG. 12, the standard reflected light from the standard sample placed at a certain atmospheric temperature (for example, 25 ° C.) is acquired. Then, in the standard spectrum generation step S533, the standard spectrum (the second standard spectrum in the example shown in FIG. 12) is calculated based on the standard reflected light. Next, the standard spectrum is translated in the wavelength direction to generate a duplicate standard spectrum. It should be noted that how much the standard spectrum is translated in the wavelength direction when the duplicated standard spectrum is generated is determined based on the ambient temperature at which the inspection system 15 is expected to be placed. For example, if the inspection system 15 is expected to be placed at an ambient temperature of 5 ° C to 35 ° C, a standard spectrum generated based on standard reflected light from a standard sample placed at an ambient temperature of 25 ° C. May be translated by −0.5 nm to +1.0 nm in the wavelength direction (horizontal axis direction in FIG. 25) to generate a duplicate standard spectrum. In this case, it is possible to obtain a duplicate standard spectrum similar to the standard spectrum generated based on the standard reflected light from the standard sample placed at an atmospheric temperature of 5 ° C to 35 ° C.
Next, each of the standard spectrum and the duplicate standard spectrum is subjected to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof, and a plurality of wavelength points are subjected to processing. Calculate each of the multiple parameter values corresponding to.
Then, a plurality of parameter values of each standard sample (parameter values calculated based on the standard spectrum of each standard sample and parameter values calculated based on the duplicated standard spectrum generated from each standard spectrum) and each standard sample. A regression equation expressing the relationship with the molecular weight of the resin material is created using the multivariate analysis method.

By using the general-purpose regression equation thus obtained, it is possible to reduce the influence of the change in the atmospheric temperature on which the object 10 is placed on the predicted molecular weight of the resin material of the object 10. In particular, the predicted molecular weight calculated based on the target reflected light from the object 10 placed at the atmospheric temperature (for example, 25 ° C.) at which the standard reflected light was acquired, and the atmospheric temperature at which the standard reflected light was acquired (for example, 25 ° C.). The difference from the predicted molecular weight calculated based on the target reflected light from the object 10 placed at an ambient temperature other than (° C.) (for example, 0 to 24 ° C., 26 to 40 ° C.) can be reduced. This is predicted based on the target reflected light from the object 10 placed at an atmospheric temperature (for example, 0 to 24 ° C., 26 to 40 ° C.) other than the atmospheric temperature (for example, 25 ° C.) at which the standard reflected light was acquired. Even when the molecular weight is calculated, it means that the predicted molecular weight close to the actual molecular weight of the resin material of the object 10 can be calculated.

In the above-described embodiment, the general-purpose regression equation is created using the standard spectrum and the duplicate standard spectrum, but the present invention is not limited to this. The general-purpose regression equation may be created using only duplicated standard spectra.

In FIG. 26, the resin material of the object 10 calculated by using the inspection system 15 shown in FIG. 2 for the object 10 placed at the atmospheric temperatures of 5 ° C, 15 ° C, 25 ° C and 35 ° C. The relationship between the predicted molecular weight of the above and the actual molecular weight of the resin material is shown. In the example shown in FIG. 26, as the regression equation, a standard regression equation created based on a standard spectrum generated from a standard reflected light from a standard sample placed at an atmospheric temperature of 25 ° C. is used. Further, in FIG. 27, the predicted molecular weight of the resin material of the object 10 calculated by using the inspection system 15 shown in FIG. 24 for the same object 10 placed at the same atmospheric temperature as the example shown in FIG. And the actual molecular weight of the resin material are shown. In the example shown in FIG. 27, as a regression equation, a standard spectrum generated from standard reflected light from a standard sample placed at an ambient temperature of 25 ° C. and the standard spectrum are obtained in the wavelength direction from −0.5 nm to +1.0 nm. A general-purpose regression equation created based on the duplicated standard spectrum generated by translating in the range of is used. As can be understood from FIGS. 26 and 27, when the predicted molecular weight is calculated using the inspection system 15 shown in FIG. 24, the predicted molecular weight is calculated using the inspection system 15 shown in FIG. The difference in the predicted molecular weight depending on the ambient temperature on which the object 10 is placed is small as a whole.

[Effect of the second embodiment]
According to the second embodiment, the regression equation is created based on a plurality of spectra (standard spectrum and duplicate standard spectrum) corresponding to the plurality of standard spectra acquired at various atmospheric temperatures. As a result, the change in the predicted molecular weight due to the change in the atmospheric temperature in which the object 10 is placed is suppressed. In particular, the predicted molecular weight calculated based on the target reflected light from the object 10 placed at the ambient temperature at which the standard reflected light was acquired (eg 25 ° C.) and the ambient temperature at which the standard reflected light was acquired (eg 25 ° C.). The difference from the predicted molecular weight calculated based on the target reflected light from the object 10 placed at an ambient temperature other than (° C.) (for example, 0 to 24 ° C., 26 to 40 ° C.) can be reduced. Then, the predicted molecular weight is determined based on the target reflected light from the object 10 placed at an atmospheric temperature (for example, 0 to 24 ° C, 26 to 40 ° C) other than the atmospheric temperature (for example, 25 ° C) from which the standard reflected light was acquired. Even in the case of calculation, it is possible to calculate the predicted molecular weight close to the actual molecular weight of the resin material of the object 10.

(Modified example of the second embodiment)
In the modification of the second embodiment, the general-purpose regression equation is created by using the standard spectrum generated from the standard reflected light actually acquired at various atmospheric temperatures without using the duplicate standard spectrum. For example, a first standard spectrum, which is a standard spectrum of a standard sample placed at a first atmospheric temperature (for example, 5 ° C.), and a second atmospheric temperature (for example, 15 ° C.) different from the first atmospheric temperature are placed. The second standard spectrum, which is the standard spectrum of the standard sample, and the third standard spectrum, which is the standard spectrum of the standard sample placed at a third atmospheric temperature (for example, 25 ° C.) different from the first and second atmospheric temperatures. And a fourth standard spectrum, which is a standard spectrum of a standard sample placed at a fourth atmospheric temperature (for example, 35 ° C.) different from the first to third atmospheric temperatures, and averaged, smoothed, and normalized. A general-purpose regression equation is created based on the parameter values obtained by performing processing including differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. In this case as well, the same effect as that of the second embodiment can be obtained.

(Third embodiment)
Next, the inspection system according to the third embodiment will be described with reference to FIGS. 28 to 30. The inspection system according to the third embodiment is different from the inspection system 15 according to the first embodiment in that the predicted molecular weight calculated in the determination step S3 is corrected by the temperature-based correction formula. Further, it is different in that the temperature monitor 30 is provided as compared with the inspection system 15 according to the first embodiment. Other points are the same as the inspection system 15 according to the first embodiment. In the third embodiment, the same parts as those of the inspection system 15 according to the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

FIG. 28 is a block diagram showing the inspection system 15 according to the third embodiment. The inspection system 15 shown in FIG. 28 includes a temperature monitor 30. Further, the storage unit 281 of the determination device 28 stores a temperature-based correction formula in addition to the regression equation (standard regression equation in the example shown in FIG. 28).

[Temperature monitor]
The temperature monitor 30 measures the atmospheric temperature of the inspection system 15 (more specifically, the atmospheric temperature in which the spectroscopic module 20 is placed). The temperature monitor 30 may be included in the spectroscopic module 20. The temperature monitor 30 may be housed in a case 40 described later. The temperature monitor 30 may have a structure separated from the spectroscopic module 20 and the case 40. The temperature monitor 30 conveys information about the atmospheric temperature to the determination device 28.

As described above, even if the object 10 is the same, the obtained reflection spectrum may change when the atmospheric temperature at which the object 10 is placed changes. Therefore, the predicted molecular weight of the resin material of the object 10 and the inspection result based on the predicted molecular weight may change depending on the ambient temperature. In this regard, the inventors of the present invention correct the predicted molecular weight calculated based on the regression equation by the temperature-specific correction formula prepared as follows, and thereby the molecular weight (corrected molecular weight) calculated by the inspection system 15. ) Was found to be able to approach the actual molecular weight. That is, it has been found that the accuracy of the inspection is improved by inspecting the state of the object 10 using not only the regression equation but also the temperature-based correction equation. The temperature-based correction formula is recorded in advance in the storage unit 281 of the determination device 28.

[How to create a temperature-based correction formula]
First, a method of creating a temperature-based correction formula will be described.
The standard sample is placed at the first atmospheric temperature (for example, 5 ° C.), and the standard parameter value calculation step S53 shown in FIGS. 11 and 12 is performed. Next, the obtained parameter values are regressed to a regression equation (standard regression equation in the example shown in FIG. 28) to calculate the predicted molecular weight, and a scatter diagram as shown in FIG. 29 is drawn. In FIG. 29, the vertical axis y shows the predicted molecular weight of the resin material of the standard sample obtained based on the regression equation, and the horizontal axis x shows the actual molecular weight of the resin material of the standard sample. Then, an approximate straight line (first approximate line C1) of the scatter plot of the standard sample placed at the first atmospheric temperature is obtained. After that, the first temperature-specific correction formula y1 is obtained so that the slope of the first approximation line C1 is set to 1 and the intercept is set to zero. For example, when the first approximate straight line C1 is represented by y = ax + b, the first temperature-based correction formula is y1 = (y−b) / a.
Similarly, the standard sample is placed at a second atmospheric temperature (for example, 15 ° C.) different from the first atmospheric temperature, and the standard parameter value calculation step S53 shown in FIGS. 11 and 12 is performed. Next, the obtained parameter values are regressed in a regression equation to calculate the predicted molecular weight, and a scatter diagram as shown in FIG. 29 is drawn. Then, an approximate straight line (second approximate line C2) of the scatter plot of the standard sample placed at the second atmospheric temperature is obtained. After that, the second temperature-specific correction formula y2 is obtained so that the slope of the second approximation line C2 is set to 1 and the intercept is set to zero. The method of obtaining the second temperature-based correction formula y2 is the same as the method of obtaining the first temperature-based correction formula y1.
Similarly, the standard sample is placed at a third atmospheric temperature (for example, 25 ° C.) different from the first and second atmospheric temperatures, and the standard parameter value calculation step S53 shown in FIGS. 11 and 12 is performed. Next, the obtained parameter values are regressed in a regression equation to calculate the predicted molecular weight, and a scatter diagram as shown in FIG. 29 is drawn. Then, an approximate straight line (third approximate line C3) of the scatter plot of the standard sample placed at the third atmospheric temperature is obtained. After that, the third temperature-specific correction formula y3 is obtained so that the slope of the third approximation line C3 is set to 1 and the intercept is set to zero. The method of obtaining the third temperature-based correction formula y3 is the same as the method of obtaining the first temperature-based correction formula y1.
Similarly, the standard sample is placed at a fourth atmospheric temperature (for example, 35 ° C.) different from the first to third atmospheric temperatures, and the standard parameter value calculation step S53 shown in FIGS. 11 and 12 is performed. Next, the obtained parameter values are regressed in a regression equation to calculate the predicted molecular weight, and a scatter diagram as shown in FIG. 29 is drawn. Then, an approximate straight line (fourth approximate line C4) of the scatter plot of the standard sample placed at the fourth atmospheric temperature is obtained. After that, the fourth temperature-specific correction formula y4 is obtained so that the slope of the fourth approximation line C4 is set to 1 and the intercept is set to zero. The method for obtaining the fourth temperature-based correction formula y4 is the same as the method for obtaining the first temperature-based correction formula y1.

[Inspection method using temperature-based correction formula]
Next, an inspection method for inspecting the state of the object 10 by using the above-mentioned temperature-based correction formula will be described.
First, the inspection calibration spectrum recording step S1 shown in FIGS. 6 and 7, and the target parameter value calculation step S2 shown in FIGS. 6 and 9 are performed. The target parameter value calculation step S2 includes a temperature measurement step of measuring the atmospheric temperature of the object 10 (more specifically, the atmospheric temperature when the target reflected light L2 is acquired) by the temperature monitor 30.
Next, the determination step S3 shown in FIG. 6 is performed. In the determination step S3, the analysis unit 282 first predicts the predicted molecular weight of the resin material of the object 10 based on the regression equation stored in the storage unit 281 of the determination device 28 and the parameter value calculated in the target parameter value calculation step S2. Is calculated. Further, based on the measured temperature measured by the temperature monitor 30, one of the first to fourth temperature-specific correction formulas y1, y2, y3, and y4 recorded in the storage unit 281 is selected. .. Next, the analysis unit 282 calculates the corrected molecular weight by correcting the predicted molecular weight with the selected temperature correction formula.
Finally, the determination unit 283 determines the state of the object 10 based on the corrected molecular weight.

The storage unit 281 stores in advance information regarding the correspondence between the atmospheric temperature of the object 10 and the temperature correction formulas y1, y2, y3, and y4. For example, the information that the temperature correction formula corresponding to the atmospheric temperature of less than 10 ° C. is the first temperature-specific correction formula y1 is stored. Further, the information that the temperature correction formula corresponding to the atmospheric temperature of 10 ° C. or higher and lower than 20 ° C. is the second temperature-specific correction formula y2 is stored. Further, the information that the temperature correction formula corresponding to the atmospheric temperature of 20 ° C. or higher and lower than 30 ° C. is the third temperature-specific correction formula y3 is stored. Further, the information that the temperature correction formula corresponding to the atmospheric temperature of 30 ° C. or higher is the fourth temperature-specific correction formula y4 is stored. In this case, if the atmospheric temperature of the object 10 is less than 10 ° C., the analysis unit 282 corrects the predicted molecular weight by the first temperature-based correction formula y1 to calculate the corrected molecular weight. If the atmospheric temperature of the object 10 is 10 ° C. or higher and lower than 20 ° C., the analysis unit 282 corrects the predicted molecular weight by the second temperature-specific correction formula y2 to calculate the corrected molecular weight. If the atmospheric temperature of the object 10 is 20 ° C. or higher and lower than 30 ° C., the analysis unit 282 corrects the predicted molecular weight by the third temperature-specific correction formula y3 to calculate the corrected molecular weight. If the atmospheric temperature of the object 10 is 30 ° C. or higher, the analysis unit 282 corrects the predicted molecular weight by the fourth temperature-specific correction formula y4 to calculate the corrected molecular weight.

FIG. 30 shows the corrected molecular weight of the resin material of the object 10 calculated by using the inspection system 15 shown in FIG. 28 for the same object 10 placed at the same atmospheric temperature as the example shown in FIG. The relationship with the actual molecular weight of the resin material is shown. As can be seen from FIGS. 26 and 30, the corrected molecular weight calculated using the test system 15 shown in FIG. 28 is subject to comparison with the predicted molecular weight calculated using the test system 15 shown in FIG. The difference due to the atmospheric temperature on which the object 10 was placed is small as a whole. This means that according to the inspection system 15 shown in FIG. 28, it is possible to suppress the change in the inspection result depending on the atmospheric temperature in which the object 10 is placed.

[Effect of the third embodiment]
According to the third embodiment, the object 10 is inspected using the corrected molecular weight obtained by correcting the predicted molecular weight by the temperature-based correction formula. As a result, it is possible to prevent the inspection result from changing depending on the atmospheric temperature at which the object 10 is placed.

(Fourth Embodiment)
The inspection system 15 according to the fourth embodiment will be described with reference to FIGS. 31 and 32. The inspection system 15 according to the fourth embodiment is different from the inspection system 15 according to the third embodiment in that the regression equation of the second embodiment is used as the regression equation. Other points are the same as the inspection system 15 of the third embodiment.

FIG. 31 is a block diagram showing an inspection system 15 according to a fourth embodiment. The inspection system 15 shown in FIG. 31 includes a temperature monitor 30. Further, the storage unit 281 of the determination device 28 stores a general-purpose regression equation and a temperature-based correction equation.

FIG. 32 shows the corrected molecular weight of the resin material of the object 10 calculated by using the inspection system 15 shown in FIG. 31 for the same object 10 placed at the same atmospheric temperature as the example shown in FIG. The relationship with the actual molecular weight of the resin material is shown. As can be seen from FIGS. 26 and 32, the corrected molecular weight calculated using the test system 15 shown in FIG. 31 is subject to comparison with the predicted molecular weight calculated using the test system 15 shown in FIG. The difference due to the atmospheric temperature on which the object 10 was placed is small as a whole. This means that according to the inspection system 15 shown in FIG. 31, it is possible to suppress the change in the inspection result depending on the atmospheric temperature in which the object 10 is placed.

Further, as can be seen from FIGS. 30 and 32, the corrected molecular weight calculated using the inspection system 15 shown in FIG. 31 is compared with the corrected molecular weight calculated using the inspection system 15 shown in FIG. 28. , It turns out that it is close to the actual molecular weight. This means that according to the inspection system 15 shown in FIG. 31, the object 10 can be inspected with higher accuracy.

[Effect of the fourth embodiment]
According to the fourth embodiment, as a regression equation, a regression equation created based on a plurality of spectra (standard spectrum and duplicate standard spectrum) corresponding to a plurality of standard spectra acquired at various atmospheric temperatures is used. I am using it. Then, the predicted molecular weight calculated based on the regression equation is corrected by the temperature-based correction formula to calculate the corrected molecular weight, and the object 10 is inspected using the corrected molecular weight. As a result, not only can the inspection result be suppressed from changing depending on the atmospheric temperature on which the object 10 is placed, but also the object 10 can be inspected with higher accuracy.

(Fifth Embodiment)
The inspection system 15 according to the fifth embodiment will be described with reference to FIG. 33. The inspection system 15 according to the fifth embodiment is different from the inspection system 15 according to the first embodiment in that it includes a temperature monitor 30. Further, the inspection system 15 according to the fifth embodiment has a different regression equation used in the determination step S3 depending on the ambient temperature at which the object 10 is placed, as compared with the inspection system 15 according to the first embodiment. Is different. Other points are the same as the inspection system 15 of the first embodiment. In the fifth embodiment, the same parts as those of the inspection system 15 according to the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

FIG. 33 is a block diagram showing the inspection system 15 according to the fifth embodiment. The inspection system 15 shown in FIG. 33 includes a temperature monitor 30 similar to the temperature monitor 30 shown in FIG. 28. Further, the storage unit 281 of the determination device 28 stores a plurality of regression equations.

As described above, even if the object 10 is the same, the obtained reflection spectrum may change when the atmospheric temperature at which the object 10 is placed changes. Therefore, the predicted molecular weight of the resin material of the object 10 and the inspection result based on the predicted molecular weight may change depending on the ambient temperature. In this regard, the inventors prepare a plurality of regression equations different from each other and calculate the predicted molecular weight using different regression equations according to the atmospheric temperature in which the object 10 is placed to actually obtain the predicted molecular weight. It was found that it can be approached to the molecular weight of.
More specifically, the first regression equation created based on the first standard spectrum generated from the standard reflected light of the standard sample placed at the first atmospheric temperature and the second atmospheric temperature are placed. Prepare a second regression equation created based on the second standard spectrum generated from the standard reflected light of the standard sample. Then, one regression equation is selected from the first regression equation and the second regression equation according to the atmospheric temperature measured by the temperature monitor 30 when the target reflected light of the object 10 is acquired. The predicted molecular weight is calculated using the selected regression equation.

In the illustrated example, the storage unit 281 of the control device 28 stores the first regression equation, the second regression equation, the third regression equation, and the fourth regression equation.
The first regression equation is a standard spectrum generated from the standard reflected light of a standard sample placed at an atmospheric temperature of 5 ° C (that is, a standard spectrum generated from the standard reflected light obtained at an atmospheric temperature of 5 ° C). It is created based on.
The second regression equation is a standard spectrum generated from the standard reflected light of a standard sample placed at an atmospheric temperature of 15 ° C. (ie, a standard spectrum generated from the standard reflected light obtained at an atmospheric temperature of 15 ° C.). It is created based on.
The third regression equation is a standard spectrum generated from the standard reflected light of a standard sample placed at an atmospheric temperature of 25 ° C. (that is, a standard spectrum generated from the standard reflected light obtained at an atmospheric temperature of 25 ° C.). It is created based on.
The fourth regression equation is a standard spectrum generated from the standard reflected light of a standard sample placed at an atmospheric temperature of 35 ° C. (that is, a standard spectrum generated from the standard reflected light obtained at an atmospheric temperature of 35 ° C.). It is created based on.

[Inspection method using multiple regression equations]
Next, an inspection method for inspecting the state of the object 10 by using the above-mentioned plurality of regression equations will be described.
First, the inspection calibration spectrum recording step S1 shown in FIGS. 6 and 7, and the target parameter value calculation step S2 shown in FIGS. 6 and 9 are performed. The target parameter value calculation step S2 includes a temperature measurement step of measuring the atmospheric temperature of the object 10 (more specifically, the atmospheric temperature when the target reflected light L2 is acquired) by the temperature monitor 30.
Next, the determination step S3 shown in FIG. 6 is performed. In the determination step S3, first, the analysis unit 282 of the control device 28 is in the first to fourth regression equations according to the atmospheric temperature measured by the temperature monitor 30 when the target reflected light L2 is acquired. Select one regression equation from. Next, the analysis unit 282 calculates the predicted molecular weight based on the selected regression equation.
Finally, the determination unit 283 determines the state of the object 10 based on the predicted molecular weight.

The storage unit 281 stores in advance information regarding the correspondence between the atmospheric temperature of the object 10 and the first to fourth regression equations. For example, the information that the regression equation corresponding to the atmospheric temperature of less than 10 ° C. is the first regression equation is stored. Further, the information that the regression equation corresponding to the atmospheric temperature of 10 ° C. or higher and lower than 20 ° C. is the second regression equation is stored. Further, the information that the regression equation corresponding to the atmospheric temperature of 20 ° C. or higher and lower than 30 ° C. is the third regression equation is stored. Further, the information that the regression equation corresponding to the atmospheric temperature of 30 ° C. or higher is the fourth regression equation is stored. In this case, if the atmospheric temperature of the object 10 is less than 10 ° C., the analysis unit 282 selects the first regression equation from the first to fourth regression equations and is based on the first regression equation. To calculate the predicted molecular weight. If the atmospheric temperature of the object 10 is 10 ° C. or higher and lower than 20 ° C., the analysis unit 282 selects the second regression equation from the first to fourth regression equations, and the second regression equation. The predicted molecular weight is calculated based on. If the atmospheric temperature of the object 10 is 20 ° C. or higher and lower than 30 ° C., the analysis unit 282 selects a third regression equation from the first to fourth regression equations, and the third regression equation. The predicted molecular weight is calculated based on. Further, if the atmospheric temperature of the object 10 is 30 ° C. or higher, the analysis unit 282 selects a fourth regression equation from the first to fourth regression equations, and based on the fourth regression equation. Calculate the predicted molecular weight.

[Effect of the fifth embodiment]
According to the fifth embodiment, a plurality of regression equations different from each other are prepared, and the predicted molecular weight is calculated using different regression equations according to the atmospheric temperature in which the object 10 is placed. As a result, the predicted molecular weight calculated by the inspection system 15 can be brought close to the actual molecular weight. Then, by inspecting the object 10 using the predicted molecular weight calculated in this way, it is possible to suppress the change in the inspection result depending on the atmospheric temperature in which the object 10 is placed.

(Sixth Embodiment)
The inspection system 15 according to the sixth embodiment is devised to suppress the movement of the case 40 during the inspection process as compared with the inspection system 15 according to the first embodiment. As a result, it is possible to suppress the possibility of noise occurring in the target spectrum or the calibration spectrum. Other points are the same as the inspection system 15 of the first embodiment.

FIG. 34 is a perspective view showing an example of the case 40 of the inspection system 15 according to the sixth embodiment. As shown in FIG. 34, the case 40 includes a first friction layer 53 provided on the first surface 41 or the outer edge. In the example shown in FIG. 34, the first friction layer 53 is provided on the first surface 41 along the third outer edge 413 and the fourth outer edge 414.

The static friction force between the first friction layer 53 and the object 10 is larger than the static friction force between the first surface 41 and the object 10. By providing the first friction layer 53 in the case 40, it is possible to prevent the case 40 from moving during the inspection process. As a result, it is possible to suppress the appearance of noise generated by the movement of the hand or the like in the target spectrum or the calibration spectrum.

The configuration of the first friction layer 53 is arbitrary. For example, the first friction layer 53 may be composed of a layer on the surface of the tape attached to the first surface 41. The tape is a non-slip tape made by Meist Co., Ltd. Item No. 5187 and the like can be used.

(Modified example of the sixth embodiment)
The inspection system 15 according to the modified example of the sixth embodiment is also devised to prevent the case 40 from moving during the inspection process. The inspection system 15 according to the modification of the sixth embodiment is different from the inspection system 15 of the sixth embodiment in that the support member 54 is provided in place of the first friction layer 53. .. Other points are the same as the inspection system 15 of the sixth embodiment.

FIG. 35 is a perspective view showing an example of the case 40 of the inspection system 15 according to the modified example of the sixth embodiment. As shown in FIG. 35, the case 40 includes a support member 54 fixed to the side surface. In the example shown in FIG. 35, the case 40 includes one support member 54 fixed to the first side surface 43 and two support members 54 fixed to the second side surface 44. Although not shown, the case 40 may include one or two support members 54, or may include four or more support members 54. The support member 54 may be fixed to the third side surface 45 or the fourth side surface 46.

The support member 54 may include a first portion 541 fixed to the side surface and a second portion 542 connected to the first portion 541. The first portion 541 may extend from the side surface toward the first surface 41. The second portion 542 may include a surface extending parallel to the first surface 41. The second portion 542 may come into contact with the object 10 during the inspection process. As a result, the posture of the case 40 can be maintained more stably during the inspection process. Therefore, it is possible to suppress the appearance of noise generated by the movement of the hand or the like in the target spectrum or the calibration spectrum.

As shown in FIG. 35, the case 40 may include a second friction layer 55 provided in the second portion 542. The second friction layer 55 contains, for example, rubber. The second friction layer 55 may come into contact with the object 10 during the inspection step. The static friction force between the second friction layer 55 and the object 10 is larger than the static friction force between the first surface 41 and the object 10. By providing the second friction layer 55 in the second portion 542, it is possible to further suppress the movement of the case 40 during the inspection process.

Although some modifications to the above-described embodiments have been described above, it is naturally possible to apply a plurality of modifications in combination as appropriate.

10 Object 10x 1st surface 10y 2nd surface 11 Base sheet 12 Resin layer 15 Inspection system 20 Spectro module 21 Irradiation device 211 Irradiation unit 24 Detection device 241 Detection unit 25 Generation device 251 First generation unit 252 Second generation unit 27 Processing device 271 1st processing unit 272 2nd processing unit 28 Judgment device 281 Storage unit 282 Analysis unit 283 Judgment unit 29 Cooling unit 30 Temperature monitor 40 Case 41 1st surface 42 2nd surface 48 Window 51 Calibration sample 53 1st friction layer 54 Support member 541 First part 542 Second part 55 Second friction layer

Claims (31)

An inspection system that inspects the condition of an object having a resin layer containing a resin material.
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
A cooling unit that cools the irradiation device and / or the detection device,
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, the regression equation of the storage unit, and a plurality of parameter values of the resin layer calculated by the processing apparatus. An inspection system including an analysis unit for calculating a predicted molecular weight of the resin material of the resin layer, and a determination unit for determining the state of the object based on the predicted molecular weight. The inspection system according to claim 1, wherein the cooling unit is a blower. An inspection system that inspects the condition of an object having a resin layer containing a resin material.
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, the regression equation of the storage unit, and a plurality of parameter values of the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating the predicted molecular weight of the resin material of the resin layer and a determination unit for determining the state of the object based on the predicted molecular weight is provided.
The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by applying the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. An inspection system created by The inspection system according to claim 3, wherein the duplicated standard spectrum is generated by translating the standard spectrum in the range of −0.5 nm to +1.0 nm in the wavelength direction. An inspection system that inspects the condition of an object having a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
Based on a storage unit in which a regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material is stored in advance, the regression equation of the storage unit, and a plurality of parameter values of the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating the predicted molecular weight of the resin material of the resin layer and a determination unit for determining the state of the object based on the predicted molecular weight is provided.
The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring a value obtained at a plurality of wavelength points by performing a process including a combination thereof and the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. , Peak shift correction, or an inspection system created based on the values obtained at a plurality of wavelength points by performing a process including a combination thereof. The regression equation is a value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averaged, smoothed, normalized, differentiated, and scattered to the first standard spectrum. A value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmission at the plurality of wavelength points of the second standard spectrum. Multiple wavelengths by subjecting the second standard spectrum to a value of light intensity or processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at the point and the third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the third standard spectrum. The inspection system according to claim 5, which is created based on the values obtained at a plurality of wavelength points by performing a process including a combination thereof. An inspection system that inspects the condition of an object having a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
A storage unit in which a plurality of regression equations including a first regression equation and a second regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material are stored in advance, and the first regression equation of the storage unit. And the resin material of the resin layer based on one regression equation selected from the plurality of regression equations including the second regression equation and a plurality of parameter values of the resin layer calculated by the processing apparatus. A determination device including an analysis unit for calculating a predicted molecular weight, a determination unit for determining the state of the object based on the predicted molecular weight, and a determination device.
The first regression equation is obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of one standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, and peak to the first standard spectrum. It is created based on the values obtained at multiple wavelength points by performing shift correction or processing including a combination thereof.
The second regression equation is the said at a plurality of wavelength points of the second standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. Processing including standard reflected light or the value of the intensity of the standard transmitted light, or the second standard spectrum including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Is created based on the values obtained at multiple wavelength points.
The analysis unit includes the first regression equation and the second regression equation according to the atmospheric temperature measured by the temperature monitor when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations, and the prediction of the resin material of the resin layer is based on the selected regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. An inspection system that calculates the molecular weight. The plurality of the regression equations include the first regression equation, the second regression equation, and a third regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material.
The third regression equation is a third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. Intensity value of the standard reflected light or the standard transmitted light at a plurality of wavelength points of, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, to the third standard spectrum. Or it is created based on the values obtained at multiple wavelength points by performing a process including a combination thereof.
The analysis unit has the first regression equation, the second regression equation, and the second regression equation according to the atmospheric temperature measured by the temperature monitor when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including the third regression equation, and the said regression equation is based on the selected regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. The inspection system according to claim 7, wherein the predicted molecular weight of the resin material of the resin layer is calculated. An inspection system that inspects the condition of an object having a resin layer containing a resin material.
A temperature monitor that measures the ambient temperature,
An irradiation device including an irradiation unit that irradiates the object with irradiation light,
A detection device that detects the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light.
A generator that generates an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing device that calculates the values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point.
A regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material, and a predicted molecular weight of the resin material of the resin layer calculated based on the regression equation and the plurality of parameter values of the resin layer calculated by the processing apparatus. A storage unit in which a temperature-specific correction formula for correcting the above atmospheric temperature is stored in advance, and a corrected molecular weight obtained by calculating the predicted molecular weight and correcting the predicted molecular weight according to the atmospheric temperature by the temperature-based correction formula. An inspection system including an analysis unit for calculating the above, a determination unit for determining the state of the object based on the corrected molecular weight, and a determination device including the determination unit. The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. 9. The inspection system according to claim 9. The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring the values obtained at a plurality of wavelength points by performing the treatment including the combination thereof and the reflected light or transmitted light of the standard sample at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. The inspection system according to claim 9, wherein the inspection system is created based on the values obtained at a plurality of wavelength points by performing a process including peak shift correction or a combination thereof. The regression equation is a value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averaged, smoothed, normalized, differentiated, and scattered to the first standard spectrum. A value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmission at the plurality of wavelength points of the second standard spectrum. Multiple wavelengths by subjecting the second standard spectrum to a value of light intensity or processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at the point and the third standard spectrum obtained by acquiring the reflected light or transmitted light of the standard sample at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the third standard spectrum. The inspection system according to claim 11, which is created based on the values obtained at a plurality of wavelength points by performing a process including a combination thereof. The inspection system according to any one of claims 3 to 12, further comprising a cooling unit for cooling the irradiation device and / or the detection device. An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
An irradiation step of irradiating the object with irradiation light using an irradiation device, and
A detection step of detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light by a detection device.
A cooling step for cooling the irradiation device and / or the detection device, and
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. An inspection method comprising a determination step of determining the state of the object based on the molecular weight. An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. A determination step of determining the state of the object based on the molecular weight is provided.
The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by applying the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Inspection method created by. The inspection method according to claim 15, wherein the duplicated standard spectrum is generated by translating the standard spectrum in the range of −0.5 nm to +1.0 nm in the wavelength direction. An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. A determination step of determining the state of the object based on the molecular weight is provided.
The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring a value obtained at a plurality of wavelength points by performing a process including a combination thereof and the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. , Peak shift correction, or an inspection method created based on the values obtained at a plurality of wavelength points by performing a process including a combination thereof. The regression equation is a value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averaged, smoothed, normalized, differentiated, and scattered to the first standard spectrum. A value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmission at the plurality of wavelength points of the second standard spectrum. Multiple wavelengths by subjecting the second standard spectrum to a value of light intensity or processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at the point and the third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the third standard spectrum. The inspection method according to claim 17, which is created based on a value obtained at a plurality of wavelength points by performing a process including a combination thereof. An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
The temperature measurement process to measure the atmospheric temperature and
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
One regression equation selected from a plurality of regression equations including a first regression equation and a second regression equation showing the relationship between a plurality of parameter values and the molecular weight of the resin material, and the calculation calculated in the processing step. A determination step of calculating the predicted molecular weight of the resin material of the resin layer based on a plurality of parameter values of the resin layer and determining the state of the object based on the predicted molecular weight is provided.
The first regression equation is obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, and peak shift to the first standard spectrum. Created based on values obtained at multiple wavelength points by correction or processing including combinations thereof.
The second regression equation is the said at a plurality of wavelength points of the second standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. Processing including standard reflected light or the value of the intensity of the standard transmitted light, or the second standard spectrum including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. Is created based on the values obtained at multiple wavelength points.
In the determination step, the first regression equation and the second regression equation are performed according to the atmospheric temperature measured in the temperature measuring step when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including, and the predicted molecular weight of the resin material of the resin layer is predicted based on the selected regression equation and the plurality of parameter values calculated in the processing step. The inspection method to calculate. The plurality of the regression equations include the first regression equation, the second regression equation, and a third regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material.
The third regression equation is a third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. Intensity value of the standard reflected light or the standard transmitted light at a plurality of wavelength points of, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, to the second standard spectrum. Or it is created based on the values obtained at multiple wavelength points by performing a process including a combination thereof.
In the determination step, the first regression equation and the second regression equation are obtained according to the atmospheric temperature measured in the temperature measuring step when the reflected light or the transmitted light of the object is acquired. One regression equation is selected from the plurality of regression equations including the third regression equation, and the resin is based on the selected regression equation and the plurality of parameter values calculated in the processing step. The inspection method according to claim 19, wherein the predicted molecular weight of the resin material of the layer is calculated. An inspection method for inspecting the condition of an object having a resin layer containing a resin material.
The temperature measurement process to measure the atmospheric temperature and
The irradiation step of irradiating the object with irradiation light and
A detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating the object with the irradiation light, and a detection step.
A generation step of generating an object spectrum containing information about the intensity of the reflected or transmitted light at multiple wavelength points.
Intensity values of the reflected or transmitted light at multiple wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or a combination thereof in the target spectrum. A processing step of calculating values obtained at a plurality of wavelength points by performing the including processing as a plurality of parameter values corresponding to each wavelength point, and a processing step.
The predicted molecular weight of the resin material of the resin layer is calculated based on the regression equation showing the relationship between the plurality of parameter values and the molecular weight of the resin material and the plurality of parameter values of the resin layer calculated in the processing step, and the prediction is made. The present invention comprises a determination step of calculating a corrected molecular weight by correcting the molecular weight by a temperature-based correction formula according to the atmospheric temperature measured in the temperature measuring step and determining the state of the object based on the corrected molecular weight. ,Inspection methods. The regression equation is a plurality of wavelengths of a standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a predetermined ambient temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a point, or the standard spectrum includes averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at a plurality of wavelength points by the treatment, the value of the light intensity represented by the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the value at a plurality of wavelength points. Based on the values obtained at a plurality of wavelength points by subjecting the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. 21. The inspection method according to claim 21. The regression equation is a first standard spectrum obtained by acquiring standard reflected light or standard transmitted light which is reflected light or transmitted light of a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the first standard spectrum. Obtained by acquiring a value obtained at a plurality of wavelength points by performing a process including a combination thereof and the standard reflected light or the standard transmitted light at a second atmospheric temperature different from the first atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the second standard spectrum, or averaging, smoothing, normalizing, differentiating, scattering correction, and baseline correction to the second standard spectrum. The inspection method according to claim 21, wherein the inspection method is created based on a value obtained at a plurality of wavelength points by performing a process including peak shift correction or a combination thereof. The regression equation is a value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points of the first standard spectrum, or averaged, smoothed, normalized, differentiated, and scattered to the first standard spectrum. A value obtained at a plurality of wavelength points by performing a process including correction, baseline correction, peak shift correction, or a combination thereof, and the standard reflected light or the standard transmission at the plurality of wavelength points of the second standard spectrum. Multiple wavelengths by subjecting the second standard spectrum to a value of light intensity or processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. The value obtained at the point and the third standard spectrum obtained by acquiring the standard reflected light or the standard transmitted light at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature. The value of the intensity of the standard reflected light or the standard transmitted light at a plurality of wavelength points, or averaging, smoothing, normalizing, differentiating, scattering correction, baseline correction, peak shift correction, or the second standard spectrum. 23. The inspection method according to claim 23, which is created based on a value obtained at a plurality of wavelength points by performing a process including a combination thereof. The irradiation light is irradiated by an irradiation device and
The intensity of the reflected light or the transmitted light is detected by the detection device, and the intensity is detected.
The inspection method according to any one of claims 12 to 18, further comprising a cooling step for cooling the irradiation device and / or the detection device. The method for manufacturing an inspection system according to any one of claims 1, 2 and 9.
A standard sample irradiation step of irradiating a plurality of standard samples containing a resin material having a known molecular weight with irradiation light, and
A standard sample detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating a plurality of the standard samples with the irradiation light, and a standard sample detection step.
A standard spectrum generation step of acquiring a plurality of standard spectra, each containing information regarding the intensity of the reflected light or the transmitted light at a plurality of wavelength points.
Intensity values of the reflected light or transmitted light at multiple wavelength points of the plurality of standard spectra, or averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, for each of the plurality of standard spectra. A standard sample processing step in which values obtained at a plurality of wavelength points by performing a peak shift correction or a process including a combination thereof are calculated as a plurality of parameter values corresponding to each wavelength point, respectively.
A method for manufacturing an inspection system, comprising an analysis step of creating a regression equation expressing the relationship between a plurality of parameter values of each standard sample and the molecular weight of the resin material of each standard sample using a multivariate analysis method. The method for manufacturing an inspection system according to claim 3 or 10.
A standard sample irradiation step of irradiating a plurality of standard samples containing a resin material having a known molecular weight with irradiation light, and
A standard sample detection step for detecting the intensity of reflected light or transmitted light obtained by irradiating a plurality of the standard samples with the irradiation light, and a standard sample detection step.
A standard spectrum generation step of acquiring a plurality of standard spectra, each containing information regarding the intensity of the reflected light or the transmitted light at a plurality of wavelength points.
The value of the intensity of the reflected or transmitted light at a plurality of wavelength points of the intensity of the light represented by the standard spectrum and the duplicated standard spectrum generated by moving the standard spectrum in parallel in the wavelength direction, or the above. It is obtained at a plurality of wavelength points by subjecting each of the standard spectrum and the duplicated standard spectrum to a process including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof. A standard sample processing step in which values are calculated as multiple parameter values corresponding to each wavelength point, and
A method for manufacturing an inspection system, comprising an analysis step of creating a regression equation expressing the relationship between a plurality of the parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method. The method for manufacturing an inspection system according to claim 5 or 11.
A first standard sample irradiation step of irradiating a plurality of standard samples with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
An analysis step for creating a regression equation expressing the relationship between a plurality of the first standard parameter values and a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample using a multivariate analysis method. And, the manufacturing method of the inspection system. The method for manufacturing an inspection system according to claim 6 or 12.
A first standard sample irradiation step of irradiating a plurality of standard samples with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A third standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature.
A third standard reflected light or a third standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the third atmospheric temperature with the irradiation light, is detected. 3 Standard sample detection process and
A third standard spectrum generation step of acquiring a plurality of third standard spectra, each containing information on the intensity of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points.
Intensity values of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points of the plurality of the third standard spectra, or averaged, smoothed, and normalized to each of the plurality of the third standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of third standard parameter values corresponding to each wavelength point. The third standard sample processing step to be calculated respectively, and
A regression equation expressing the relationship between the plurality of the first standard parameter values, the plurality of the second standard parameter values, and the plurality of the third standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample is multivariate. A manufacturing method of an inspection system including an analysis process created by using an analysis method. The method for manufacturing an inspection system according to claim 7.
A first standard sample irradiation step of irradiating the standard sample with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A first analysis step of creating a first regression equation expressing the relationship between a plurality of the first standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A second analysis step of creating a second regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method is provided. , How to manufacture the inspection system. The method for manufacturing an inspection system according to claim 8.
A first standard sample irradiation step of irradiating the standard sample with irradiation light by placing a plurality of standard samples containing a resin material having a known molecular weight at a first atmospheric temperature.
A first standard reflected light or a first standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the first atmospheric temperature with the irradiation light, is detected. 1 Standard sample detection process and
A first standard spectrum generation step of acquiring a plurality of first standard spectra, each containing information about the intensity of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points.
Intensity values of the first standard reflected light or the first standard transmitted light at a plurality of wavelength points of the plurality of the first standard spectra, or averaged, smoothed, and normalized to each of the plurality of the first standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of first standard parameter values corresponding to each wavelength point. The first standard sample processing step to be calculated respectively, and
A first analysis step of creating a first regression equation expressing the relationship between a plurality of the first standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A second standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a second atmospheric temperature different from the first atmospheric temperature.
A second standard reflected light or a second standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the second atmospheric temperature with the irradiation light, is detected. 2 Standard sample detection process and
A second standard spectrum generation step of acquiring a plurality of second standard spectra, each containing information about the intensity of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points.
Intensity values of the second standard reflected light or the second standard transmitted light at a plurality of wavelength points of the plurality of the second standard spectra, or averaged, smoothed, and normalized to each of the plurality of the second standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of second standard parameter values corresponding to each wavelength point. The second standard sample processing step to be calculated respectively, and
A second analysis step of creating a second regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A third standard sample irradiation step of irradiating the plurality of standard samples with irradiation light by placing the plurality of the standard samples at a third atmospheric temperature different from the first atmospheric temperature and the second atmospheric temperature.
A third standard reflected light or a third standard transmitted light, which is a reflected light or a transmitted light obtained by irradiating a plurality of the standard samples placed at the third atmospheric temperature with the irradiation light, is detected. 3 Standard sample detection process and
A third standard spectrum generation step of acquiring a plurality of third standard spectra, each containing information on the intensity of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points.
Intensity values of the third standard reflected light or the third standard transmitted light at a plurality of wavelength points of the plurality of the third standard spectra, or averaged, smoothed, and normalized to each of the plurality of the third standard spectra. The values obtained at a plurality of wavelength points by performing a process including conversion, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof are used as a plurality of third standard parameter values corresponding to each wavelength point. The third standard sample processing step to be calculated respectively, and
A third analysis step of creating a third regression equation expressing the relationship between a plurality of the second standard parameter values of each standard sample and the molecular weight of the resin material of each standard sample by using a multivariate analysis method.
A method of manufacturing an inspection system.

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