WO2021149762A1 - Oil state diagnostic method and oil state diagnostic device - Google Patents

Abstract

In the present invention, an oil state is diagnosed by: acquiring a Raman spectrum of an oil (S102); calculating at least one value obtained by normalizing a prescribed peak intensity in the acquired Raman spectrum by a peak intensity derived from a saturated alkane in the Raman spectrum (S103); and diagnosing the oil state from the at least one normalized value that was calculated, on the basis of a correlation between the oil state and the value obtained by normalizing the prescribed peak intensity in the Raman spectrum of the oil calculated in advance by the peak intensity derived from the saturated alkane in the Raman spectrum (S104).

Description

Oil condition diagnosis method and oil condition diagnosis device

This disclosure relates to an oil condition diagnosis method and an oil condition diagnosis device for diagnosing the condition of oil used in mechanical devices and the like.

Conventionally, the mainstream method for analyzing oils such as lubricating oil and engine oil in machinery is to sample the oil from the machinery and request an analysis from a specialized inspection agency. However, it is troublesome because it is necessary to stop the operation of the mechanical device in order to sample the oil from the mechanical device. In addition, it takes time for the results to be returned after the oil sample is sent to a specialized inspection agency. Therefore, there is a demand for a method and an apparatus for diagnosing the state of the oil by analyzing the oil in the mechanical device relatively easily.

For example, Patent Document 1 discloses a deterioration degree evaluation method and a deterioration degree evaluation device for turbine oil using infrared absorption spectroscopy. In the technique described in Patent Document 1, the ^{rate of change from the new oil in the absorbance of the comparative absorption peak near the wave number of 720 cm -1 of the} turbine oil is obtained, and the absorbance of the oxide absorption peak is corrected based on this rate of change. The total acid value corresponding to the absorbance of the corrected oxide absorption peak is obtained, and the degree of deterioration of the turbine oil is evaluated from this total acid value.

Japanese Unexamined Patent Publication No. 2003-0287993

According to the prior art described in Patent Document 1, in order to obtain the rate of change from the new oil in the absorbance of the comparative absorption peak near ^{the wave number of 720 cm -1 of the turbine oil, the turbine oil is used in the new oil state before being used.} It is necessary to measure the absorbance of the absorption peak, which is troublesome. Further, it is disclosed that the prior art described in Patent Document 1 is not very effective even when applied to an engine oil such as diesel oil. That is, in the prior art described in Patent Document 1, depending on the type of oil, the degree of deterioration of the oil (hereinafter, also referred to as the state of the oil) may not be accurately evaluated.

Therefore, the present disclosure provides an oil state diagnosis method and an oil state diagnosis device that can easily and accurately diagnose the oil state.

In the oil state diagnosis method according to one aspect of the present disclosure, a Raman spectrum of oil is acquired, and the intensity of a peak derived from saturated alcan in the Raman spectrum is standardized with respect to the intensity of a predetermined peak in the acquired Raman spectrum. At least one of the normalized values is calculated, and the value and the state of the oil normalized by the intensity of the peak derived from the saturated Alcan in the Raman spectrum with respect to the pre-calculated intensity of the predetermined peak in the Raman spectrum of the oil. The state of the oil is diagnosed from the calculated at least one standardized value based on the correlation with.

Further, the oil state diagnostic apparatus according to one aspect of the present disclosure is derived from an acquisition unit that acquires a Raman spectrum of oil and a saturated alkane in the Raman spectrum with respect to the intensity of a predetermined peak in the acquired Raman spectrum. A calculation unit that calculates at least one value normalized by the peak intensity, and the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the pre-calculated intensity of the predetermined peak in the Raman spectrum of the oil. It includes a storage unit that stores the correlation between the standardized value and the oil state, and a diagnostic unit that diagnoses the oil state from at least one standardized value calculated based on the correlation. ..

It should be noted that these comprehensive or specific aspects may be realized by a system, a device, a method, an integrated circuit, a computer program, or a non-temporary recording medium such as a computer-readable CD-ROM, and the system. , Devices, methods, integrated circuits, computer programs, and any combination of recording media.

According to the present disclosure, an oil condition diagnosis method and an oil condition diagnosis device capable of diagnosing an oil condition easily and accurately are provided.

FIG. 1 is a diagram showing an example of a flow of Raman spectroscopic analysis. FIG. 2 is a diagram showing Raman spectra of oils having different usage times measured in step S001. FIG. 3 is a diagram showing a spectrum of Raman scattered light obtained by removing fluorescence noise from the Raman spectrum of FIG. 2 in step S002. FIG. 4 is a diagram for explaining measurement problems that may occur depending on the state of oil. FIG. 5 is a block diagram showing an example of the functional configuration of the oil state diagnostic apparatus according to the embodiment. FIG. 6 is a flowchart showing an example of the oil state diagnosis method according to the embodiment. FIG. 7 is a schematic view showing an example of the configuration of the laser Raman spectroscopic measuring device. FIG. 8 is a schematic cross-sectional view taken along the line AA of the sample plate of FIG. FIG. 9 is a diagram showing the data of the first embodiment. FIG. 10 is a diagram showing an example of an oil state diagnosis system including the oil state diagnosis device according to the present disclosure.

(Findings leading to this disclosure)
The oil used in the mechanical device has a lubricating action that lubricates the movement of each part in the mechanical device, for example, a sealing action that seals the gap between the piston and the piston silling to prevent gas leakage and keeps airtightness, combustion, etc. It has a cooling action that absorbs and releases the generated heat, a cleaning and dispersing action that takes in dirt generated by combustion, and an anticorrosion action that protects the mechanical device from corrosion such as rust. Due to the reduction of these actions, a malfunction of the mechanical device occurs. Therefore, it is necessary to grasp the state of oil in the mechanical device and replace it with new oil at an appropriate time.

Analysis of oil used in machinery is usually performed for the following purposes. The purpose of the analysis is, for example, to determine an appropriate oil change time, to grasp the state of a mechanical device, to detect a sign of a mechanical device failure, and to detect a mechanical device failure. To identify the state of the device and the cause of the failure. The analysis of oil determines the analysis method and the analysis target in the oil according to these purposes. For example, analysis of oil oxidation and degradation is performed by infrared absorption spectroscopy or gas chromatography.

However, these analyzers are generally large and very expensive, and lack versatility. Further, if these analyzers are miniaturized, the analysis accuracy is lowered. Therefore, the analysis of oils used in machinery is generally performed by a specialized analytical institution. Although the oil data analyzed by the analytical institution is highly accurate and reliable, it usually takes about three weeks for the user of the mechanical device to know the result. Analytical costs are also high due to the use of expensive equipment. Therefore, it is difficult to analyze the oil frequently, and it is insufficient to predict the precursor of a failure, for example.

The state of oil in a machine device differs depending on the environment in which the machine device is used, even if the machine device is of the same type. Therefore, for example, the state of oil is not always the same even if the operating time is the same. .. In particular, when the mechanical device is a construction machine, the magnitude of the load applied to the mechanical device and the internal combustion engine such as the engine included in the mechanical device differs depending on the environment in which the mechanical device is used. Therefore, the rate of change in the state of oil such as lubricating oil is not uniform. In response to this, construction machinery is currently changing oil at very short intervals.

In contrast to the idea of requesting an inspection organization to analyze, there is an idea of in-line analysis in which an analyzer is installed inside the mechanical device and oil is analyzed at any time.

If in-line analysis can be applied to the analysis of oil in the mechanical device, the oil can be analyzed at any time without sampling the oil from the mechanical device, so that the user of the mechanical device can grasp the state of the oil in a timely manner. can do. As a result, the user can appropriately perform maintenance necessary for the mechanical device such as oil change according to the state of the oil.

The analysis method applied to this disclosure will be described below.

In recent years, Raman spectroscopy has attracted attention as a method for chemical analysis of substances. Raman spectroscopy refers to excitation light obtained by irradiating a substance under test with excitation light of a single wavelength, generally laser light, and mixing it with the reflected light and scattered light (Rayleigh scattered light). Is a technique for obtaining information on the chemical properties of the substance to be measured from the spectra of light of different wavelengths (Raman scattered light). However, the Raman scattered light has an intensity of only about ^{10 to 6 with} respect to the intensity of the reflected light having the same wavelength as the excitation light or the Rayleigh scattered light which is the scattered light, and is extremely weak. Therefore, a highly sensitive detector and an optical system are required, and a laser as an excitation light source is also required to have high performance such as wavelength stability and monochromaticity. For this reason, Raman spectroscopy has not been widely applied to industry as compared to infrared absorption spectroscopy, despite its high usefulness.

In Raman spectroscopy, the difference in the number of waves between Raman scattered light and excitation light (so-called Raman shift) corresponds to the energy difference between the vibrational levels of the chemical bonds of the molecules that make up the substance to be measured, which is typical. Infrared absorption spectroscopy, which is a vibrational spectroscopy method, and roughly the same information on chemical bonds can be obtained. It should be noted here that in Raman scattered light, not the excitation light itself, but the wavelength deviation from the excitation light (difference in the reciprocal of energy in photon theory) indicates the correspondence with the chemical bond. That is, the wavelength of the excitation light is arbitrary, and as the excitation light, light having an arbitrary wavelength from ultraviolet light, visible light, near-infrared light, or the like can be used. This makes it possible to use general-purpose optical elements in the visible light region without using special detectors and optical elements as in infrared absorption spectroscopy.

However, as mentioned above, Raman spectroscopy has not yet been applied to the industrial field, so it cannot be said that there is sufficient knowledge for the analysis of oils (that is, oils) in machinery.

As a knowledge about the analysis of oils of conventional mechanical devices, for example, there is a standard (ASTM E2412-10; 2018) for monitoring the state of lubricating oil. The standard defines the frequency domain and belonging substances of characteristic signals on the infrared absorption spectrum that should be monitored in the monitoring of the state of lubricating oil by Fourier transform infrared absorption spectroscopy (FT-IR). There is. On the other hand, in Raman spectroscopy, such a standard does not exist.

From the physical principle, both infrared absorption spectroscopy and Raman spectroscopy are molecular vibration spectroscopy, and the characteristic signal on the spectrum is the energy corresponding to the binding energy of each molecule contained in the oil. Appears at the position of. However, the physical element process that absorbs infrared light of energy showing a characteristic signal in infrared absorption spectroscopy and the physical element process that produces Raman scattered light of energy showing a characteristic signal in Raman spectroscopy are different. In general, even signals belonging to the same molecular vibration have different signal intensities. This is called the selection rule, and sometimes even if the same substance is measured by infrared absorption spectroscopy and Raman spectroscopy, completely different spectra can be obtained.

In addition, Raman spectroscopy irradiates an object to be measured (here, oils) with excitation light of a specific wavelength, generally a visible light laser, in principle. Since the laser has a very high energy density, it may induce autofluorescence of the object to be measured. That is, depending on the components contained in the object to be measured, autofluorescence with a signal much higher than that of Raman scattered light may occur, and this autofluorescence interferes with the analysis of weak Raman scattered light. For example, in order to detect weak Raman scattered light, it is generally required to lengthen the exposure time for obtaining a spectrum. However, if autofluorescence occurs with a signal much higher than the Raman scattered light signal, the autofluorescence can saturate the output of the photodetector for spectral measurement.

The flow of Raman spectroscopic analysis will be described below. FIG. 1 is a diagram showing an example of a flow of Raman spectroscopic analysis.

As shown in FIG. 1, first, the object to be measured (oil in this case) is irradiated with excitation light with a laser, and the Raman spectrum is measured (step S001). At this time, since autofluorescence (so-called fluorescence noise) is generated by irradiating the object to be measured with excitation light, the measured Raman spectrum contains fluorescence noise. Subsequently, the fluorescence noise is removed by fitting with an appropriate function, and the baseline correction is performed (step S002). This gives a spectrum of Raman scattered light. Subsequently, the Raman spectrum obtained in step S002 is fitted using a peak shape function such as a Gaussian function, and individual peaks are separated (step S003). As a result, the shape, position, height and area of the peak can be obtained.

FIG. 2 is a diagram showing Raman spectra of oils having different usage times measured in step S001. FIG. 3 is a diagram showing a spectrum of Raman scattered light obtained by removing fluorescence noise from the Raman spectrum of FIG. 2 in step S002.

As shown in FIG. 2, in the Raman spectrum measured in step S001, the fluorescence intensity of the autofluorescence of the oil increases as the oil usage time increases, but the usage time is a predetermined time (here, 514 hours). If it exceeds, the fluorescence intensity of the autofluorescence of the oil decreases as the usage time increases.

Further, as shown in FIG. 3, also in the spectrum of the Raman scattered light of the oil obtained in step S002, the signal intensity of the spectrum of the Raman scattered light increases as the usage time of the oil increases, but the predetermined usage time It decreases when it exceeds (for example, 514 hours).

In this way, not only the fluorescence noise but also the signal intensity of the entire spectrum of the Raman scattered light increases or decreases. Therefore, the spectrum of the Raman scattered light obtained in step S002 is peak-fitted in step S003 to obtain the peak height. Even if you ask for such things, it may not be possible to accurately evaluate the state of the oil.

For example, in oil used in mechanical devices (for example, engines), coloring substances such as soot may be generated in the oil as the usage time becomes longer. Since colored substances such as soot easily absorb light, a part of the excitation light irradiated to the oil (hereinafter, also referred to as irradiation light) is blocked by the colored substance, and the light intensity of the excitation light irradiated to the oil. Is thought to decrease. Hereinafter, a more specific description will be given with reference to FIG.

FIG. 4 is a diagram for explaining measurement problems that may occur depending on the state of oil. FIG. 4A schematically shows the measurement of oil in which almost no coloring is observed, and FIG. 4B schematically shows the measurement of oil colored containing a coloring substance such as soot. Shown. FIG. 4 (c) schematically shows an example of a spectrum of Raman scattered light that is considered to be obtained by the measurements of FIG. 4 (a) and FIG. 4 (b).

As shown in FIG. 4A, it is considered that in the oil in which almost no coloring is observed, a Raman spectrum L _2a including fluorescence noise can be obtained _{when the irradiation light L 1 is irradiated from the laser.} On the other hand, as shown in FIG. 4 (b), colored oil contain coloring material such as soot, even the irradiation light L ₁ from the laser is irradiated, a part of the irradiation light L ₁ is in the oil blocked is absorbed by the coloring material, the light intensity of the irradiation light L ₁ irradiated to the oil is thought to be attenuated. Therefore, it is considered that the signal intensity of the _{Raman spectrum L 2b} including the fluorescence noise also decreases.

A schematic diagram of a spectrum obtained by baseline-correcting the Raman spectrum obtained under these conditions is shown in FIG. 4 (c). The spectrum a in (c) of FIG. 4 is a schematic diagram when the Raman spectrum considered to be obtained by the measurement of (a) of FIG. 4 is baseline-corrected. Further, the spectrum b is a schematic diagram when the Raman spectrum considered to be obtained in FIG. 4B is corrected by baseline.

As shown in FIG. 4 (c), it is considered that the spectrum b of the Raman scattered light of the colored oil has a lower signal intensity of the entire spectrum than the spectrum a of the Raman scattered light of the uncolored oil. Thus, it is considered that the light absorption by the coloring substance such as soot affects the intensity difference of the entire signal of the Raman spectrum.

As a result of diligent studies in view of the above problems, the inventors of the present application have found a method capable of reducing the influence of disturbances such as autofluorescence derived from oil in a mechanical device and soot in oil in Raman spectroscopy.

Therefore, the present disclosure provides an oil state diagnosis method and an oil state diagnosis device that can easily and accurately diagnose the oil state.

The outline of one aspect of the present disclosure is as follows.

In the oil state diagnosis method according to one aspect of the present disclosure, a Raman spectrum of oil is acquired, and the intensity of a peak derived from saturated alcan in the Raman spectrum is standardized with respect to the intensity of a predetermined peak in the acquired Raman spectrum. At least one of the normalized values is calculated, and the value and the state of the oil normalized by the intensity of the peak derived from the saturated Alcan in the Raman spectrum with respect to the pre-calculated intensity of the predetermined peak in the Raman spectrum of the oil. The state of the oil is diagnosed from the calculated at least one standardized value based on the correlation with.

As described above, in the oil state diagnosis method according to one aspect of the present disclosure, the obtained Raman of the oil is found in the correlation between the normalized value of the predetermined peak intensity in the Raman spectrum of the oil and the state of the oil calculated in advance. By substituting a normalized value of a predetermined peak intensity in the spectrum, the state of the oil can be easily diagnosed.

Further, according to the method, in order to standardize the intensity of a predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, the autofluorescence of the oil with respect to the Raman spectrum of the oil, the soot in the oil, and the oil The influence of disturbance such as coloring can be easily removed. This is due to the following reasons.

For example, saturated alkane, which is the main component of oil, hardly changes in total amount even if some components of oil change due to oxidation. That is, even if the state of the oil changes, the absolute intensity of the peak derived from the saturated alkane of the oil hardly changes. For example, even if a part of the components of the oil are changed by oxidation, the total amount of saturated alkanes, which are the main components of the oil, is hardly affected, so that the absolute intensity of the peak derived from the saturated alkanes does not change. Further, when the excitation light is absorbed by the soot and the coloring of the oil in the oil and the light intensity of the excitation light is attenuated, the influence of the attenuation affects the intensity of the entire signal of the Raman spectrum of the oil. Therefore, by normalizing the intensity of the predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, in other words, by calculating the relative ratio of the predetermined component to the main component of the oil, the oil The state of can be evaluated accurately.

Therefore, by normalizing the intensity of the predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, the predetermined peak intensity is corrected to an appropriate value corresponding to the change in the state of the oil. NS. That is, the influence of the above-mentioned disturbance on the Raman spectrum of oil can be easily removed.

Further, according to the method, since the above standardized value is an appropriate value corresponding to a change in the oil state, the oil state is accurately evaluated based on the above-mentioned correlation calculated in advance. can do.

From the above, according to the oil condition diagnosis method according to one aspect of the present disclosure, the oil condition can be diagnosed easily and accurately.

For example, in the oil state diagnosis method according to an embodiment of the present disclosure, a peak derived from the saturated alkane of the Raman ^spectra, wave number range of 1400 cm -1 ~ 1600 cm ^{-1, or,} wavenumber of 2840cm ^-1 ~ 3000cm -1 It may be located in the range.

_{As a result, among the peaks in the wavenumber range of the Raman spectrum derived from the saturated alkane (-CH 2-} ), which is the main component of the oil, the peak showing a relatively strong signal intensity can be used as the standard for normalization. Reliable data (that is, normalized values) can be obtained.

For example, in the oil state diagnostic method according to one aspect of the present disclosure, the peak derived from the saturated alkane in the Raman spectrum may be located at a ^{wave number of 1450 cm -1.}

As a result, the normalized value is calculated based on the peak showing the strong signal strength derived from the saturated alkane, so that the oil state can be diagnosed with high accuracy.

For example, in the oil state diagnosis method according to an embodiment of the present disclosure, the predetermined peak wavenumber ^{1300 cm} -1, may be located in at least one of 1600 cm ^-1 and 1750 cm ^-1.

This makes it possible to accurately diagnose the oil condition based on the peak with a relatively strong signal strength among the peaks generated due to the change of the oil condition (for example, the change of the component due to the oxidation of the oil).

For example, in the oil condition diagnosis method according to one aspect of the present disclosure, the predetermined peak may be located at a ^{wave number of 1300 cm -1.}

As a result, the diagnosis accuracy is improved because the oil state is diagnosed based on the intensity of the peak in which the change in signal intensity due to the change in oil state is very large as compared with infrared absorption spectroscopy.

For example, in the oil state diagnosis method according to one aspect of the present disclosure, at least one of the total acid value and the oxidation value of the oil may be evaluated based on the standardized values in the diagnosis.

This makes it possible to easily and accurately diagnose the state of oil change due to oxidation.

For example, the oil state diagnosis method according to one aspect of the present disclosure further corrects the acquired baseline of the Raman spectrum, and in the calculation, the normalized value is calculated with respect to the corrected Raman spectrum. You may.

As a result, a standardized value can be calculated for the corrected Raman spectrum, so that the oil state can be diagnosed more accurately.

Further, the oil state diagnostic apparatus according to one aspect of the present disclosure is derived from an acquisition unit that acquires a Raman spectrum of oil and a saturated alkane in the Raman spectrum with respect to the intensity of a predetermined peak in the acquired Raman spectrum. A calculation unit that calculates at least one value normalized by the peak intensity, and the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the pre-calculated intensity of the predetermined peak in the Raman spectrum of the oil. It includes a storage unit that stores the correlation between the standardized value and the oil state, and a diagnostic unit that diagnoses the oil state from at least one standardized value calculated based on the correlation. ..

As described above, in the oil state diagnostic apparatus according to one aspect of the present disclosure, the obtained Raman of the oil is found in the correlation between the normalized value of the predetermined peak intensity in the Raman spectrum of the oil calculated in advance and the state of the oil. By substituting a normalized value of a predetermined peak intensity in the spectrum, the state of the oil can be easily diagnosed.

Further, according to the apparatus, in order to standardize the intensity of a predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, the autofluorescence of the oil with respect to the Raman spectrum of the oil, the soot in the oil, and the oil The influence of disturbance such as coloring can be easily removed. This is due to the following reasons. For example, the total amount of saturated alkane, which is the main component of oil, hardly changes even if some components of the oil change due to oxidation. That is, even if the state of the oil changes, the absolute intensity of the peak derived from the saturated alkane of the oil hardly changes.

For example, even if some components of the oil change due to oxidation, there is almost no effect on the total amount of saturated alkanes, which are the main components of the oil, so the absolute intensity of the peak derived from saturated alkanes does not change. Further, when the excitation light is absorbed by the soot and the coloring of the oil in the oil and the light intensity of the excitation light is attenuated, the influence of the attenuation affects the intensity of the entire signal of the Raman spectrum of the oil. Therefore, by normalizing the intensity of the predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, in other words, by calculating the relative ratio of the predetermined component to the main component of the oil, the oil The state of can be evaluated accurately.

Therefore, by normalizing the intensity of the predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, the predetermined peak intensity is corrected to an appropriate value corresponding to the change in the state of the oil. NS. That is, the influence of the above-mentioned disturbance on the Raman spectrum of oil can be easily removed.

Further, according to the apparatus, since the above standardized value is an appropriate value corresponding to a change in the oil state, the oil state is accurately evaluated based on the above-mentioned correlation calculated in advance. can do.

From the above, according to the oil condition diagnostic apparatus according to one aspect of the present disclosure, the oil condition can be easily and accurately diagnosed.

It should be noted that these comprehensive or specific aspects may be realized by a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, and the system, the method, the integrated circuit. , A computer program, and any combination of recording media.

Hereinafter, embodiments of the present disclosure will be specifically described with reference to the drawings.

Note that all of the embodiments described below show comprehensive or specific examples. Numerical values, shapes, components, arrangement positions and connection forms of components, steps, step order, and the like shown in the following embodiments are examples, and are not intended to limit the present disclosure. Further, among the components in the following embodiments, the components not described in the independent claims indicating the highest level concept are described as arbitrary components.

Also, each figure is not necessarily exactly illustrated. Therefore, for example, the scales and the like do not always match in each figure. Further, in each figure, substantially the same configuration is designated by the same reference numerals, and duplicate description will be omitted or simplified.

Further, in the present specification, terms indicating relationships between elements such as parallel or orthogonal, terms indicating the shape of elements such as squares or rectangles, and numerical ranges are not expressions expressing only strict meanings. , Is an expression meaning that a substantially equivalent range, for example, a difference of about several percent is included.

(Embodiment)
[Oil condition diagnostic device]
First, the oil state diagnostic apparatus according to the embodiment will be described. FIG. 5 is a block diagram showing an example of the functional configuration of the oil condition diagnostic apparatus 100 according to the embodiment. In FIG. 5, the movement of light is shown by a broken line, and the signal transmission direction is shown by a solid line.

As shown in FIG. 5, the oil state diagnostic apparatus 100 according to the embodiment includes, for example, a light source 10, a spectroscope 20, and a processing unit 70.

The light source 10 irradiates the oil with excitation light. The excitation light may be ultraviolet light, visible light, or infrared light. Above all, the excitation light is preferably visible light. As a result, an inexpensive visible light laser can be used as the light source 10. Further, as the optical system, an inexpensive optical system for visible light can be used. Therefore, since the oil state diagnosis device 100 can be manufactured at low cost, the versatility of the oil state diagnosis device 100 is improved.

For example, when the oil condition diagnostic apparatus 100 performs in-line analysis of oil in a mechanical device, the light source 10 emits excitation light to the oil through an optical window (not shown) provided on the flow path of the oil in the mechanical device. You may irradiate. At this time, the light source 10 may irradiate the oil with excitation light via an optical fiber (not shown). An example of applying the oil condition diagnostic apparatus according to the present disclosure to in-line analysis of oil will be described later in [Application Example].

The spectroscope 20 derives a spectrum of Raman scattered light (hereinafter, also referred to as Raman spectrum) by dispersing Raman scattered light scattered from a measurement object (here, oil) by irradiation with excitation light. For example, the spectroscope 20 has a measuring unit (not shown) that measures the spectrum of Raman scattered light scattered from the oil by irradiation with excitation light, and an output unit (not shown) that outputs the measured Raman spectrum to the processing unit 70. And. The spectroscope 20 may further include a filter (not shown) and a spectroscope unit (not shown). The light reflected and scattered by the oil due to the irradiation of the excitation light is incident on the spectroscope 20. Most of the scattered light is light having the same wavelength as the excitation light, and is so-called Rayleigh scattered light. The light incident on the spectroscope 20 is incident on the filter. The filter is, for example, a band stop filter that allows Raman scattered light to pass through and removes Rayleigh scattered light. The scattered light that has passed through the filter is separated into light for each wavelength band by the spectroscopic unit. The intensity of light in each wavelength band dispersed by the spectroscopic unit is measured by the measuring unit. The measuring unit includes, for example, an image sensor (not shown), and the image sensor receives light in each wavelength band dispersed by the spectroscopic unit and converts it into an electric signal. The image sensor outputs the converted electric signal as a digital value to the output unit. The output unit outputs a digital value indicating the intensity of light in each wavelength band to the processing unit 70 as a spectrum of Raman scattered light of oil. The configuration of the spectroscope 20 described above is an example, and the spectroscope 20 only needs to be able to measure the Raman spectrum by dispersing the Raman scattered light from the oil, and the configuration and the measuring method thereof are particularly limited. Not done.

The processing unit 70 acquires the Raman spectrum of the oil output from the spectroscope 20 and executes a process of diagnosing the state of the oil.

The processing unit 70 includes an acquisition unit 30, a calculation unit 40, a storage unit 50, and a diagnosis unit 60. The processing unit 70 is connected to the spectroscope 20. The processing unit 70 may be connected to the spectroscope 20 by wireless communication such as Bluetooth (registered trademark) or wired communication such as Ethernet (registered trademark). The processing unit 70 may be mounted on a computer, for example, or may be mounted on one device together with the light source 10 and the spectroscope 20 as shown in FIG.

The acquisition unit 30 acquires the Raman spectrum of the oil output from the spectroscope 20.

The calculation unit 40 calculates at least one value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the intensity of the predetermined peak in the Raman spectrum acquired by the acquisition unit 30.

The storage unit 50 stores the correlation between the value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum and the state of the oil with respect to the intensity of the predetermined peak in the Raman spectrum of the oil calculated in advance. do. For example, the correlation may be calculated in advance for each type of oil and stored in the storage unit 50. The correlation may be a table in which inputs and outputs are associated, such as a Lookup table. Here, the input is a standardized value, and the output is the state of the oil (for example, the total acid value or the oxidation value indicating the degree of oxidation of the oil). In the following, the value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the intensity of the predetermined peak in the Raman spectrum of the oil is also simply referred to as a normalized value.

The diagnosis unit 60 reads the correlation from the storage unit 50, and diagnoses the oil state from at least one standardized value calculated by the calculation unit 40 based on the correlation.

Note that FIG. 5 shows an example in which the oil state diagnostic apparatus 100 includes a light source 10 and a spectroscope 20, but the present invention is not limited to this. For example, the oil condition diagnostic apparatus does not have to include the light source 10 and the spectroscope 20. For example, the oil state diagnostic device may be the processing unit 70.

[Oil condition diagnosis method]
Subsequently, an example of the oil state diagnosis method will be described with reference to FIG. FIG. 6 is a flowchart showing an example of the oil state diagnosis method according to the embodiment.

The oil state diagnosis method according to the embodiment includes, for example, irradiation step S100 of irradiating the oil to be measured with excitation light, and a spectrum of scattered light scattered from the oil by irradiation of the excitation light (that is, Raman of oil). Measurement step S101 for measuring (spectrum), acquisition step S102 for acquiring the Raman spectrum of oil, and calculation for calculating a value obtained by standardizing the intensity of a predetermined peak in the acquired Raman spectrum with the intensity of a peak derived from saturated alkylan. Includes step S103 and diagnostic step S104 for diagnosing the state of the oil from standardized values.

Hereinafter, each step will be described in more detail with reference to FIGS. 5 and 6.

As shown in FIG. 6, in the irradiation step S100, the light source 10 irradiates the oil with excitation light. As described above, the excitation light may be any of ultraviolet light, visible light, and infrared light. The excitation light is, for example, a laser beam.

Next, in the measurement step S101, the spectroscope 20 measures the Raman spectrum of the oil. As described above, the spectroscope 20 includes a filter (not shown), a spectroscopic unit (not shown), a measuring unit (not shown), and an output unit (not shown). More specifically, in the measurement step S101, the filter passes the Raman scattered light among the light incident on the spectroscope 20 and removes the Rayleigh scattered light. The spectroscopic unit disperses the Raman scattered light that has passed through the filter into light for each wavelength band. The measuring unit measures the intensity of light in each wavelength band dispersed by the spectroscopic unit. The measuring unit includes an image sensor (not shown), and the image sensor receives light in each wavelength band dispersed by the spectroscopic unit and converts it into an electric signal. Then, the image sensor outputs the converted electric signal as a digital value to the output unit. The output unit outputs a digital value indicating the intensity of light in each wavelength band to the processing unit 70 as a spectrum of Raman scattered light of oil (that is, Raman spectrum of oil).

Next, in the acquisition step S102, the acquisition unit 30 of the processing unit 70 acquires the Raman spectrum of the oil output from the spectroscope 20. As described above, the processing unit 70 may be connected to the spectroscope 20 by wireless communication such as Bluetooth (registered trademark) or wired communication such as Ethernet (registered trademark). The acquisition unit 30 acquires the Raman spectrum of the oil output by the spectroscope 20 and outputs the acquired Raman spectrum of the oil to the calculation unit 40.

Next, in the calculation step S103, the calculation unit 40 calculates at least one value obtained by normalizing the intensity of a predetermined peak in the acquired Raman spectrum with the intensity of the peak derived from the saturated alkane. For example, the intensity of each peak in the Raman spectrum may be the signal intensity at the top of each peak. In the calculation step S103, the calculation unit 40 may further perform baseline correction of the acquired Raman spectrum and calculate the above standardized value with respect to the corrected Raman spectrum. For example, the calculation unit 40 may correct the baseline of the acquired Raman spectrum of the oil based on the correlation between the fluorescence noise intensity and the Raman signal average intensity calculated in advance. As a result, a standardized value can be calculated for the corrected Raman spectrum, so that the oil state can be diagnosed more accurately.

For example, a peak derived from a saturated alkane Raman spectra of ^oil wavenumber range of 1400 cm -1 ~ 1600 cm ^-1, or ^located wavenumber range of 2840cm ^-1 ~ 3000cm -1. _{As a result, among the peaks in the wavenumber range of the Raman spectrum derived from the saturated alkane (-CH 2-} ), which is the main component of the oil, the peak showing a relatively strong signal intensity can be used as the standard for normalization. Reliable data (that is, normalized values) can be obtained. Above all, the peak derived from the saturated alkane may be located at a ^{wave number of 1450 cm -1.} As a result, the normalized value is calculated based on the peak showing the strong signal strength derived from the saturated alkane, so that the oil state can be diagnosed with high accuracy.

Further, for example, a predetermined peak in the Raman spectrum of the obtained oil, the wave number ^{1300 cm} -1, is located at least one 1600 cm ^-1 and 1750 cm ^-1. Thereby, the state of the oil can be accurately diagnosed based on the peak having a relatively strong signal strength among the peaks generated due to the change of the state of the oil (for example, the change of the component due to the oxidation of the oil). Above all, the predetermined peak may be located at a ^{wave number of 1300 cm -1.} As a result, the state of the oil is diagnosed based on the intensity of the peak in which the change in the signal intensity due to the change in the state of the oil is very large as compared with the infrared absorption spectroscopy, so that the diagnostic accuracy is improved.

The peak intensity in the Raman spectrum may be, for example, the signal intensity at the peak top or the integrated intensity of the peak. Further, the signal intensity of the peak top in the Raman spectrum of the acquired oil may be used as it is, or the signal intensity of the peak top in the corrected Raman spectrum obtained by removing the fluorescence baseline from the Raman spectrum may be used. For example, when the integrated intensity of the peak is used, it may be the integrated intensity of the peak in the Raman spectrum of the acquired oil, or it may be the integrated intensity of the peak in the corrected Raman spectrum. Further, for example, when the Raman spectrum is expressed as the sum of a plurality of peak functions, for example, a Gaussian function, the intensity of the peak in the Raman spectrum may be the height or area of each peak of the plurality of Gaussian functions.

Next, in the diagnostic step S104, the diagnostic unit 60 normalizes the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the intensity of the predetermined peak stored in the storage unit 50 in the Raman spectrum of the oil. Read the correlation between the value and the oil state. The correlation is calculated in advance and stored in the storage unit 50. The correlation may be calculated for each type of oil. The diagnosis unit 60 reads out the correlation corresponding to the type of oil from the storage unit 50 according to the type of oil measured. Based on the correlation read from the storage unit 50, the oil state is diagnosed from at least one standardized value calculated by the calculation unit 40. For example, in the diagnostic step S104, the diagnostic unit 60 may evaluate at least one of the total acid value and the oxidation value of the oil based on the standardized value. As a result, the diagnostic unit 60 can easily and accurately diagnose the state of change in oil due to oxidation.

Based on the above, in the oil state diagnosis method according to the present embodiment, at least a value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum is set with respect to the intensity of the predetermined peak in the Raman spectrum of the measured oil. One is calculated, and the correlation between the value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum and the state of the oil with respect to the intensity of the predetermined peak in the Raman spectrum of the oil calculated in advance. Based on this, the oil condition is diagnosed from at least one calculated value. As a result, the oil state diagnosis method according to the present embodiment can easily remove the influence of disturbance such as autofluorescence of the oil, soot in the oil, and coloring of the oil, so that the oil can be easily and accurately used. Can be diagnosed.

Although the example in which the oil state diagnosis method includes the irradiation step S100 and the measurement step S101 has been described in the present embodiment, the oil state diagnosis method may not include the irradiation step S100 and the measurement step S101.

Hereinafter, the oil state diagnosis method of the present disclosure will be specifically described with reference to Experimental Examples and Examples, but the present disclosure is not limited to the following Experimental Examples and Examples.

In the following experimental example, the object to be measured is a lubricating oil for a mechanical device (hereinafter, simply referred to as oil), and the measuring device is a laser Raman spectroscopic measuring device. FIG. 7 is a schematic view showing an example of the configuration of the laser Raman spectroscopic measuring device.

First, a laser Raman spectroscopic measuring device and an oil sample will be described. As shown in FIG. 7, in the laser Raman spectrophotometer, the light source 10 emits a laser beam (that is, excitation light) L ₁ having a wavelength of 785 nm. The emitted excitation light L ₁ passes through the beam splitter 12 and is focused through the objective lens of the microscope 16 to irradiate the sample (oil) in the sample plate 1. _{The Raman scattered light L 2} generated from the oil 6 (see FIG. 8) by the irradiation of the excitation light L ₁ is focused by the objective lens (not shown) of the microscope 16. The focused Raman scattered light L ₂ passes through the beam splitter 12 and then passes through the filter 14 that cuts the Rayleigh scattered light. _{The Raman scattered light L 3 that} has passed through the filter 14 is incident on the spectroscopic unit 22 of the spectroscope 20 and is dispersed into light in each wavelength band. The measuring unit 24 measures the intensity of light in each wavelength band dispersed by the spectroscopic unit 22. By the above operation, the laser Raman spectroscopic measuring device measures the Raman spectrum of the oil 6.

FIG. 8 is a schematic cross-sectional view taken along the line AA of the sample plate 1 of FIG. As shown in FIG. 8, the sample plate 1 includes a quartz substrate 2, a spacer 4 arranged on the quartz substrate 2, a sample holding portion 5 surrounded by the spacer 4, and quartz arranged on the spacer 4. A cover glass 3 and the like are provided. The sample holding portion 5 is filled with oil 6.

(Experimental Example 1)
In Experimental Example 1, the area of the peak located at the ^{wave number of 1450 cm-1} in the Raman spectrum of each of the 10 types of oils used in the mechanical device for different times was derived. The peak located at wave number 1450 cm ^-1 is a peak derived from saturated alkane, which is the main component of oil.

Further, in Experimental Example 1, the total acid value was used as an index for evaluating the state of the oil. The total acid value was measured by titration for each of the above 10 oils. Then, for each of the above 10 types of oils, the correlation between the area of the peak located at the ^{wave number 1450 cm -1 in the Raman spectrum and the total acid value was investigated.} The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of the oil, and the area of the peak derived from a saturated alkane located wavenumber 1450 cm ^-1, R ² value for the linear approximation of the total acid number (so-called correlation coefficient) Was 0.15.

(Comparative Example 1)
In Comparative Example 1, the area of the peak located at the ^{wave number of 1300 cm -1} in the Raman spectrum of each of the above 10 kinds of oils was derived. The peak located at wave number 1300 cm ^-1 is a peak derived from C = C generated by the oxidation of oil.

Further, in Comparative Example 1, as in Experimental Example 1, the total acid value was used as an index for evaluating the state of the oil. Then, for each of the above 10 types of oils, the correlation between the area of the peak located at the ^{wave number 1300 cm -1 in the Raman spectrum and the total acid value was investigated.} The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of oil, ^{R 2} value for the linear approximation of the area of the peak derived from C = C located wavenumber 1300 cm ^-1, and total acid number (so-called, the correlation coefficient ) Was 0.13.

(Comparative Example 2)
In Comparative Example 2, the same procedure as in Comparative Example 1 was performed except that the area of the peak located ^{at the wave number of 1600 cm -1 was derived.} The peak located at wave number 1600 cm ^-1 is a peak derived from C = C generated by the oxidation of oil.

In Comparative Example 2, the correlation between the area of the peak located at the ^{wave number of 1600 cm -1} in the Raman spectrum and the total acid value was investigated for each of the above 10 types of oils. The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of oil, ^{R 2} value for the linear approximation of the area of the peak derived from C = C located wavenumber 1600 cm ^-1, and total acid number (so-called, the correlation coefficient ) Was 0.02.

(Comparative Example 3)
In Comparative Example 3, the same procedure as in Comparative Example 1 was performed except that the area of the peak located ^{at the wave number of 1750 cm -1 was derived.} The peak located at the wave number 1750 cm ^-1 is a peak derived from C = O generated by the oxidation of oil.

In Comparative Example 3, the correlation between the area of the peak located at the ^{wave number 1750 cm -1} in the Raman spectrum and the total acid value was investigated for each of the above 10 types of oils. The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of oil, ^{R 2} value for the linear approximation of the area of the peak derived from C = O located wavenumber 1750 cm ^-1, and total acid number (so-called, the correlation coefficient ) Was 0.01.

(Example 1)
In Example 1, using the results of Experimental Example 1 and Comparative Example 1, the ten oil use time are different in the machine, located at a wavenumber of 1300 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation between the ratio of the area of the peaks (hereinafter, also referred to as the peak ratio) and the total acid value was investigated. The results are shown in FIG. 9 and Table 1.

FIG. 9 is a diagram showing the data of the first embodiment. As shown in FIG. 9, for the above 10 kinds of the oil, and the ratio of the area of the peak located at wavenumber 1300 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the total acid value, a linear It showed a relationship. Further, as shown in Table 1, ^{R 2} values for these linear approximation (so called, the correlation coefficient) was 0.70. Therefore, thus, the ratio of the area of the peak located at wavenumber 1300 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the total acid value was found to be higher correlation than Comparative Example 1.

(Example 2)
In Example 2, using the results of Experimental Example 1 and Comparative Example 2, for the above 10 kinds of the oil, and the ratio of the peak area of which is positioned at a wave number of 1600 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation with the total acid value was investigated. The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of the oil, and the ratio of the area of the peak located at wavenumber 1600 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, R for a linear approximation of the total acid value ^{The binary} value (so-called correlation coefficient) was 0.31. Therefore, the ratio of the area of the peak located at wavenumber 1600 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the total acid value was found to be higher correlation than Comparative Example 2.

(Example 3)
In Example 3, using the results of Experimental Example 1 and Comparative Example 3, for the above 10 kinds of the oil, and the ratio of the peak area of which is positioned at a wave number of 1750 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation with the total acid value was investigated. The results are shown in Table 1.

As shown in Table 1, for the above 10 kinds of the oil, and the ratio of the area of the peak located at wavenumber 1750 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, R for a linear approximation of the total acid value ^{The binary} value (so-called correlation coefficient) was 0.28. Therefore, the ratio of the area of the peak located at wavenumber 1750 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the total acid value was found to be correlated higher than Comparative Example 3.

(summary)
As shown in Table 1, the correlation coefficient of Example 1 is higher than that of Comparative Example 1 in the relationship between the intensity of a predetermined peak caused by the change in oil and the evaluation of the state of the oil (here, the total acid value). It was high, the correlation coefficient of Example 2 was higher than that of Comparative Example 2, and the correlation coefficient of Example 3 was higher than that of Comparative Example 3. Therefore, from the results of Comparative Examples 1 to 3 and Examples 1 to 3, the intensity of a predetermined peak generated by the oxidation of the oil in the Raman spectrum of the oil is standardized by the intensity of the peak derived from saturated alkane, which is the main component of the oil. As a result, it was confirmed that the effects of disturbances such as the autofluorescence of the oil, soot in the oil, and coloring of the oil on the Raman spectrum of the oil can be easily removed. It was also confirmed that due to the effect of the above standardization, the predetermined peak intensity is corrected to an appropriate value corresponding to the change in the state of the oil.

(Comparative Example 4)
In Comparative Example 4, the same procedure as in Comparative Example 1 was carried out except that the oxidation value was used as an index for evaluating the state of the oil. Oxidation values were measured by FT-IR (Fourier Transform Infrared Spectroscopy) for each of the nine oils used in the machinery. Then, for each of the above nine types of oils, the correlation between the area of the peak located at the ^{wave number of 1300 cm -1 in the Raman spectrum and the oxidation value was investigated.} The results are shown in Table 1.

As shown in Table 1, for the above nine kinds of oils, and the area of the peak derived from C = C located wavenumber 1300 cm ^-1, R ² value for the linear approximation of the oxidation value (so-called correlation coefficient) Was 0.33.

(Comparative Example 5)
In Comparative Example 5, the area of the peak located at the wave number 1600 cm ^-1 was derived, and the correlation between the area of the peak located at the ^{wave number 1600 cm -1} in the Raman spectrum and the oxidation value was investigated for each of the above nine types of oils. Except for the above points, the same procedure as in Comparative Example 4 was performed. The results are shown in Table 1.

As shown in Table 1, for the above nine types of oil, the area of the peak derived from C = C located at a ^{wave number of 1600 cm -1 and the R-squared} value (so-called correlation coefficient) with respect to the linear approximation of the oxidation value. Was 0.02.

(Comparative Example 6)
In Comparative Example 6, the area of the peak located at the wave number 1750 cm ^-1 was derived, and the correlation between the area of the peak located at the ^{wave number 1750 cm -1} in the Raman spectrum and the oxidation value was investigated for each of the above nine types of oils. Except for the above points, the same procedure as in Comparative Example 4 was performed.

As shown in Table 1, for the above nine types of oil, the area of the peak derived from C = O located at ^{wave number 1750 cm -1 and the R-squared} value (so-called correlation coefficient) with respect to the linear approximation of the oxidation value. Was 0.17.

(Example 4)
In Example 4, using the results of Experimental Example 1 and Comparative Example 4, the nine types of oils used time are different in the machine, located at a wavenumber of 1300 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation between the ratio of the area of the peaks (hereinafter, also referred to as the peak ratio) and the oxidation value was investigated. The results are shown in Table 1.

As shown in Table 1, for the above nine kinds of oil, the ratio of the area of the peak located at wavenumber 1300 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^{-1, R 2} for a linear approximation with the oxidation value The value (so-called correlation coefficient) was 0.45. Therefore, the ratio of the area of the peak located at wavenumber 1300 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the oxidation value, it was found that a correlation is higher than Comparative Example 4.

(Example 5)
In Example 5, using the results of Experimental Example 1 and Comparative Example 5, for the above nine kinds of oil, the ratio of the peak area of which is positioned at a wave number of 1600 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation with the oxidation value was investigated. The results are shown in Table 1.

As shown in Table 1, for the above nine kinds of oil, the ratio of the area of the peak located at wavenumber 1600 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^{-1, R 2} for a linear approximation with the oxidation value The value (so-called correlation coefficient) was 0.08. Therefore, the ratio of the area of the peak located at wavenumber 1600 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the oxidation value, it was found that a correlation is higher than Comparative Example 5.

(Example 6)
In Example 6, using the results of Experimental Example 1 and Comparative Example 6, the nine types of oil above, and the ratio of the area of the peak located at wavenumber 1750 cm ^-1 to the area of peak located at wavenumber 1450 cm ^-1 The correlation with acid value was investigated. The results are shown in Table 1.

As shown in Table 1, for the above nine kinds of oil, the ratio of the area of the peak located at wavenumber 1750 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^{-1, R 2} for a linear approximation with the oxidation value The value (so-called correlation coefficient) was 0.58. Therefore, the ratio of the area of the peak located at wavenumber 1750 cm ^-1 to the area of the peak located at a wave number of 1450 cm ^-1, and the oxidation value, it was found that a correlation is higher than comparative Example 6.

(summary)
As shown in Table 1, the correlation coefficient of Example 4 is higher than that of Comparative Example 4 in the relationship between the intensity of a predetermined peak caused by the change in oil and the evaluation of the state of the oil (here, the oxidation value). The correlation coefficient of Example 5 was higher than that of Comparative Example 5, and the correlation coefficient of Example 6 was higher than that of Comparative Example 6. Therefore, from the results of Comparative Examples 4 to 6 and Examples 4 to 6, the intensity of the predetermined peak generated by the oxidation of the oil in the Raman spectrum of the oil is standardized by the intensity of the peak derived from the saturated alkane which is the main component of the oil. As a result, it was confirmed that the effects of disturbances such as the autofluorescence of the oil, soot in the oil, and coloring of the oil on the Raman spectrum of the oil can be easily removed. It was also confirmed that due to the effect of the above standardization, the predetermined peak intensity is corrected to an appropriate value corresponding to the change in the state of the oil.

From the results of the above comparative examples and examples, the value obtained by normalizing the intensity of the peak derived from the oxidizing substance generated by the oxidation of the oil by the intensity of the peak derived from the saturated alkane which is the main component of the oil, and the state of the oil. Was confirmed to have a relatively high correlation. Further, as described above, in the oil state diagnosis method according to the present disclosure, (i) the intensity of a predetermined peak derived from a change in the state of the oil is standardized by the intensity of the peak derived from saturated alkan, thereby producing an oil. It is easy to remove the influence of disturbance such as self-fluorescence, soot in oil and coloring of oil, and (ii) based on the correlation between the above standardized value and the evaluation value of the oil condition. It was confirmed that the condition of the oil to be measured can be diagnosed with high accuracy. Therefore, according to the oil condition diagnosis method according to the present disclosure, it was confirmed that the influence of disturbance such as autofluorescence of oil, soot in oil, and coloring of oil can be easily removed.

(Other embodiments)
The oil state diagnosis method and the oil state diagnosis device according to one or more aspects of the present disclosure have been described above based on the above-described embodiments, but the present disclosure is limited to these embodiments. is not it. As long as the gist of the present disclosure is not deviated, one or more embodiments of the present disclosure may be obtained by subjecting various modifications that can be conceived by those skilled in the art to the embodiment or by combining components in different embodiments. It may be included in the range of.

For example, a part or all of the components included in the oil condition diagnostic apparatus in the above embodiment may be composed of one system LSI (Large Scale Integration: large-scale integrated circuit). For example, the oil state diagnostic apparatus may be composed of a system LSI having a light source, a spectroscopic unit, and a processing unit. The system LSI may not include a light source, and may not include a light source and a spectroscopic unit.

A system LSI is an ultra-multifunctional LSI manufactured by integrating a plurality of components on a single chip. Specifically, a microprocessor, a ROM (Read Only Memory), a RAM (Random Access Memory), etc. It is a computer system composed of. A computer program is stored in the ROM. The system LSI achieves its function by operating the microprocessor according to the computer program.

Although it is referred to as a system LSI here, it may be referred to as an IC, an LSI, a super LSI, or an ultra LSI due to the difference in the degree of integration. Further, the method of making an integrated circuit is not limited to LSI, and may be realized by a dedicated circuit or a general-purpose processor. An FPGA (Field Programmable Gate Array) that can be programmed after the LSI is manufactured, or a reconfigurable processor that can reconfigure the connection and settings of the circuit cells inside the LSI may be used.

Furthermore, if an integrated circuit technology that replaces an LSI appears due to advances in semiconductor technology or another technology derived from it, it is naturally possible to integrate functional blocks using that technology. The application of biotechnology, etc. is possible.

Further, one aspect of the present disclosure may be not only such an oil state diagnosis device but also an oil state diagnosis method in which a characteristic component included in the device is a step. Further, one aspect of the present disclosure may be a computer program that causes a computer to execute each characteristic step included in the oil state diagnosis method. Further, one aspect of the present disclosure may be a non-temporary recording medium that can be read by a computer on which such a computer program is recorded.

[Application example]
FIG. 10 is a diagram showing an example of an oil state diagnosis system 500 including the oil state diagnosis device 100a according to the present disclosure. The oil state diagnosis system 500 is, for example, a system that monitors the state of consumables included in the mechanical device 200 and notifies the user of the mechanical device 200 of the state of deterioration of the consumables and the like.

The mechanical device 200 includes, for example, various large or small mechanical devices installed inside and outside in factories, offices, public facilities and houses, construction equipment operating outdoors, trucks, buses, passenger cars, motorcycles, ships, aircrafts and trains. Includes various vehicles such as industrial vehicles and construction vehicles, or equipment such as engines, transmissions, and actuators provided therein.

Further, the consumables included in the mechanical device 200 are repeatedly used in the mechanical device 200, for example, and are replaced regularly. The consumables are, for example, oils and function as a lubricating medium for the mechanical device 200. Since such consumables are arranged inside the mechanical device 200, it is not easy for the user of the mechanical device 200 to check the state of the consumables. Therefore, by incorporating the oil condition diagnosis device 100a into the mechanical device 200, the state of consumables can be measured in-line.

For example, as shown in FIG. 10, in the oil state diagnostic device 100a, the light source 10a and the spectroscope 20a are incorporated in the mechanical device 200, and the processing unit 70a is mounted on the computer. The processing unit 70a is not limited to a computer, and may be mounted on a terminal such as a smartphone, a mobile phone, a tablet terminal, a wearable terminal, or a computer mounted on the mechanical device 200. The spectroscope 20a and the processing unit 70a can communicate with each other. For example, the user may input operation information via an input unit (not shown) such as a touch panel, a keyboard, a mouse, or a microphone, and transmit the operation information to the light source 10a, the spectroscope 20a, or the server 300. In addition, the user may select necessary information and have it presented to a presentation unit such as a monitor or a speaker. As a result, the user can obtain information such as the state of consumables, the timing of replacement of consumables, and troubles that may occur in the mechanical device 200. The input unit and the display unit may be connected to the processing unit 70a, and may be provided in a device other than the device on which the processing unit 70a is mounted. Further, the input unit and the presentation unit are not limited to one, and a plurality of input units and the presentation unit may be connectable to the processing unit 70a. The device on which the processing unit 70a is mounted is connected to the server 300 via the network 400, transmits the measurement result of consumables to the server 300, and is stored in the database arranged on the server 300 by the information processing program. The diagnosed diagnosis result may be acquired. The processing unit 70a may have the presentation unit present the acquired diagnosis result to notify the user.

In the present disclosure, the intensity of a peak derived from saturated alkane, which is the main component of an oil, is used to standardize the intensity of a predetermined peak in the Raman spectrum of the oil. The effects of disturbances such as soot and oil coloring can be easily and well removed. For example, even if a part of the components of the oil are changed by oxidation, the total amount of saturated alkanes, which are the main components of the oil, is hardly affected, so that the absolute intensity of the peak derived from the saturated alkanes does not change. Further, when the excitation light is absorbed by the soot and the coloring of the oil in the oil and the light intensity of the excitation light is attenuated, the influence of the attenuation affects the intensity of the entire signal of the Raman spectrum of the oil. Therefore, by normalizing the intensity of the predetermined peak in the Raman spectrum of the oil by the intensity of the peak derived from the saturated alkane, in other words, by calculating the relative ratio of the predetermined component to the main component of the oil, the oil The state of can be evaluated accurately. Therefore, according to the oil condition diagnostic apparatus according to one aspect of the present disclosure, the oil condition can be diagnosed easily and accurately.

According to the present disclosure, the influence of disturbance such as autofluorescence of oil, soot in oil, and coloring of oil can be easily and well removed from the Raman spectrum of oil. Therefore, the state of the oil can be diagnosed easily and accurately. Further, since a visible light laser can be used, it is possible to provide an analyzer having a simple configuration and a miniaturization without using a special optical system. Therefore, it can be used not only as an analyzer but also as an in-line analyzer by incorporating it into a mechanical device.

10, 10a Light source 20, 20a Spectrometer 30 Acquisition unit 40 Calculation unit 50 Storage unit 60 Diagnosis unit 70, 70a Processing unit 100, 100a Oil condition diagnostic equipment 200 Mechanical equipment 300 Server 400 Network 500 Oil condition diagnostic system

Claims (9)

1. Obtain the Raman spectrum of oil and
   For the acquired intensity of the predetermined peak in the Raman spectrum, at least one value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum was calculated.
   It was calculated based on the correlation between the value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum and the state of the oil with respect to the intensity of the predetermined peak in the Raman spectrum of the oil calculated in advance. Diagnose the condition of the oil from at least one standardized value.
   Oil condition diagnosis method.
2. Peak derived from the saturated alkane of the Raman ^spectra, wave number range of 1400 cm -1 ~ 1600 cm ^-1, or ^located wavenumber range of 2840cm ^-1 ~ 3000cm -1,
   The oil condition diagnosis method according to claim 1.
3. The peak derived from the saturated alkane in the Raman spectrum is located at a ^{wave number of 1450 cm -1.}
   The oil condition diagnosis method according to claim 1 or 2.
4. The predetermined peak is located at least one wave number ^{1300 cm} -1, 1600 cm ^-1 and 1750 cm ^-1,
   The oil condition diagnosis method according to any one of claims 1 to 3.
5. The predetermined peak is located at a wave number of 1300 cm ^-1.
   The oil condition diagnosis method according to claim 4.
6. In the diagnosis, at least one of the total acid value and the oxidation value of the oil is evaluated based on the normalized value.
   The oil condition diagnosis method according to any one of claims 1 to 5.
7. Further, the acquired baseline of the Raman spectrum is corrected, and the baseline is corrected.
   In the calculation, the normalized value is calculated with respect to the corrected Raman spectrum.
   The oil condition diagnosis method according to any one of claims 1 to 6.
8. The oil is a lubricating oil.
   The oil condition diagnosis method according to any one of claims 1 to 7.
9. The acquisition unit that acquires the Raman spectrum of oil,
   A calculation unit that calculates at least one value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum with respect to the acquired intensity of the predetermined peak in the Raman spectrum.
   A storage unit that stores the correlation between the value normalized by the intensity of the peak derived from the saturated alkane in the Raman spectrum and the state of the oil with respect to the intensity of the predetermined peak in the Raman spectrum of the oil calculated in advance. ,
   A diagnostic unit that diagnoses the state of the oil from the calculated at least one standardized value based on the correlation.
   To prepare
   Oil condition diagnostic device.

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