Method for correcting influence of light source photothermal effect on sample spectrum

Abstract

The invention relates to the technical field of spectral analysis, and discloses a method for correcting the influence of a light source photothermal effect on a sample spectrum. The method comprises the following steps: collecting a plurality of sample spectrums of a target sample under the influence of a light source photothermal effect; according to the first spectral information and the second spectral information, obtaining a first projection matrix of a spectrum related to the to-be-detected component / property of the sample and a second projection matrix of a spectrum influenced by the photothermal effect of a light source by adopting an orthogonal projection method; acquiring a difference matrix formed by differences among the multiple sample spectrums, and performing sparse principal component analysis on the difference matrix to acquire a load matrix capable of mapping spectral information in the sample spectrums into a subspace only influenced by the photothermal effect of the light source; the second projection matrix is determined according to the load matrix, the first projection matrix is determined according to the second projection matrix, the first projection matrix is adopted to correct the sample spectrum under the influence of the light source photothermal effect, and the evaluation precision of the to-be-detected component / property of the sample is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of spectral analysis, and particularly relates to a correction method, device, equipment and medium for the influence of the light - heat effect of a light source on a sample spectrum. Background Technique

[0002] Spectral analysis technology is an advanced means that can realize rapid and non - destructive detection of the components or properties of substances, and is widely used in many industries such as agriculture, food, medicine, and petrochemical industry. Spectral analysis technology uses the collected spectra of substances, such as Raman spectra, near - infrared spectra, etc., and combines with a pre - established chemometric model to qualitatively or quantitatively evaluate the components and properties of substances. In the establishment of the chemometric database and the spectral test process, the quality requirements for the acquisition of sample spectra are relatively high.

[0003] At present, some solid materials with a uniform surface and non - transparency (referred to as "samples" in the present invention) often adopt the form of diffuse reflection testing for spectral acquisition. Diffuse reflection light sources generally have a relatively large power. When continuously irradiating the sample, the light - heat effect of the light source will cause the temperature of the sample to rise significantly. Along with the rapid evaporation of adsorbed substances including moisture, it will cause a large change in the sample spectrum. This spectral change will affect the accuracy of the chemometric model, resulting in a decrease in the evaluation accuracy of the sample components or properties. Summary of the Invention

[0004] The purpose of the present invention is to provide a correction method, system, equipment and medium for the influence of the light - heat effect of a light source on a sample spectrum, which can solve the technical problem that the light - heat effect of the light source causes a large change in the sample spectrum, resulting in a decrease in the evaluation accuracy of the sample components or properties.

[0005] To solve the above - mentioned technical problem, an embodiment of the present invention provides a correction method for the influence of the light - heat effect of a light source on a sample spectrum, including the following steps: Collect multiple sample spectra of a target sample under the influence of the light - heat effect of the light source. The spectral information in the sample spectra includes first spectral information related to the components / properties to be measured of the sample and second spectral information generated under the influence of the light - heat effect of the light source; According to the first spectral information and the second spectral information, using the orthogonal projection method, respectively obtain a first projection matrix of the spectrum related to the components / properties to be measured of the sample and a second projection matrix of the spectrum affected by the light - heat effect of the light source; wherein, the first projection matrix and the second projection matrix are orthogonal; Obtain a difference matrix formed by the differences between multiple sample spectra, and through sparse principal component analysis of the difference matrix, obtain a loading matrix that can map the spectral information in the sample spectrum to a subspace only affected by the light - heat effect of the light source; Determine the second projection matrix according to the load matrix, and determine the first projection matrix according to the second projection matrix, so as to correct the sample spectrum affected by the photothermal effect of the light source using the first projection matrix.

[0006] Further, perform sparse principal component analysis on the difference matrix through the following formula: ; In the formula, represents the j th load vector, α represents the process value of the load vector, represents the difference matrix, represents the covariance matrix of the difference matrix, represents elastic net regularization, and is a preset parameter for controlling the regularization strength; The load matrix is: L = { l 1, l 2, … l m}; In the formula, m is an integer greater than 1.

[0007] Further, the second projection matrix is obtained through the following formula: ; In the formula, Q represents the second projection matrix.

[0008] Further, correct the sample spectrum affected by the photothermal effect of the light source through the following formula: ; In the formula, represents the corrected sample spectrum, represents the sample spectrum before correction, and P represents the first projection matrix.

[0009] Further, before obtaining the first projection matrix related to the spectrum of the sample to be measured component / property and the second projection matrix of the spectrum affected by the photothermal effect of the light source respectively by using the orthogonal projection method according to the first spectral information and the second spectral information, it further includes: Adopt the Savitzky-Golay smoothing method to fit the jumping noise data in the sample spectrum into smooth polynomial data in the form of polynomial fitting within a preset window.

[0010] An embodiment of the present invention also provides a correction device for the influence of the photothermal effect of a light source on a sample spectrum, including: A spectral acquisition module for acquiring multiple sample spectra of a target sample under the influence of the photothermal effect of a light source, where the spectral information in the sample spectra includes first spectral information related to the components / properties to be measured of the sample and second spectral information generated under the influence of the photothermal effect of the light source; A matrix transformation module for respectively obtaining a first projection matrix of the spectrum related to the components / properties to be measured of the sample and a second projection matrix of the spectrum affected by the photothermal effect of the light source by using the orthogonal projection method according to the first spectral information and the second spectral information; wherein, the first projection matrix and the second projection matrix are orthogonal; A matrix analysis module for obtaining a difference matrix formed by the differences between multiple sample spectra and obtaining a loading matrix that can map the spectral information in the sample spectra to a subspace only affected by the photothermal effect of the light source through sparse principal component analysis of the difference matrix; A spectral correction module for determining the second projection matrix according to the loading matrix and determining the first projection matrix according to the second projection matrix, so as to correct the sample spectra under the influence of the photothermal effect of the light source by using the first projection matrix.

[0011] An embodiment of the present invention also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, instructions executable by the at least one processor are stored in the memory, and when the instructions are executed by the at least one processor, the at least one processor can execute the above-mentioned correction method for the influence of the photothermal effect of the light source on the sample spectra.

[0012] An embodiment of the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned correction method for the influence of the photothermal effect of the light source on the sample spectra is implemented.

[0013] The correction method for the influence of the photothermal effect of the light source provided by the present invention has at least the following beneficial effects: Since the spectral information in the sample spectra includes first spectral information related to the components / properties to be measured of the sample and second spectral information generated under the influence of the photothermal effect of the light source, the present invention represents the relationship between these in matrix form, and obtains a first projection matrix of the spectrum related to the components / properties to be measured of the sample and a second projection matrix of the spectrum affected by the photothermal effect of the light source. If it is necessary to correct the sample spectra under the influence of the photothermal effect of the light source, it is necessary to obtain a spectral projection matrix independent of the photothermal effect, that is, the first projection matrix of the spectrum related to the components / properties to be measured of the sample, and since the first projection matrix and the second projection matrix are orthogonal, it is necessary to first obtain the second projection matrix of the spectrum affected by the photothermal effect of the light source.

[0014] At this time, the differences between multiple sample spectra are obtained and formed into a difference matrix. By performing sparse principal component analysis on the difference matrix, the spectral information in the sample spectra can be mapped to a loading matrix in the subspace that is only affected by the photothermal effect of the light source, so as to obtain the sparse characteristic information that regularly changes in the multiple spectra, which represents the characteristic information in the sample spectra that is only affected by the photothermal effect of the light source. Based on this, the second projection matrix can be determined, and then the first projection matrix can be determined to obtain a projection matrix orthogonal to the influence of the photothermal effect, so as to correct the sample spectra affected by the photothermal effect of the light source through this projection matrix and improve the evaluation accuracy of the sample components or properties. Brief Description of the Drawings

[0015] One or more embodiments are exemplarily illustrated by the pictures in the corresponding drawings, and these exemplary illustrations do not constitute a limitation on the embodiments.

[0016] Figure 1 is a flowchart of a method for correcting the influence of the photothermal effect of a light source on a sample spectrum provided according to an embodiment of the present invention Figure 1 ; Figure 2 is a flowchart of a method for correcting the influence of the photothermal effect of a light source on a sample spectrum provided according to an embodiment of the present invention Figure 2 ; Figure 3 is a schematic diagram of a spectrum under the influence of a photothermal effect provided according to an embodiment of the present invention; Figure 4 is a schematic diagram of a smoothed spectrum provided according to an embodiment of the present invention; Figure 5 is a schematic diagram of a corrected spectrum provided according to an embodiment of the present invention. Detailed Embodiments

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in the embodiments of the present invention, many technical details are provided to help readers better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions required to be protected by the present invention can still be implemented. The following division of each embodiment is for convenience of description and should not constitute any limitation on the specific implementation manner of the present invention. The various embodiments can be combined and cross-referenced with each other on the premise of not conflicting with each other.

[0018] The spectral analysis industry has not paid attention to the influence of the photothermal effect of the light source. The photothermal effect of the light source mainly affects materials containing a large amount of easily heat-volatile components (such as moisture, etc.). The volatilization of these components will cause the spectrum of the sample to change significantly in specific wavelength bands. For example, the volatilization of moisture will cause obvious changes in the spectrum of the sample at 1400nm and 1920nm.

[0019] Currently, there is no correction technology for spectra under the photothermal effect of the light source. Some general spectral correction methods, such as the preprocessing methods of noise reduction, baseline correction, and scattering correction commonly used in near-infrared spectroscopy, cannot correct partial distortions of the spectrum, so the correction of the influence of the photothermal effect cannot be achieved. And some related wavelength band deletion and spectral nonlinear correction methods will cause loss of effective information.

[0020] However, the correction method for the influence of the photothermal effect of the light source of the present invention can achieve spectral correction for the influence of the photothermal effect of the light source, can retain the effective information of the spectrum to the greatest extent, and avoid the loss of spectral information brought by methods such as wavelength band deletion and spectral nonlinear correction.

[0021] An embodiment of the present invention relates to a correction method for the influence of the photothermal effect of the light source on the sample spectrum. The implementation details of the correction method for the influence of the photothermal effect of the light source in this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0022] The specific process of the correction method for the influence of the photothermal effect of the light source in this embodiment can be as Figure 1 shown, including: Step 101, collect multiple sample spectra of the target sample under the influence of the photothermal effect of the light source. The spectral information in the sample spectra includes first spectral information related to the components / properties to be measured of the sample, and second spectral information generated under the influence of the photothermal effect of the light source.

[0023] Specifically, obtain a set of spectra under the influence of the photothermal effect of the light source. Use the light source of the spectrometer probe to continuously irradiate the sample, and collect the spectrum of the sample every 5s to obtain a set of spectra S = { S 1, S 2, …, S n}, S i where each is the spectrum collected each time S = { x 1, x 2, …, x d}. To achieve a better correction effect, n it needs to be greater than 10, that is, at least 10 spectra are collected.

[0024] Step 102: According to the first spectral information and the second spectral information, the orthogonal projection method is used to respectively obtain a first projection matrix of the spectrum related to the component / property to be measured of the sample and a second projection matrix of the spectrum affected by the photothermal effect of the light source; wherein, the first projection matrix and the second projection matrix are orthogonal.

[0025] Specifically, let S be the two-dimensional space composed of spectra, which can be specifically expressed as: S = C + G + R ; In the formula, C is the spectral information related to the property / component to be measured of the sample (i.e., the first spectral information), G is the spectral perturbation information generated by external irrelevant parameters, such as the spectral information generated by the photothermal effect of the light source (i.e., the second spectral information), R is the noise information.

[0026] Expressing the above formula in matrix form is: X = X P +X Q +R ; In the formula, P is the projection matrix of the spectrum related to the property / component to be measured of the sample (i.e., the first projection matrix), and Q is the projection matrix of the spectrum affected by the photothermal effect (i.e., the second projection matrix).

[0027] In one example, using the orthogonal projection method, the spectrum needs to ensure low noise. Therefore, before obtaining the first projection matrix of the spectrum related to the component / property to be measured of the sample and the second projection matrix of the spectrum affected by the photothermal effect of the light source according to the first spectral information and the second spectral information by using the orthogonal projection method, the Savitzky-Golay smoothing method is first used to reduce the spectral noise. This method fits the jumping noise data in the sample spectrum into smooth polynomial data in the form of polynomial fitting within a preset window. Considering the retention rate of data information and the window size w is closely related. For this method, the window size should not exceed 2% of the number of spectral features, and the polynomial order k can be taken as 2 - 4 orders.

[0028] Within the smoothing window, use k times of polynomial fitting for the original data, as follows: ; In the formula, c 0~ c k are the preset fitting coefficients, obtained by performing least squares fitting within the window. The sliding window calculates the y at the center of each window successively, and finally obtains the smoothed spectrum Ss-g ={ y 1, y 2,…, y d}, d which is the spectral dimension.

[0029] Step 103: Obtain a difference matrix formed by the differences between multiple sample spectra, and through performing sparse principal component analysis on the difference matrix, obtain a loading matrix that can map the spectral information in the sample spectra to a subspace affected only by the photothermal effect of the light source; Specifically, in the two-dimensional space composed of spectra in matrix form, R can be ignored, so we can get X P = X - X Q, that is, X P = X (I - Q), where I is the identity matrix. Since Q is the projection matrix of the perturbed part of the original spectra, Q can be obtained by performing calculations on the difference matrix D under spectral perturbation. Specifically, perform sparse principal component analysis on D T D (the covariance matrix of D, which captures the linear relationships between variables in the original data), and the data can be transformed into a new coordinate system. The matrix that realizes this transformation is the loading matrix L.

[0030] Among them, the difference matrix is calculated by the following formula: ; In the formula, The n th smoothed sample spectrum.

[0031] And perform sparse principal component analysis on the covariance matrix of the difference matrix through the following formula: ; In the formula, represents the j th loading vector, α represents the process value of the loading vector, represents the difference matrix, represents the covariance matrix of the difference matrix, represents elastic net regularization, and is a preset parameter for controlling the regularization strength.

[0032] The loading matrix is: L = { l 1, l 2,… l m}; In the formula, mis an integer greater than 1, obtained by cumulative feature contribution degree of sparse principal component analysis, and taking the load vector corresponding to the first 99.9% of the cumulative feature contributions.

[0033] Step 104, determine the second projection matrix according to the load matrix, and determine the first projection matrix according to the second projection matrix, so as to correct the sample spectrum affected by the photothermal effect of the light source using the first projection matrix.

[0034] Specifically, the load matrix can be considered as mapping the information of the original spectrum into a subspace only affected by spectral differences (i.e., the subspace only affected by the photothermal effect of the light source). Therefore, the second projection matrix of the spectrum affected by the photothermal effect of the light source can be determined through the load matrix as follows: ; This formula is a classical matrix operation. Q represents a projection matrix (i.e., the second projection matrix), which is obtained by projecting an arbitrary vector onto the subspace spanned by the columns of L. Therefore, the Q subspace correlation matrix can be called the subspace correlation matrix. Since P is orthogonal to Q, the orthogonal projection matrix P can finally be obtained by P = I - Q.

[0035] Finally, for the spectrum after Savitzky-Golay smoothing S s-g , the corrected spectrum can be calculated through the following formula s c : .

[0036] In this embodiment, since the spectral information in the sample spectrum includes the first spectral information related to the component / property to be measured of the sample and the second spectral information generated under the influence of the photothermal effect of the light source, the present invention represents the relationship between these in matrix form, obtaining the first projection matrix of the spectrum related to the component / property to be measured of the sample and the second projection matrix of the spectrum affected by the photothermal effect of the light source. If it is necessary to correct the sample spectrum under the influence of the photothermal effect of the light source, it is necessary to obtain the spectral projection matrix independent of the photothermal effect, that is, the first projection matrix of the spectrum related to the component / property to be measured of the sample. Since the first projection matrix is orthogonal to the second projection matrix, it is necessary to first obtain the second projection matrix of the spectrum affected by the photothermal effect of the light source.

[0037] At this time, the differences between multiple sample spectra are obtained to form a difference matrix. By performing sparse principal component analysis on the difference matrix, the spectral information in the sample spectra can be mapped to a loading matrix in the subspace that is only affected by the photothermal effect of the light source, so as to obtain the sparse characteristic information that regularly changes in multiple spectra, which represents the characteristic information in the sample spectra that is only affected by the photothermal effect of the light source. Based on this, the second projection matrix can be determined, and then the first projection matrix can be determined to obtain a projection matrix orthogonal to the influence of the photothermal effect, so as to correct the sample spectra affected by the photothermal effect of the light source through this projection matrix and improve the evaluation accuracy of the sample components or properties.

[0038] Since insulating paper is a typical material susceptible to the photothermal effect of the light source, in a specific embodiment, taking the sample as insulating paper as an example, the correction method for the influence of the photothermal effect of the light source on the sample spectra of the present invention will be specifically described. The specific process of the correction method for the influence of the photothermal effect of the light source on the sample spectra in this embodiment is as Figure 2 shown and includes: 1. Spectral acquisition under the influence of the photothermal effect: Obtain a set of insulating paper spectra under the influence of the photothermal effect of the light source. The spectrometer uses a NIRQuest+2.2 fixed grating array detector type near-infrared spectrometer, equipped with an ISP-REF integrating sphere probe. Use the spectrometer probe light source to continuously irradiate the sample, and collect the spectra of the sample every 5 s for a total of 200 s to obtain a set of spectra S = { s 1, s 2,…, s n}, s i where is the spectrum collected each time s ={ x 1, x 2,…, x d}. For this embodiment, n is 41. The collected spectra are as Figure 3 shown. It can be seen that with the irradiation of the light source, the insulating paper spectra show an upward trend in some bands, indicating that the influence of the photothermal effect on the spectra is relatively large.

[0039] 2. Spectral data preprocessing: As an orthogonal projection method, the spectra need to ensure low noise. The Savitzky-Golay smoothing method is used to reduce the spectral noise. This method fits the jumping noise data into smooth polynomial data in the form of polynomial fitting within a certain window. Considering the retention rate of data information and the window size w is closely related. For this method, the window size should not exceed 2% of the spectral characteristic number. In this embodiment, it is taken as 11, and the polynomial order kTaking the 2nd to 4th order is sufficient. In this embodiment, a 3rd order polynomial is used. Within the smoothing window, use 3 the polynomial to fit the original data, and the smoothed spectrum is as shown in Figure 4 .

[0040] 3. Calculate the difference matrix: Take the spectrum of the first test s 1 as the reference spectrum, and take all 30 spectra as the calculation data for the interference orthogonal subspace projection matrix to calculate the difference matrix D.

[0041] 4. Calculate the difference spectral loading matrix through sparse principal component analysis: Perform sparse principal component analysis on DTD. On the premise of ensuring feature sparsity, extract its main patterns, that is, the subspace only affected by the photothermal effect of the light source. For this embodiment, m = 3 in the sparse principal component analysis.

[0042] 5. Calculate the subspace correlation matrix Q and the subspace orthogonal projection matrix P of the photothermal effect of the light source: The space spanned by L is the interference subspace of the photothermal effect of the light source, and Q is calculated based on this.

[0043] 6. Calculate the corrected spectrum: For the spectrum after Savitzky-Golay smoothing s s-g , for the remaining test spectral data, calculate the corrected spectrum s c . The spectrum used by the finally obtained subspace projection matrix almost coincides with the test data spectrum, indicating that the correction effect is good. Among them, the corrected spectrum can be as shown in Figure 5 .

[0044] The correction method for the influence of the photothermal effect of the light source of the present invention has the following beneficial effects: 1. Correct the spectrum through the subspace matrix orthogonal to the influence mode of the photothermal effect. This correction method does not require testing quantitative results, and the process is simple.

[0045] 2. Obtain the influence mode of the photothermal effect through sparse principal component analysis, and obtain the subspace correlation matrix of the spectral characteristics of the photothermal effect in the form of expansion by the loading matrix. This method can effectively extract the influence mode of the photothermal effect.

[0046] 3. The influence of the photothermal effect of the light source is proposed for the first time and is also the only solution at present.

[0047] 4. Applicable to the correction of the photo-thermal effect of all spectroscopic instruments, not limited to near-infrared spectrometers, and also applicable to all substances that will produce significant spectral changes under the influence of the photo-thermal effect, not limited to insulating paper.

[0048] 5. The implementation process is simple. The form of sampling orthogonal projection does not require quantification of the influence of the photo-thermal effect, and the operation threshold is low, making it suitable for all R & D personnel and instrument operators with relevant needs.

[0049] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of the present invention; adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of its algorithm and process, is within the protection scope of the invention.

[0050] Another embodiment of the present invention relates to a correction device for the influence of the photo-thermal effect of a light source on the spectrum of a sample. The implementation details of the correction device for the influence of the photo-thermal effect of a light source on the spectrum of a sample in this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution. The correction device for the influence of the photo-thermal effect of a light source on the spectrum of a sample in this embodiment includes: Specifically, a spectrum acquisition module for acquiring multiple sample spectra of a target sample under the influence of the photo-thermal effect of a light source. The spectral information in the sample spectra includes first spectral information related to the components / properties to be measured of the sample and second spectral information generated under the influence of the photo-thermal effect of the light source; A matrix transformation module for respectively obtaining a first projection matrix of the spectrum related to the components / properties to be measured of the sample and a second projection matrix of the spectrum affected by the photo-thermal effect of the light source by using the orthogonal projection method according to the first spectral information and the second spectral information; wherein, the first projection matrix and the second projection matrix are orthogonal; A matrix analysis module for obtaining a difference matrix formed by the differences between multiple sample spectra and obtaining a loading matrix that can map the spectral information in the sample spectra to the subspace only affected by the photo-thermal effect of the light source through sparse principal component analysis of the difference matrix; A spectrum correction module for determining the second projection matrix according to the loading matrix and determining the first projection matrix according to the second projection matrix, so as to correct the sample spectra under the influence of the photo-thermal effect of the light source by using the first projection matrix.

[0051] It is not difficult to find that this embodiment is a device embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment. The relevant technical details and technical effects mentioned in the above embodiments are still valid in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the above embodiments.

[0052] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, to highlight the innovative part of the present invention, units that are not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0053] Another embodiment of the present invention relates to a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for correcting the influence of the light source photothermal effect on the sample spectrum in the above embodiments.

[0054] Among them, the memory and the processor are connected by a bus. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be an element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted over the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0055] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory can be used to store the data used by the processor when executing operations.

[0056] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0057] That is, those skilled in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0058] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention. In actual applications, various changes can be made in form and details without departing from the spirit and scope of the present invention.

Claims

1. A method for correcting the influence of the photothermal effect of a light source on the spectrum of a sample, characterized in that: include: Collecting multiple sample spectra of the target sample under the influence of the photothermal effect of the light source, wherein the spectral information in the sample spectrum includes first spectral information related to the component / property to be measured in the sample, and second spectral information generated by the photothermal effect of the light source; According to the first spectral information and the second spectral information, an orthogonal projection method is used to respectively obtain a first projection matrix of a spectrum related to the component / property to be measured of the sample and a second projection matrix of a spectrum affected by the photothermal effect of the light source; wherein the first projection matrix is ​​orthogonal to the second projection matrix; Obtaining a difference matrix formed by differences between a plurality of sample spectra, and performing sparse principal component analysis on the difference matrix to obtain a loading matrix capable of mapping spectral information in the sample spectra into a subspace affected only by the photothermal effect of the light source; The second projection matrix is ​​determined according to the load matrix, and the first projection matrix is ​​determined according to the second projection matrix, so as to use the first projection matrix to correct the spectrum of the sample under the influence of the photothermal effect of the light source.

2. The method for correcting the influence of the light source photothermal effect on the sample spectrum according to claim 1, characterized in that: The sparse principal component analysis of the difference matrix is ​​performed by the following formula: ； In the formula, Indicates j load vector, α represents the process value of the load vector, represents the difference matrix, represents the covariance matrix of the dissimilarity matrix, represents elastic net regularization, and is the preset parameter to control the regularization strength; The load matrix is: L={ l 1, l 2,… l m }; In the formula, m is an integer greater than 1.

3. The method for correcting the influence of the light source photothermal effect on the sample spectrum according to claim 2, characterized in that: The second projection matrix is ​​obtained by the following formula: ； Where Q represents the second projection matrix.

4. The method for correcting the influence of the light source photothermal effect on the sample spectrum according to claim 3, characterized in that: The sample spectrum affected by the photothermal effect of the light source is corrected by the following formula: ； In the formula, represents the corrected sample spectrum, represents the sample spectrum before correction, and P represents the first projection matrix.

5. The method for correcting the influence of the light source photothermal effect on the sample spectrum according to claim 1, characterized in that: Before respectively acquiring a first projection matrix of a spectrum related to the components / properties to be measured of the sample and a second projection matrix of a spectrum affected by the photothermal effect of the light source by using an orthogonal projection method according to the first spectrum information and the second spectrum information, the method further includes: The Savitzky-Golay smoothing method is used to fit the jumping noise data in the sample spectrum into smooth polynomial data in the form of polynomial fitting within the preset window.

6. A correction device for the influence of the photothermal effect of a light source on the spectrum of a sample, characterized in that: include: A spectrum acquisition module is used to acquire multiple sample spectra of a target sample under the influence of the photothermal effect of a light source, wherein the spectral information in the sample spectrum includes first spectral information related to the component / property to be measured in the sample, and second spectral information generated under the influence of the photothermal effect of the light source; A matrix transformation module is used to obtain, according to the first spectral information and the second spectral information, a first projection matrix of the spectrum related to the component / property to be measured of the sample and a second projection matrix of the spectrum affected by the photothermal effect of the light source by using an orthogonal projection method; wherein the first projection matrix is ​​orthogonal to the second projection matrix; A matrix analysis module is used to obtain a difference matrix formed by the differences between multiple sample spectra, and to obtain a load matrix capable of mapping the spectral information in the sample spectra to a subspace affected only by the photothermal effect of the light source by performing sparse principal component analysis on the difference matrix; The spectrum correction module is used to determine the second projection matrix according to the load matrix, and determine the first projection matrix according to the second projection matrix, so as to use the first projection matrix to correct the spectrum of the sample under the influence of the photothermal effect of the light source.

7. A computer device, characterized in that: include: at least one processor; And, a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the correction method for the influence of the photothermal effect of the light source on the sample spectrum as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for correcting the influence of the photothermal effect of a light source on the spectrum of a sample as claimed in any one of claims 1 to 5 is implemented.

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