CN113074814B - Method and device for evaluating quality of spectral signal of dispersion confocal sensor - Google Patents
Method and device for evaluating quality of spectral signal of dispersion confocal sensor Download PDFInfo
- Publication number
- CN113074814B CN113074814B CN202110264422.XA CN202110264422A CN113074814B CN 113074814 B CN113074814 B CN 113074814B CN 202110264422 A CN202110264422 A CN 202110264422A CN 113074814 B CN113074814 B CN 113074814B
- Authority
- CN
- China
- Prior art keywords
- signal
- sensor
- characteristic
- dimensional
- confocal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000006185 dispersion Substances 0.000 title claims abstract description 89
- 230000003595 spectral effect Effects 0.000 title claims abstract description 67
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000001228 spectrum Methods 0.000 claims abstract description 85
- 238000012545 processing Methods 0.000 claims abstract description 36
- 230000003287 optical effect Effects 0.000 claims abstract description 21
- 238000013441 quality evaluation Methods 0.000 claims abstract description 16
- 238000012938 design process Methods 0.000 claims abstract description 15
- 238000005457 optimization Methods 0.000 claims abstract description 8
- 230000035945 sensitivity Effects 0.000 claims description 72
- 238000006073 displacement reaction Methods 0.000 claims description 48
- 238000005259 measurement Methods 0.000 claims description 31
- 230000004075 alteration Effects 0.000 claims description 27
- 230000015654 memory Effects 0.000 claims description 25
- 238000010586 diagram Methods 0.000 claims description 18
- 238000013507 mapping Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 8
- 238000013461 design Methods 0.000 abstract description 25
- 230000033228 biological regulation Effects 0.000 abstract description 8
- 238000000605 extraction Methods 0.000 description 35
- 230000006870 function Effects 0.000 description 20
- 238000005070 sampling Methods 0.000 description 19
- 230000008569 process Effects 0.000 description 9
- 238000004891 communication Methods 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000012512 characterization method Methods 0.000 description 4
- 230000001276 controlling effect Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 230000001105 regulatory effect Effects 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000005484 gravity Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J2003/2859—Peak detecting in spectrum
Abstract
The invention discloses a method and a device for evaluating the quality of a spectral signal of a dispersion confocal sensor. The method comprises the steps of acquiring and collecting a two-dimensional spectrum signal of a dispersion confocal sensor; performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal; and optimizing the precision characteristic of the optical design process of the dispersive confocal sensor based on the quality index. The invention realizes the determination of the influence relationship of the spectral signal characteristics of the single-frame dispersion confocal signal and the signal frame-to-frame consistency on the precision characteristics, thereby obtaining the signal characteristic quality index related to the design parameters of the sensor and providing a design target for the optimization design of the sensor, in particular for the regulation and control of the precision characteristics of the sensor.
Description
Technical Field
The application relates to the technical field of design of a dispersion confocal sensor, in particular to a method and a device for evaluating the quality of a spectrum signal of the dispersion confocal sensor.
Background
The performance index of a dispersive confocal sensor is limited by the level of sensor design. Performance indexes such as dispersion range, object numerical aperture, transverse resolution, light quantity collection rate and the like can be directly regulated and controlled in the optical design process, but precision characteristics such as axial resolution, linearity error and the like cannot be directly reflected in the optical design process, so that a direct and effective design target is lacked, the precision characteristics of the sensor are difficult to guarantee or regulate in the optical design process of the sensor, and the quality rate of the finally produced sensor is influenced.
Disclosure of Invention
In order to solve the above problems, embodiments of the present application provide a method and an apparatus for evaluating the quality of a spectral signal of a dispersive confocal sensor.
In a first aspect, an embodiment of the present application provides a method for evaluating spectral signal quality of a dispersive confocal sensor, where the method includes:
acquiring and collecting a two-dimensional spectrum signal of a dispersion confocal sensor;
performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal;
and optimizing the precision characteristic of the optical design process of the dispersive confocal sensor based on the quality index.
Preferably, the quality index includes an actual measurement error of the sensor;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
collecting standard spectrum signals of the dispersion confocal sensor under different standard displacements;
extracting the standard peak wavelength of each frame of the standard spectrum signal, and constructing a mapping relation between standard displacement and the extracted standard peak wavelength;
after the two-dimensional spectrum signal of the dispersion confocal sensor is collected in actual measurement, extracting the actual peak wavelength of the two-dimensional spectrum signal, and performing sensor displacement decoding according to the mapping relation to obtain a sensor displacement measurement result;
and determining a sensor calibration error corresponding to the sensor displacement measurement result, and determining the sensor calibration error as an actual measurement error of the sensor.
Preferably, the quality indicator comprises a single-frame dispersion confocal signal characteristic at average sensitivity; the single-frame dispersion confocal signal features at the average sensitivity comprise full-width-at-half-maximum features and asymmetry features;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
keeping the spectrum working bandwidth and the dispersion range of the dispersion confocal sensor unchanged, and calculating the full-width half-maximum characteristic of the two-dimensional spectrum signal;
calculating and controlling monochromatic aberration of the dispersive confocal sensor through wave aberration and a diffuse spot sequence diagram, and determining the asymmetry characteristic of the two-dimensional spectral signal based on the monochromatic aberration;
determining a quality indicator of the two-dimensional spectral signal based on the full-width-at-half-maximum feature and the asymmetry feature.
Preferably, the quality index comprises an interframe consistency characteristic of a plurality of frames of dispersive confocal signals; the interframe consistency characteristics of the multiframe dispersion confocal signal comprise sensitivity consistency characteristics and asymmetry consistency characteristics;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
determining sensitivities with different full widths at half maximum corresponding to two-dimensional spectral signals with different displacements under non-constant sensitivity, calculating and determining the average sensitivity and the maximum sensitivity of each sensitivity, and obtaining the sensitivity consistency characteristic of the two-dimensional spectral signals based on the ratio of the average sensitivity to the maximum sensitivity;
calculating each RMS radius of each two-dimensional spectral signal under different displacements through the scattered spot sequence, and determining the asymmetry consistency characteristic of the two-dimensional spectral signals based on the ratio of the maximum RMS radius to the minimum RMS radius;
determining a quality indicator of the two-dimensional spectral signal based on the sensitivity consistency characteristic and the asymmetry consistency characteristic.
In a second aspect, the present application provides an apparatus for evaluating the spectral signal quality of a dispersive confocal sensor, the apparatus including:
the acquisition module is used for acquiring and collecting a two-dimensional spectrum signal of the dispersion confocal sensor;
the processing module is used for performing signal processing and signal quality evaluation on the two-dimensional spectrum signal and determining a quality index of the two-dimensional spectrum signal;
and the optimization module is used for optimizing the precision characteristic of the optical design process of the dispersive confocal sensor based on the quality index.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method according to the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as provided in the first aspect or any one of the possible implementations of the first aspect.
The invention has the beneficial effects that: and (3) following the spectral signal processing flow, establishing a signal processing error calculation model for representing the quality of the spectral signal of the dispersion confocal sensor, and analyzing the characteristics of the spectral signal of the dispersion confocal sensor. The influence relation of the spectral signal characteristics of the single-frame dispersion confocal signal and the signal frame-to-frame consistency of the two dispersion confocal sensors on the accuracy characteristics is determined, so that the signal characteristic quality index related to the design parameters of the sensor is obtained, and a design target is provided for the optimization design of the sensor, particularly the regulation and control of the accuracy characteristics of the sensor.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for evaluating the quality of a spectral signal of a dispersive confocal sensor according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram illustrating an exemplary characteristic of a single-frame dispersive confocal signal of a dispersive confocal sensor spectrum signal at an average sensitivity according to an embodiment of the present application;
fig. 3(a) is an exemplary schematic diagram of a shift wavelength relationship of a sensitivity consistency characteristic at different shifts in an inter-frame consistency characteristic of a multi-frame dispersive confocal signal provided by an embodiment of the present application;
fig. 3(b) is an exemplary schematic diagram of a shift wavelength relationship of an asymmetry consistency feature at different shifts in an inter-frame consistency feature of a multi-frame dispersive confocal signal provided by an embodiment of the present application;
fig. 4 is an exemplary diagram of peak wavelength extraction errors under different discrete sampling offsets according to an embodiment of the present application;
FIG. 5 shows the peak wavelength extraction accuracy and signal provided by the embodiments of the present application
An exemplary schematic of the relationship of (a);
FIG. 6 is a schematic diagram illustrating an exemplary relationship between a measurement error and a sensor sensitivity consistency characteristic provided by an embodiment of the present application;
fig. 7 is an exemplary diagram illustrating a relationship between a linearity error level and an asymmetry consistency characteristic provided in an embodiment of the present application;
fig. 8 is a schematic structural diagram of an apparatus for evaluating the spectral signal quality of a dispersive confocal sensor according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the invention, which may be combined with or substituted for various embodiments, and the invention is thus to be construed as embracing all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then the invention should also be construed as including embodiments that include one or more of all other possible combinations of A, B, C, D, even though such embodiments may not be explicitly recited in the following text.
The following description provides examples, and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different than the order described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
The design idea of the application is as follows: and performing index evaluation on the spectral signal quality of the dispersive confocal sensor reflecting the design level and the precision characteristic of the sensor based on the logical angle consideration that the spectral signal quality of the dispersive confocal sensor influences the signal processing precision and further influences the precision characteristic of the sensor. And in the whole process, a signal quality index function related to design parameters of the sensor is refined and confirmed according to a spectrum confocal signal processing flow, so that an influence relation between the signal quality index function and the precision characteristic is constructed, and an optical design target is provided for the optimal design of the sensor based on the influence relation.
Referring to fig. 1, fig. 1 is a schematic flowchart of a method for evaluating the spectral signal quality of a dispersive confocal sensor according to an embodiment of the present application. In an embodiment of the present application, the method includes:
s101, acquiring and collecting a two-dimensional spectrum signal of the dispersion confocal sensor.
S102, performing signal processing and signal quality evaluation on the two-dimensional spectrum signal, and determining a quality index of the two-dimensional spectrum signal.
Specifically, the quality of the spectrum signal of the dispersive confocal sensor comprises a quality index describing the spectrum signal characteristic of the dispersive confocal sensor, a signal-to-noise ratio (SNR) and the like, wherein the SNR is mainly limited by the electrical performance of a detector such as a spectrometer, the actual SNR of the signal mainly depends on the signal light intensity under the same condition, and the signal quality concept in the application focuses more on the quality index describing the spectrum signal characteristic of the dispersive confocal sensor. The characterization of the spectrum signal quality of the dispersive confocal sensor is to construct an influence rule between a signal quality index function and the accuracy characteristic of the sensor, and provide a design target for the design of the sensor, such as the accuracy characteristic regulation.
In one possible embodiment, the quality indicator includes an actual measurement error of the sensor;
step S102 includes:
collecting standard spectrum signals of the dispersion confocal sensor under different standard displacements;
extracting the standard peak wavelength of each frame of the standard spectrum signal, and constructing a mapping relation between standard displacement and the extracted standard peak wavelength;
after the two-dimensional spectrum signal of the dispersion confocal sensor is collected in actual measurement, extracting the actual peak wavelength of the two-dimensional spectrum signal, and performing sensor displacement decoding according to the mapping relation to obtain a sensor displacement measurement result;
and determining a sensor calibration error corresponding to the sensor displacement measurement result, and determining the sensor calibration error as an actual measurement error of the sensor.
In the embodiment of the present application, the characterization of the spectral signal quality of the dispersive confocal sensor is calculated, that is, a mapping relationship between the spectral signal of the dispersive confocal sensor and the calibration error of the sensor is constructed. Firstly, collecting dispersion confocal signals under different standard displacements, namely two-position spectral signals, namely collecting a spectral signal data set of a dispersion confocal sensor; and then, extracting the peak wavelength of each frame of dispersion confocal signal, and constructing a mapping relation between the standard displacement and the extracted peak wavelength, namely a calibration process of the sensor. During actual measurement, after the actual peak wavelength is extracted according to the actually collected dispersion confocal signal, the peak wavelength is decoded according to the calibrated displacement response mapping relation, and the sensor displacement measurement result is obtained. According to the displacement measurement result, a corresponding displacement measurement error can be obtained. In terms of signal processing, the displacement decoding and displacement response calibration processes of the sensor are reciprocal, so that the actual measurement error of the sensor can be reflected by the calibration error of the sensor, and the quality index of the two-dimensional spectral signal is determined.
Specifically, the spectrum signal of the dispersive confocal sensor is provided with a wavelength sequence lambda with equal intervals in the wavelength dimensionsThe expression is as follows:
λs＝[λ-n，λ-n+1，...，λ-1，λ0，λ1，...，λn-1，λn]
wherein the index i ∈ {0, ± 1, ± 2. }, the wavelength sampling interval is Δ λ. According to the spectrum signal model of the dispersion confocal sensor, the dispersion confocal signal at the displacement l is expressed as:
I(λs|l)＝I2D(λs，l)
on this basis, the peak wavelength of the dispersive confocal signal is expressed as:
pn(l)＝Θ[λs，I(λs|l)+IN]
wherein p isn(l) Represents the extracted peak wavelength, Θ [ ·]Denotes the peak extraction operation, INRepresenting random noise. The intensity of the signal is typically normalized and thresholded prior to the signal peak wavelength extraction process. The thresholding operation means that only points with normalized intensity equal to or greater than the threshold value will participate in the calculation.
The method adopts Monte Carlo simulation to describe the peak wavelength extraction process of the dispersion confocal signal: firstly, calculating to obtain a dispersion confocal signal at a given displacement according to a dispersion confocal signal expression at a displacement l; then, adding noise simulation to the signal to obtain a plurality of frames of dispersion confocal signals containing noise, and calculating the peak wavelength of the signal according to the peak wavelength expression of the dispersion confocal signals; finally, the displacement is modified and the above calculation process is repeated. SNR is defined herein as the ratio of the mean of the intensity at the maximum intensity of the signal to the standard deviation of the noise jitter.
According to the calculation result of the peak wavelength, the calibration error of the sensor is expressed as:
ef＝Fs[pn，l]
wherein l represents a shift sequence, pnDenotes the peak extraction wavelength sequence, F, at noisy signalsSAnd expressing the calibration error obtained by calculation by taking the theoretical displacement-wavelength mapping relation S as a fitting function. At the same shift, the error sequence efReflects the linearity error of the sensor, and the error sequence efThe standard deviation of (a) reflects the axial resolution of the sensor. By processing error sequences e under different dispersion confocal sensor spectrum signalsfThe quality of the spectrum signal of the dispersive confocal sensor can be quantitatively evaluated by the statistical analysis.
Besides quantitatively evaluating the quality index of the spectrum signal by using an error, the quality of the spectrum signal of the dispersive confocal sensor is closely related to the design parameters of the sensor, and the purpose of evaluating the signal quality is to guide the configuration of the design parameters of the sensor, so that the spectrum signal of the dispersive confocal sensor is simplified into the following two characteristics: the characteristic of single-frame dispersion confocal signals and the inter-frame consistency characteristic of multi-frame dispersion confocal signals at the average sensitivity. On the basis, four signal quality index functions related to sensor design parameters are refined to quantitatively describe single-frame signal characteristics and signal inter-frame consistency characteristics. The simplification of the spectral signal characteristics of the dispersive confocal sensor and the refinement of the signal quality index function have the following purposes: firstly, the influence of quality indexes describing the spectral signal characteristics of the dispersive confocal sensor on the precision characteristics is researched, and the signal quality evaluation process can be simplified; secondly, more importantly, the spectrum signal form of the dispersion confocal sensor is complex and is influenced by various design parameters, the simplification of the characteristics and the refinement of quality indexes can be oriented to the design process of the sensor, and the regulation and control of various design parameters are convenient in practical application.
In one possible embodiment, the quality indicator includes a single frame dispersion confocal signal feature at average sensitivity; the single-frame dispersion confocal signal features at the average sensitivity comprise full-width-at-half-maximum features and asymmetry features;
step S102 includes:
keeping the spectrum working bandwidth and the dispersion range of the dispersion confocal sensor unchanged, and calculating the full-width half-maximum characteristic of the two-dimensional spectrum signal;
calculating and controlling monochromatic aberration of the dispersive confocal sensor through wave aberration and a diffuse spot sequence diagram, and determining the asymmetry characteristic of the two-dimensional spectral signal based on the monochromatic aberration;
determining a quality indicator of the two-dimensional spectral signal based on the full-width-at-half-maximum feature and the asymmetry feature.
In the embodiment of the present application, as shown in fig. 2, fig. 2 is an exemplary diagram of the characteristics of a single-frame dispersive confocal signal of a dispersive confocal sensor spectrum signal at an average sensitivity, wherein the characteristics of the single-frame dispersive confocal signal at the average sensitivity can be divided into average sensitivities
Full Width at Half maximum feature (Full Width at Half maximum, F)WHM) and asymmetry characteristics. These two types of features affect the peak wavelength extraction of the dispersive confocal signal and thus can affect the measurement accuracy characteristics of the sensor.
The FWHM of the dispersive confocal signal in the dispersive confocal sensor spectral signal is not only related to the confocal characteristic parameter of the sensor, but also to the sensitivity of the sensor. When the spectral working bandwidth and the dispersion range of the sensor are not changed, the average sensitivity of the sensor is not changed regardless of the dispersion characteristic of the sensor
Is constant, while dispersing the confocal signal
Only on the confocal characteristic parameters. For this purpose, the quality index is used
The FWHM characteristic of a single frame dispersive confocal signal at average sensitivity is described, expressed as:
thus, the signal quality index is controlled
The configuration of the confocal characteristic of the sensor can be controlled.
The monochromatic aberration of the dispersive confocal optical system can cause the asymmetric distortion of the dispersive confocal signal, and the signal distortion greatly affects the signal processing precision. In optical design, the magnitude of aberration is often controlled by wave aberration and a scattered spot map (spot diagram). For this purpose, the quality index α is usedASYMThe asymmetry characteristic of the dispersed confocal signal at average sensitivity is described and expressed as:
αASYM＝rrms
wherein r isrmsThe RMS radius of the diffuse spot histogram in the in-focus state is shown. When r isrmsWhen the dispersion confocal signal is zero, the dispersion confocal signal is completely symmetrical, namely the asymmetry characteristic is zero; with rrmsThe asymmetry characteristic of the dispersive confocal signal increases.
In one possible embodiment, the quality indicator includes an inter-frame consistency characteristic of a multi-frame dispersive confocal signal; the interframe consistency characteristics of the multiframe dispersion confocal signal comprise sensitivity consistency characteristics and asymmetry consistency characteristics;
step S102 includes:
determining sensitivities with different full widths at half maximum corresponding to two-dimensional spectral signals with different displacements under non-constant sensitivity, calculating and determining the average sensitivity and the maximum sensitivity of each sensitivity, and obtaining the sensitivity consistency characteristic of the two-dimensional spectral signals based on the ratio of the average sensitivity to the maximum sensitivity;
calculating each RMS radius of each two-dimensional spectral signal under different displacements through the scattered spot sequence, and determining the asymmetry consistency characteristic of the two-dimensional spectral signals based on the ratio of the maximum RMS radius to the minimum RMS radius;
determining a quality indicator of the two-dimensional spectral signal based on the sensitivity consistency characteristic and the asymmetry consistency characteristic.
In the embodiment of the present application, as can be seen from fig. 3(a) and 3(b), the inter-frame consistency characteristic of the multiple frames of dispersive confocal signals in the dispersive confocal sensor spectrum signal can be divided into a sensitivity consistency characteristic and an asymmetry consistency characteristic. The two characteristics influence the extraction precision of the peak wavelength of the dispersive confocal signal at different displacement positions and the representation of the actual displacement-wavelength relation, thereby influencing the precision characteristic.
When the sensor confocal characteristic parameters are determined, the non-constant sensitivity may result in different FWHM of the confocal signals of different displacement dispersions. For this purpose, the quality index βKThe sensitivity consistency of the spectral signal of the dispersive confocal sensor is described and expressed as:
the signal quality index function can be conveniently obtained in an optical design.
The dispersion confocal signals at different displacement positions in the spectrum signals of the dispersion confocal sensor have different asymmetry degrees due to unequal monochromatic aberrations, and the peak wavelength extraction error of the dispersion confocal signals with different displacements and the actual displacement-wavelength characterization error of the sensor are caused by the above reasons, so that the precision characteristic of the sensor is influenced. For this purpose, the quality index β is usedαDescribing the asymmetry consistency characteristic of the spectrum signal of the dispersive confocal sensor, and the asymmetry consistency characteristic is expressed as follows:
wherein r isrms(l) The RMS radius of the scattered spot histogram at displacement i is expressed. Even under the same aberration, the working wavelength at different displacement positions is different, and the RMS radius of the dispersed spot diagram is also different, so the influence of the wavelength change needs to be considered when calculating the asymmetry consistency index.
In order to prove the influence of the quality index of the spectrum signal of the dispersive confocal sensor on the accuracy characteristics, the following verification is performed:
for the influence of the single-frame signal characteristics on the precision characteristics, determining the peak extraction error e of the dispersion confocal signal according to the peak wavelength expression of the dispersion confocal signaln(l) The following were used:
en(l)＝pn(l)-λo
wherein λ isoRepresents the ideal peak wavelength of the dispersive confocal signal at the shift l, expressed as:
λo＝Sinv(l)
discrete sample offset is an inherent property of a discrete confocal signal that represents the distance of the ideal peak of the signal to the nearest sample point. In practical studies, the sample sequence is subtracted from the nearest sample point of the ideal peak, when the discrete sample offset is equivalent to the ideal peak.
When signal to noise ratioWhen the SNR is 200 and the wavelength sampling interval satisfies FWHM 10 Δ λ, as shown in fig. 4, fig. 4 shows the relationship between the peak extraction error and the discrete sampling offset of a common peak extraction algorithm. It is clear that the center of gravity method (CA) and the fitting method based on the mathematical model include the parabolic fitting method (PFA), the Gaussian fitting method (GFA) and the sin2The fitting method has a peak value extraction system error and a standard deviation related to discrete sampling bias. Although the peak wavelength extraction error of the fitting method is much smaller than that of the gravity center method, the extraction accuracy depends on the matching degree of the fitting function model and the dispersion confocal signal model. Confocal signals are not gaussian or sin due to chromatic dispersion2The peak wavelength extraction error (including the system error and standard deviation) of the signal, therefore, is still as high as ± 0.04 Δ λ.
Aiming at the condition that the same algorithm has different peak positioning performances when different discrete sampling offsets exist and the discrete sampling offsets can take any value during actual measurement, the system error RMS value and the standard deviation RMS value extracted under the peak wavelength of different discrete sampling offsets (the variation range of the discrete sampling offsets is one wavelength sampling interval) are calculated and respectively recorded as EXPRMSAnd STDRMS. The peak positioning accuracy of the four common algorithms described above at this time is shown in the following table:
the error is calculated from the peak wavelength, and the sensor measurement error can be simplified as follows:
wherein the error e associated with the peak wavelength extraction system errorSYSRMS value reflecting the linearity error of the sensor, error e related to the peak wavelength extraction standard deviationSTDReflecting the axial resolution of the sensor.
When the spectral working bandwidth and the dispersion range of the sensor are determined, the average sensitivity K of the sensor is also determined, and the precision of the sensor is determined at the momentThe degree characteristic mainly depends on the peak wavelength extraction error. Assuming average sensitivity of the sensor
When the wavelength sampling interval Δ λ is 0.5nm, the measurement error of the sensor is estimated as shown in the following table:
due to eSYSAnd eSTDCalculated from the RMS value of the peak wavelength extraction error, the actual measurement error, such as the maximum linearity error and the maximum standard deviation, may be several times larger than the data in the table above, at this time, the linearity error of the sensor may reach ± 0.27 μm, and the axial resolution is about 120 nm.
According to the above, due to the difference between the dispersive confocal signal model and the fitting model, the discrete sampling offset may cause systematic error in the extraction of the peak wavelength of the signal, thereby causing linearity error of the sensor.
Specifically, for the effect of the full width at half maximum signature, when the dispersive confocal signal SNR is unchanged, as shown in fig. 5, fig. 5 illustrates the peak wavelength extraction error and the signal
The relationship between them. Peak wavelength extraction systematic error on signal
Is oscillated, the peak wavelength extraction standard deviation is taken along with the signal
Increasing to exhibit a linear increasing trend.
In the regulation of signal
In the meantime, attention needs to be paid
And the adaptability with the spectrum working bandwidth delta lambda, the dispersion range delta l and the spectrometer wavelength sampling interval delta lambda. First, the spectral operating bandwidth depends on the bandwidth of the broadband light source and the spectrometer, so the adaptation of the operating bandwidths of the light source and the spectrometer needs to be paid attention to when selecting or designing the two (usually, the operating bandwidth of the spectrometer is much larger than that of the broadband light source). Secondly, on the basis, the average sensitivity of the sensor is determined according to the requirement of the dispersion range, and a spectrometer with a proper wavelength sampling interval delta lambda is selected. Also, the adaptability between the spectrometer bandwidth and the wavelength sampling interval needs to be taken into account. Finally, regulating and controlling signals according to the axial resolution or linearity error requirement and the like of the sensor
For example, a decrease in dispersion range Δ l while the spectrometer wavelength sampling interval Δ λ and spectral operating bandwidth Δ Λ are constant can result in an average sensitivity
Increasing the size of the confocal characteristic parameter to optimize the axial resolution of the sensor
The relative relationship with the wavelength sampling interval Δ λ is unchanged.
For signal asymmetry characteristic rrmsIn terms of the influence of (a), it is verified that the dispersed confocal signal asymmetry characteristic, i.e. the dispersed confocal signal dispersion point histogram r in the focused statermsIn relation to the monochromatic aberration coefficient, W is taken040＝-4，W 0603 and W040＝-5，W060Two sizes of spherical aberration 4. Meanwhile, on the premise of ensuring that the signal-to-noise ratio and the confocal characteristic parameter of the signal are not changed, the relation between the relative extraction precision of the peak wavelength of the dispersion confocal signal and the monochromatic aberration coefficient is established, wherein the extraction precision of the peak wavelength of the zero-asymmetry signal is taken as a unit. When the aberration level exceeds W040＝-4，W060Signal pair No. 3The influence of degree of weighing is not great; when the aberration level exceeds W040＝-5，W060The signal peak extraction error increases dramatically, resulting in a dramatic increase in sensor axial resolution and linearity error.
As for the influence of the inter-signal feature on the accuracy characteristic, as shown in fig. 6, it can be seen that the sensor measurement error decreases as the sensitivity consistency characteristic index increases, so the sensor sensitivity consistency characteristic index is ensured in the sensor design process. In addition, the sensitivity consistency characteristic can cause the sensor to have different accuracies at different displacements, but the problem can be solved by means of light source power regulation and the like.
Characteristic index beta of consistency of sensitivity of regulation and control signalKIt is also necessary to avoid that the signal FWHM is too small, and to ensure that it is not less than 5 Δ λ, and the above choice has two purposes: firstly, the occurrence of great calculation errors during extraction of peak wavelengths is avoided; secondly, the spectrometer is a complex optical system, and even an ideal monochromatic wavelength will present a frame of a limited broadband spectral signal on the detector of the spectrometer, i.e. the transfer function of the spectrometer will span several wavelength sampling intervals. Therefore, ensuring the signal FWHM is of a certain size can effectively avoid the problem that the spectrometer transfer function introduces additional signal distortion.
For the effect of the signal asymmetry uniformity characteristic, the relationship of the sensor linearity error to the asymmetry uniformity characteristic due to unequal amounts of aberrations when other conditions are unchanged is shown in fig. 7. When the variation range of the aberration coefficient is 0%, 10% and 20%, namely, the asymmetry degree consistency characteristic indexes are 1.00, 1.22 and 1.50, the linearity errors caused by the factors are 0.07 μm, 0.47 μm and 1.97 μm respectively. In addition, the above analysis ignores the factors such as peak wavelength extraction error introduced by asymmetry characteristic and peak wavelength extraction accuracy consistency caused by sensitivity consistency characteristic, and if the factors are comprehensively considered, the sensor linearity error will be larger. Therefore, in the sensor design process, the characteristic index of the asymmetric consistency of the signals needs to be regulated and controlled as much as possible. In the regulation process, the working wavelengths at different displacement positions are not consistent, so that the influence of wavelength change is eliminated when the characteristic index of the asymmetry consistency is calculated, and meanwhile, the maximum value of the signal asymmetry characteristic is ensured to be in a limited range in the process.
S103, optimizing the precision characteristic of the optical design process of the dispersive confocal sensor based on the quality index.
In the embodiment of the application, after the quality indexes related to the precision characteristics of the dispersion confocal sensor are determined, the precision characteristic design optimization is performed on the optical design process of the dispersion confocal sensor reversely based on the quality indexes, and then the continuous optimization of the precision characteristics of the dispersion confocal sensor produced subsequently is realized.
In particular, the axial resolution of the sensor depends primarily on the single frame signal
And signal asymmetry characteristics. Assuming average sensitivity of the sensor
SNR is 200, wavelength sampling interval Δ λ is 0.5nm, if this is the case
The dispersion confocal signal peak wavelength extraction standard deviation is about 0.02 delta lambda, i.e. the sensor axial resolution is about 120 nm. Based on the foregoing, the signal asymmetry characteristic will deteriorate the extraction of the peak wavelength of the signal, but if the signal asymmetry characteristic is controlled within a reasonable range, for example, the error introduced by the asymmetry characteristic is not more than 1.3 times of that in the symmetric state, the axial resolution of the sensor is about 160 nm. The signal can be roughly determined by using the estimation according to known conditions such as dispersion range and spectral working bandwidth and the like facing specific axial resolution requirements
So as to determine the value of the confocal characteristic parameter of the sensor.
The linearity error of the sensor mainly originates from a system error extracted by a dispersion confocal signal peak value and a characterization error of an actual displacement-wavelength relation. Under the aforementioned conditions, the linearity error due to the signal peak wavelength extraction system error is about ± 0.27 μm. In addition, the non-uniformity characteristic of sensitivity and the non-symmetry uniformity characteristic both cause additional linearity errors.
Therefore, when the sensor is designed, the sensitivity consistency characteristic of the sensor can be preferentially improved according to the conditions such as the limitation of design cost; and then, linear errors caused by peak wavelength extraction system errors, sensitivity consistency characteristics, asymmetry consistency characteristics and the like are inhibited by developing a high-precision peak wavelength extraction algorithm and a high-precision calibration method. And on the basis, the characteristic index of the asymmetry consistency of the sensor is improved as much as possible.
The following describes in detail the evaluation apparatus for spectral signal quality of a dispersive confocal sensor according to an embodiment of the present invention with reference to fig. 8. It should be noted that the apparatus for evaluating the spectral signal quality of the dispersive confocal sensor shown in fig. 8 is used for executing the method of the embodiment shown in fig. 1 of the present invention, and for convenience of description, only the portion related to the embodiment of the present invention is shown, and details of the technology are not disclosed, please refer to the embodiment shown in fig. 1 of the present invention.
Referring to fig. 8, fig. 8 is a diagram illustrating an apparatus for evaluating the quality of a spectrum signal of a dispersive confocal sensor according to an embodiment of the present invention. As shown in fig. 8, the apparatus includes:
an obtaining module 801, configured to obtain and collect a two-dimensional spectral signal of a chromatic dispersion confocal sensor;
a processing module 802, configured to perform signal processing and signal quality evaluation on the two-dimensional spectrum signal, and determine a quality index of the two-dimensional spectrum signal;
an optimizing module 803, configured to perform precision characteristic optimization on the optical design process of the dispersive confocal sensor based on the quality index.
In an implementation manner, the processing module 802 is specifically configured to:
collecting standard spectrum signals of the dispersion confocal sensor under different standard displacements;
extracting the standard peak wavelength of each frame of the standard spectrum signal, and constructing a mapping relation between standard displacement and the extracted standard peak wavelength;
after the two-dimensional spectrum signal of the dispersion confocal sensor is collected in actual measurement, extracting the actual peak wavelength of the two-dimensional spectrum signal, and performing sensor displacement decoding according to the mapping relation to obtain a sensor displacement measurement result;
and determining a sensor calibration error corresponding to the sensor displacement measurement result, and determining the sensor calibration error as an actual measurement error of the sensor.
In an implementation manner, the processing module 802 is specifically configured to:
keeping the spectrum working bandwidth and the dispersion range of the dispersion confocal sensor unchanged, and calculating the full-width half-maximum characteristic of the two-dimensional spectrum signal;
calculating and controlling monochromatic aberration of the dispersive confocal sensor through wave aberration and a diffuse spot sequence diagram, and determining the asymmetry characteristic of the two-dimensional spectral signal based on the monochromatic aberration;
determining a quality indicator of the two-dimensional spectral signal based on the full-width-at-half-maximum feature and the asymmetry feature.
In an implementation manner, the processing module 802 is specifically configured to:
determining sensitivities with different full widths at half maximum corresponding to two-dimensional spectral signals with different displacements under non-constant sensitivity, calculating and determining the average sensitivity and the maximum sensitivity of each sensitivity, and obtaining the sensitivity consistency characteristic of the two-dimensional spectral signals based on the ratio of the average sensitivity to the maximum sensitivity;
calculating each RMS radius of each two-dimensional spectral signal under different displacements through the scattered spot sequence, and determining the asymmetry consistency characteristic of the two-dimensional spectral signals based on the ratio of the maximum RMS radius to the minimum RMS radius;
determining a quality indicator of the two-dimensional spectral signal based on the sensitivity consistency characteristic and the asymmetry consistency characteristic.
It is clear to a person skilled in the art that the solution according to the embodiments of the invention can be implemented by means of software and/or hardware. The "unit" and "module" in this specification refer to software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), or the like.
Each processing unit and/or module according to the embodiments of the present invention may be implemented by an analog circuit that implements the functions described in the embodiments of the present invention, or may be implemented by software that executes the functions described in the embodiments of the present invention.
Referring to fig. 9, a schematic structural diagram of an electronic device according to an embodiment of the present invention is shown, where the electronic device may be used to implement the method in the embodiment shown in fig. 1. As shown in fig. 9, the electronic device 900 may include: at least one central processor 901, at least one network interface 904, a user interface 903, a memory 905, at least one communication bus 902.
Wherein a communication bus 902 is used to enable connective communication between these components.
The user interface 903 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 903 may also include a standard wired interface and a wireless interface.
The network interface 904 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
The central processor 901 may include one or more processing cores. The central processor 901 connects various parts within the overall terminal 900 using various interfaces and lines, and performs various functions of the terminal 900 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 905, and calling data stored in the memory 905. Optionally, the central Processing unit 901 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The CPU 901 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It is to be understood that the modem may not be integrated into the central processor 901, and may be implemented by a single chip.
The Memory 905 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 905 includes a non-transitory computer-readable medium. The memory 905 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 905 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described method embodiments, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 905 may optionally be at least one storage device located remotely from the central processor 901. As shown in fig. 9, the memory 905, which is a type of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and program instructions.
In the electronic device 900 shown in fig. 9, the user interface 903 is mainly used for providing an input interface for a user to obtain data input by the user; and the processor 901 may be configured to invoke an evaluation application program of the spectral signal quality of the dispersive confocal sensor stored in the memory 905, and specifically perform the following operations:
acquiring and collecting a two-dimensional spectrum signal of a dispersion confocal sensor;
performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal;
and optimizing the precision characteristic of the optical design process of the dispersive confocal sensor based on the quality index.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus can be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some service interfaces, devices or units, and may be an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure are intended to be included within the scope of the present disclosure. Embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (6)
1. A method for evaluating the quality of a spectral signal of a dispersive confocal sensor, which is characterized by comprising the following steps:
acquiring and collecting a two-dimensional spectrum signal of a dispersion confocal sensor;
performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal;
performing precision characteristic optimization on the optical design process of the dispersion confocal sensor based on the quality index;
the quality index comprises single-frame dispersion confocal signal characteristics at the average sensitivity; the single-frame dispersion confocal signal features at the average sensitivity comprise full-width-at-half-maximum features and asymmetry features;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
keeping the spectrum working bandwidth and the dispersion range of the dispersion confocal sensor unchanged, and calculating the full-width half-maximum characteristic of the two-dimensional spectrum signal;
calculating and controlling monochromatic aberration of the dispersive confocal sensor through wave aberration and a diffuse spot sequence diagram, and determining the asymmetry characteristic of the two-dimensional spectral signal based on the monochromatic aberration;
determining a quality indicator of the two-dimensional spectral signal based on the full-width-at-half-maximum feature and the asymmetry feature.
2. The method of claim 1, wherein the quality indicator comprises a sensor actual measurement error;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
collecting standard spectrum signals of the dispersion confocal sensor under different standard displacements;
extracting the standard peak wavelength of each frame of the standard spectrum signal, and constructing a mapping relation between standard displacement and the extracted standard peak wavelength;
after the two-dimensional spectrum signal of the dispersion confocal sensor is collected in actual measurement, extracting the actual peak wavelength of the two-dimensional spectrum signal, and performing sensor displacement decoding according to the mapping relation to obtain a sensor displacement measurement result;
and determining a sensor calibration error corresponding to the sensor displacement measurement result, and determining the sensor calibration error as an actual measurement error of the sensor.
3. The method of claim 1, wherein the quality indicator comprises an inter-frame consistency characteristic of a multiframe of a dispersive confocal signal; the interframe consistency characteristics of the multiframe dispersion confocal signal comprise sensitivity consistency characteristics and asymmetry consistency characteristics;
the performing signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal includes:
determining sensitivities with different full widths at half maximum corresponding to two-dimensional spectral signals with different displacements under non-constant sensitivity, calculating and determining the average sensitivity and the maximum sensitivity of each sensitivity, and obtaining the sensitivity consistency characteristic of the two-dimensional spectral signals based on the ratio of the average sensitivity to the maximum sensitivity;
calculating each RMS radius of each two-dimensional spectral signal under different displacements through the scattered spot sequence, and determining the asymmetry consistency characteristic of the two-dimensional spectral signals based on the ratio of the maximum RMS radius to the minimum RMS radius;
determining a quality indicator of the two-dimensional spectral signal based on the sensitivity consistency characteristic and the asymmetry consistency characteristic.
4. An apparatus for evaluating the quality of a dispersive confocal sensor spectral signal, the apparatus comprising:
the acquisition module is used for acquiring and collecting a two-dimensional spectrum signal of the dispersion confocal sensor;
the processing module is used for performing signal processing and signal quality evaluation on the two-dimensional spectrum signal and determining a quality index of the two-dimensional spectrum signal;
the optimization module is used for optimizing the precision characteristic of the optical design process of the dispersion confocal sensor based on the quality index;
wherein the quality indicator comprises a single-frame dispersion confocal signal characteristic at average sensitivity; the single-frame dispersion confocal signal features at the average sensitivity comprise full-width-at-half-maximum features and asymmetry features;
the processing module performs signal processing and signal quality evaluation on the two-dimensional spectrum signal to determine a quality index of the two-dimensional spectrum signal, and the method comprises the following steps:
keeping the spectrum working bandwidth and the dispersion range of the dispersion confocal sensor unchanged, and calculating the full-width half-maximum characteristic of the two-dimensional spectrum signal;
calculating and controlling monochromatic aberration of the dispersive confocal sensor through wave aberration and a diffuse spot sequence diagram, and determining the asymmetry characteristic of the two-dimensional spectral signal based on the monochromatic aberration;
determining a quality indicator of the two-dimensional spectral signal based on the full-width-at-half-maximum feature and the asymmetry feature.
5. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-3 are implemented when the computer program is executed by the processor.
6. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110264422.XA CN113074814B (en) | 2021-03-11 | 2021-03-11 | Method and device for evaluating quality of spectral signal of dispersion confocal sensor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110264422.XA CN113074814B (en) | 2021-03-11 | 2021-03-11 | Method and device for evaluating quality of spectral signal of dispersion confocal sensor |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113074814A CN113074814A (en) | 2021-07-06 |
| CN113074814B true CN113074814B (en) | 2022-03-29 |
Family
ID=76612203
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110264422.XA Active CN113074814B (en) | 2021-03-11 | 2021-03-11 | Method and device for evaluating quality of spectral signal of dispersion confocal sensor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113074814B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114235785A (en) * | 2021-11-09 | 2022-03-25 | 合肥金星智控科技股份有限公司 | Laser-induced breakdown spectroscopy quality determination method and system |
| CN116880907B (en) * | 2023-08-30 | 2024-01-30 | 武汉精一微仪器有限公司 | Real-time wavelength peak value extraction method, device, equipment and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109186458A (en) * | 2018-09-28 | 2019-01-11 | 华中科技大学 | A kind of compensation fitting differential signal method for the confocal peak extraction of dispersion |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102006007170B4 (en) * | 2006-02-08 | 2009-06-10 | Sirona Dental Systems Gmbh | Method and arrangement for fast and robust chromatic confocal 3D metrology |
| US20110286006A1 (en) * | 2010-05-19 | 2011-11-24 | Mitutoyo Corporation | Chromatic confocal point sensor aperture configuration |
| CN107131855B (en) * | 2017-04-14 | 2020-02-14 | 中国科学院光电研究院 | Spectrum confocal measurement system calibration device and calibration method |
| CN110095066B (en) * | 2019-03-04 | 2020-04-10 | 华中科技大学 | Spectral confocal signal peak wavelength rapid high-precision extraction method based on Mean-shift |
| CN111208633B (en) * | 2020-01-09 | 2020-10-23 | 华中科技大学 | Optimization method of characteristic parameters of dispersion confocal microscope |
-
2021
- 2021-03-11 CN CN202110264422.XA patent/CN113074814B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109186458A (en) * | 2018-09-28 | 2019-01-11 | 华中科技大学 | A kind of compensation fitting differential signal method for the confocal peak extraction of dispersion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113074814A (en) | 2021-07-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113074814B (en) | Method and device for evaluating quality of spectral signal of dispersion confocal sensor | |
| Desimoni et al. | About estimating the limit of detection by the signal to noise approach | |
| CN109596543B (en) | Spectral reflectivity reconstruction method for particle swarm optimization multi-core support vector regression | |
| US20190238581A1 (en) | Method, apparatus and system for detecting abnormal behavior of user | |
| CN105719033B (en) | Method and device for identifying object risk | |
| Zheng et al. | Realized volatility and absolute return volatility: a comparison indicating market risk | |
| JP2016070812A (en) | Device, method, and program for determining transformer connection phase | |
| Beleites et al. | Assessing and improving the stability of chemometric models in small sample size situations | |
| Fan et al. | Predictive quantile regressions under persistence and conditional heteroskedasticity | |
| US9565060B2 (en) | Managing a network connection for use by a plurality of application program processes | |
| CN115439160A (en) | Anomaly monitoring method, apparatus, device, medium, and program product | |
| CN109086954B (en) | Prediction method, device, equipment and medium for predicting yield based on fund flow | |
| US10129466B2 (en) | Image generating apparatus, image generating method, and image generating program | |
| JP6555164B2 (en) | Particle size distribution measuring apparatus, data processing method, and data processing program | |
| US20220260489A1 (en) | System and method for analyzing molecular interactions on living cells using biosensor techniques | |
| JP6332545B2 (en) | Noise level estimation method, measurement data processing apparatus, and measurement data processing program | |
| CN111415066A (en) | Risk assessment method and device | |
| Huckvale et al. | Reference image selection for difference imaging analysis | |
| CN109800816A (en) | A kind of multichannel Raman spectrum method for reconstructing, terminal device and storage medium | |
| CN113256328B (en) | Method, device, computer equipment and storage medium for predicting target clients | |
| Tsvetkov | Analysis of the results of a comparison of two standards | |
| CN113362137B (en) | Insurance product recommendation method and device, terminal equipment and storage medium | |
| KR102569395B1 (en) | Data broker device of competitive data trading system and operating method thereof | |
| CN109656803B (en) | Information pushing method and device and electronic equipment | |
| KR102569393B1 (en) | System and method for competitive data trading according to non-cooperative competition |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |