A spectrum peak determination method, system, storage medium and electronic device

Abstract

The present application belongs to the field of spectrum, and particularly relates to a spectrum peak determination method and system, a storage medium and an electronic device. The method comprises: sequentially performing baseline removal and spectrum denoising on a measured Raman signal to obtain a high-frequency noise signal and a standard spectrum; performing basic data calculation on the high-frequency noise signal and the standard spectrum, and obtaining a global signal-to-noise ratio of the measured Raman signal based on the basic data; judging the global signal-to-noise ratio and a threshold to obtain a judgment result, determining all spectrum peaks in the standard spectrum data, and screening the spectrum peaks according to preset conditions adjusted based on the judgment result to obtain final spectrum peaks. Through the pre-processing of the Raman spectrum, the additional calculation work in the peak searching process can be reduced. In addition, through the processing of the signal-to-noise ratio, the processing efficiency can be improved, and the accuracy of the spectrum peak determination can be improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of spectrum, and particularly relates to a spectrum peak determination method and system, a storage medium and an electronic device. BACKGROUND

[0002] Raman spectrum is a molecular scattering spectrum, and is an analysis technology for "fingerprint" identification of molecular structure. Raman scattering is generated by non-elastic scattering of light irradiation on a substance, and the position and intensity of a spectrum peak directly reflect structure and content information of the substance. Raman spectrum has advantages of rapidity, non-destructiveness, no need for sample pretreatment, and realization of online analysis, and laser Raman spectrum analysis technology is gradually becoming one of the fastest developing technologies. How to quickly find a spectrum peak in a spectrum has become an important research direction. SUMMARY

[0003] The application aims to provide a spectrum peak determination method and system, a storage medium and an electronic device.

[0004] The technical scheme for solving the above technical problem is as follows: a spectrum peak determination method, comprising:

[0005] Step 1, sequentially performing baseline removal processing and spectrum denoising processing on a measured Raman signal to obtain a high-frequency noise signal and a standard spectrum;

[0006] Step 2, performing basic data calculation on the high-frequency noise signal and the standard spectrum, and obtaining a global signal-to-noise ratio of the measured Raman signal based on the basic data;

[0007] Step 3, judging the global signal-to-noise ratio and a threshold to obtain a judgment result, determining all spectrum peaks in the standard spectrum data, and screening the spectrum peaks according to a preset condition adjusted based on the judgment result to obtain final spectrum peaks.

[0008] The application has the beneficial effects that: the pre-processing of the Raman spectrum can reduce additional calculation work in the peak searching process, and the processing efficiency can be improved and the accuracy of the spectrum peak determination can be improved by processing the signal-to-noise ratio.

[0009] On the basis of the above technical scheme, the application can be further improved as follows.

[0010] Further, the process of sequentially performing baseline removal processing and spectrum denoising processing on the measured Raman signal is as follows:

[0011] The measured Raman signal is sequentially subjected to baseline removal processing to obtain a first signal from which the baseline is removed, and the first signal is subjected to spectrum denoising processing by a high-pass filter to obtain a high-frequency noise signal of a measured spectrum and a standard spectrum.

[0012] Further, the basis data calculation of the high-frequency noise signal specifically includes:

[0013] calculating the standard deviation of the high-frequency noise signal and calculating the maximum value of the standard spectrum.

[0014] Further, the determination of all spectral peaks in the standard spectrum data specifically includes:

[0015] performing first-order difference processing on the standard spectrum data to obtain a first processing result, performing first-order difference processing on the first processing result to obtain a second processing result, and determining all spectral peaks based on the second processing result.

[0016] Further, the preset condition is:

[0017] removing spectral peaks with a half-peak width exceeding a first threshold value and removing spectral peaks with a height value lower than a second threshold value, the first threshold value and the second threshold value being parameters adjusted according to the judgment result.

[0018] Another technical solution of the present application to solve the above technical problems is as follows: a spectral peak determination system, comprising:

[0019] The first processing module is configured to sequentially perform baseline removal processing and spectrum denoising processing on the measured Raman signal to obtain a high-frequency noise signal and a standard spectrum.

[0020] The calculation module is configured to perform basis data calculation on the high-frequency noise signal and the standard spectrum, and obtain a global signal-to-noise ratio of the measured Raman signal based on the basis data.

[0021] The screening module is configured to judge the global signal-to-noise ratio and a threshold value to obtain a judgment result, determine all spectral peaks in the standard spectrum data, and screen the spectral peaks according to a preset condition adjusted based on the judgment result to obtain final spectral peaks.

[0022] The present application has the following advantages: through the pre-processing of the Raman spectrum, the additional calculation work in the peak searching process can be reduced, in addition, through the processing of the signal-to-noise ratio, the processing efficiency can be improved, and the accuracy of the spectral peak determination can be improved.

[0023] Further, the process of sequentially performing baseline removal processing and spectrum denoising processing on the measured Raman signal includes:

[0024] The baseline removal processing is sequentially performed on the measured Raman signal to obtain a first signal with the baseline removed, the spectrum denoising processing is performed on the first signal through a high-pass filter to obtain a high-frequency noise signal of the measured spectrum and a standard spectrum.

[0025] Further, the basis data calculation of the high-frequency noise signal specifically includes:

[0026] a standard deviation of the high-frequency noise signal is calculated, and a maximum value of the standard spectrum is calculated.

[0027] Further, the determining all spectral peaks in the standard spectrum data specifically comprises:

[0028] The standard spectrum data is subjected to first-order differential processing to obtain a first processing result, the first processing result is subjected to first-order differential processing to obtain a second processing result, and all spectral peaks are determined based on the second processing result.

[0029] Further, the preset condition is:

[0030] Spectral peaks with a half-peak width exceeding a first threshold value and spectral peaks with a height value lower than a second threshold value are removed, and the first threshold value and the second threshold value are parameters adjusted according to the determination result.

[0031] Another technical solution of the present application to solve the above technical problems is as follows: a storage medium, the storage medium stores instructions, when the computer reads the instructions, the computer executes the method as described in any one of the above.

[0032] The present application has the beneficial effects that: through the pre-processing of the Raman spectrum, the additional calculation work in the peak searching process can be reduced, in addition, through the processing of the signal-to-noise ratio, the processing efficiency can be improved, and the accuracy of the spectral peak determination is improved.

[0033] Another technical solution of the present application to solve the above technical problems is as follows: an electronic device, comprising the above storage medium and a processor executing the instructions in the above storage medium.

[0034] The present application has the beneficial effects that: through the pre-processing of the Raman spectrum, the additional calculation work in the peak searching process can be reduced, in addition, through the processing of the signal-to-noise ratio, the processing efficiency can be improved, and the accuracy of the spectral peak determination is improved. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 A flowchart is provided for an embodiment of a spectrum peak determination method of the present application;

[0036] Figure 2 A structural framework diagram is provided for an embodiment of a spectrum peak determination system of the present application;

[0037] Figure 3 An algorithm logic diagram is provided for an embodiment of a spectrum peak determination method of the present application;

[0038] Figure 4 A spectrum peak searching logic diagram is provided for an embodiment of a spectrum peak determination method of the present application;

[0039] Figure 5 A spectrum peak searching principle diagram provided by the spectrum peak determination method embodiment of the present application;

[0040] Figure 6 An ammonium nitrate spectrum diagram provided by the spectrum peak determination method embodiment of the present application;

[0041] Figure 7 An FWHM diagram provided by the spectrum peak determination method embodiment of the present application;

[0042] Figure 8 A spectrum baseline removal diagram provided by the spectrum peak determination method embodiment of the present application;

[0043] Figure 9 A spectrum denoising diagram provided by the spectrum peak determination method embodiment of the present application;

[0044] Figure 10 A first ammonium nitrate spectrum diagram provided by the spectrum peak determination method embodiment of the present application;

[0045] Figure 11 A second ammonium nitrate spectrum diagram provided by the spectrum peak determination method embodiment of the present application;

[0046] Figure 12 A spectrum peak searching effect diagram provided by the spectrum peak determination method embodiment of the present application. DETAILED DESCRIPTION

[0047] The principles and features of the present application are described below, and the examples are only used to explain the present application, and are not used to limit the scope of the present application.

[0048] As shown in Figure 1 A spectrum peak determination method comprises:

[0049] Step 1, the measured Raman signal is sequentially subjected to baseline removal processing and spectrum denoising processing, to obtain a high-frequency noise signal and a standard spectrum;

[0050] Step 2, the high-frequency noise signal and the standard spectrum are subjected to basic data calculation, and a global signal-to-noise ratio of the measured Raman signal is obtained based on the basic data;

[0051] Step 3, the global signal-to-noise ratio is compared with a threshold value to obtain a judgment result, all spectrum peaks are determined in the standard spectrum data, the spectrum peaks are screened according to a preset condition adjusted based on the judgment result, and a final spectrum peak is obtained.

[0052] In some possible embodiments, the pre-processing of the Raman spectrum can reduce the additional calculation work in the peak searching process, and the processing efficiency can be improved and the accuracy of the spectrum peak determination can be improved by processing the signal-to-noise ratio.

[0053] It should be noted that, as shown in Figure 3 , the real Raman spectrum should include three parts, i.e. the useful Raman signal, the baseline interference in the measured spectrum, the baseline interference, including the fluorescence and phosphorescence background of the sample itself, the sample container and the like, the black body radiation of the sample and the surrounding environment, and various noises, including the shot noise, the dark current noise and the readout noise of the CCD detector, the emission noise introduced by the excitation light source and the cosmic rays and the like, as shown in (1-1):

[0054] S1 = S0 + B + N (1-1)

[0055] wherein S1 represents the measured Raman signal, S0 represents the real Raman signal, B represents the baseline interference, and N is the comprehensive various noises. The baseline interference is removed before the signal-to-noise ratio is evaluated, and there are many ways to remove the baseline interference. The present patent takes the automated baseline estimation (ABE) method proposed by H. Georg Schulze as an example. The method smoothes the spectrum by using the cyclic sliding window average method, removes the positions in the original spectrum which are greater than the smoothed spectrum, and removes the baseline.

[0056] After the baseline is removed, the remaining spectrum is shown in formula (1-2), wherein S2 is the measured spectrum S1 removing the baseline

[0057] S2 = S0 + N (1-2)

[0058] The noise S0 is superimposed by a large number of random noises, and S0 can be considered to conform to the Gaussian distribution. The Gaussian noise is mainly concentrated in the high frequency domain. After the original signal is filtered by the high-pass filter, the low frequency signal is filtered out. The main part after the high-pass filter is the noise S3, and the interference of the useful signal is small, as shown in formula (1-3):

[0059] S3 = N1 (1-3)

[0060] wherein N1≈N, because S0 will be filtered out after S2 is filtered by the high-pass filter, and part of the information will also be lost, so the spectrum remaining after S2 is filtered by the high-pass filter is not completely equal to N. It is assumed that the standard deviation of the Gaussian noise in S2 is σ N , the standard deviation of the signal S3 filtered by a certain high-pass filter G is σ N1 , and the calculation method of σ N1 is as follows:

[0061] The unit impulse response sequence of the high-pass filter is g(n), then the power spectral density of N1, the spectral distribution of the high-pass filter, is divided into (1-4), (1-5) formula.

[0062]

[0063]

[0064] In the formula, w represents the digital angular frequency, w ∈ [-π, π].

[0065] N1 is obtained after N is filtered by a high-pass filter, which satisfies (1-6) formula

[0066] N1 = N * G (1-6)

[0067] After a series of derivations, (1-7) formula is obtained

[0068]

[0069] That is, the noise variance of the noise filtered by a certain high-pass filter is equal to the noise variance of the noise in the original signal multiplied by the square of the modulus of the filter response vector.

[0070] Therefore, the noise standard deviation σ N The core idea of estimation is to use the noise standard deviation filtered by a high-pass filter to estimate the noise standard deviation in the measured signal. There are many types of high-pass filters, and this patent takes the second-order difference method as an example. The second-order difference operation is equivalent to a high-pass filter with a unit impulse response sequence of [1, -2, 1]. After filtering by this high-pass filter, the low-frequency part of the measured signal is filtered out, including the Raman signal, etc. The remaining is various high-frequency noise, so the noise standard deviation after filtering by the second-order difference filter divided by the modulus of the impulse response sequence can obtain the estimated value of the noise standard deviation in the measured signal.

[0071] The specific calculation steps are as follows:

[0072] 1, First, remove the baseline of the obtained measured Raman signal S1 to obtain the baseline-removed signal S2;

[0073] 2, The second step is to pass S2 through a high-pass filter, spectrum denoising, and retain high-frequency noise S3;

[0074] 3, The third step calculates the standard deviation σ N of S3 _max ;

[0075] 4, The fourth step is to divide S _max by σ N , to obtain the global signal-to-noise ratio SNR of the measured Raman spectrum = S _max / σ N .

[0076] As Figure 4 shown, global signal-to-noise ratio (SNR) is crucial for spectral peak finding, which is modularly designed. The principle of obtaining all spectral peaks of spectral data is to find the boundary point where the monotonicity of spectral intensity changes, i.e., the extreme value. The monotonicity of the intensity of discrete data can be obtained by the difference method. The specific method is as shown in Figure 5

[0077] The first-order difference is as shown in (1-8):

[0078] Y = [y0(2) - y0(1) y0(3) - y0(2)... y0(m) - y0(m-1)] (1-8)

[0079] In the formula, y0 is the original spectral sequence, and m represents the length of the spectrum.

[0080] The sign function is defined as follows:

[0081] Y = sign(x) returns a sequence with the same length as x, and the elements in Y are specifically defined as follows:

[0082]

[0083] In the formula, x(i) is the ith element of x.

[0084] The specific peak finding calculation steps are as follows:

[0085] First-order difference of spectral data y0 to obtain difference spectrum y1;

[0086] Y1 is calculated by the sign function to obtain y2, i.e.

[0087] Y2 = sign(y1) (1-10)

[0088] Y2 is first-order differentiated again to obtain difference sequence y3;

[0089] Find the position imax of y3 = -2;

[0090] IpX = imax + 1 is the position of the spectral peak in the original spectrum, i.e., the X coordinate. After obtaining ipx, the spectral peak intensity of y0, i.e., the Y coordinate, can be obtained.

[0091] Generally, there are multiple spectral peaks in Raman spectrum, Figure 6 where the horizontal coordinate represents the wave number, and the vertical coordinate represents the spectral intensity. The circle is the "spectral peak" of the Raman spectrum. It is obvious that most of the "spectral peaks" are false peaks, i.e., spectral noise, which needs to be removed. The removal logic is as shown in Figure 4 Figure 7 ​​The figure shows a schematic diagram of the full width at half maximum (FWHM) of the spectral peak. In the figure, f max This represents the maximum value of the spectral peak, FWHM as shown in (1-11):

[0092] FWHM=x2-x1 (1-11)

[0093] For a specific Raman spectrometer, the spectral resolution determines the peak width at half maximum (FWHM). In other words, the FWHM corresponds to the spectral resolution of the instrument. Peaks with an FWHM that is too large or too small are not normal. An FWHM that is too large may be due to the fluorescence background of the sample, while an FWHM that is too small may be due to spectral noise or cosmic rays. Therefore, peaks with abnormal FWHM must be removed. According to industry experience, the FWHM value is within ±25% of the spectral resolution. Therefore, peaks that are 25% lower than the spectral resolution of the instrument and peaks that are 25% higher than the spectral resolution should be removed.

[0094] At the same time, such as Figure 6 As shown, a large amount of noise is mistakenly identified as spectral peaks and should be removed. The removal logic is as follows: Figure 4 As shown, the ABE algorithm is used for baseline removal of the spectrum, and the second-order difference method is used for spectral denoising, which is consistent with the high-pass filter used to calculate the spectral signal-to-noise ratio (SNR).

[0095] Spectral baseline removal uses the ABE algorithm, and the effect is as follows: Figure 8 As shown, spectral denoising uses second-order difference, and the effect is as follows: Figure 9 As shown. It should be noted that, Figure 9 The spectrum after denoising (represented by dashed lines) is higher than the original spectrum. This is to observe the effect. The spectral intensity is increased by 1000 based on the original spectral intensity.

[0096] Therefore, after baseline removal, spectral denoising, and peak acquisition, the position (X coordinate), peak intensity (Y coordinate), and full width at half maximum (FWHM) of the peak can be obtained.

[0097] Based on the measured global signal-to-noise ratio (SNR) of the spectrum, and combined with the performance indicators of the equipment used, a corresponding peak-finding height threshold is assigned, as shown below:

[0098]

[0099] In the formula, SNR represents the global signal-to-noise ratio of the measured Raman spectrum, TH represents the peak height threshold, and the determination of the peak is highly correlated with SNR. The figure shows the spectra obtained from two measurements of ammonium nitrate under different conditions using the same equipment. Figure 10 And as shown in 11, it is obvious Figure 10 The measured SNR of ammonium nitrate spectrum is higher than that of ammonium nitrate. Figure 11 The measured SNR of ammonium nitrate spectrum is high; if given...Figure 10 and Figure 11 The same peak height threshold TH, Figure 11 A significant amount of noise will be mistaken for spectral peaks, so different peak height thresholds must be assigned based on the SNR, as shown in (1-12). Peaks below the threshold will not be retained. Specific values ​​should be obtained through statistical analysis based on the equipment's performance.

[0100] Additionally, you can choose the number of peaks to retain, sort them in descending order of spectral intensity, and retain the first n spectra.

[0101] at last, Figure 10 Based on the complete spectral peak-finding logic, the spectral peaks are obtained as follows: Figure 12 As shown:

[0102] Preferably, in any of the above embodiments, the process of sequentially performing baseline removal processing and spectral denoising processing on the measured Raman signal is as follows:

[0103] The measured Raman signal is subjected to baseline removal processing in sequence to obtain the first signal with the baseline removed. The first signal is then subjected to spectral denoising processing through a high-pass filter to obtain the high-frequency noise signal of the measured spectrum and the standard spectrum.

[0104] Preferably, in any of the above embodiments, the basic data calculation for the high-frequency noise signal specifically involves:

[0105] Calculate the standard deviation of the high-frequency noise signal and the maximum value of the standard spectrum.

[0106] Preferably, in any of the above embodiments, determining all spectral peaks in the standard spectral data specifically involves:

[0107] The standard spectral data is subjected to first-order difference processing to obtain a first processing result. The first processing result is subjected to first-order difference processing to obtain a second processing result. All spectral peaks are determined based on the second processing result.

[0108] Preferably, in any of the above embodiments, the preset condition is:

[0109] Spectral peaks with a half-width exceeding a first threshold and spectral peaks with a height value lower than a second threshold are removed. The first threshold and the second threshold are parameters adjusted based on the judgment result.

[0110] like Figure 2 As shown, a spectral peak determination system includes:

[0111] The first processing module 100 is used to: sequentially perform baseline removal processing and spectral denoising processing on the measured Raman signal to obtain a high-frequency noise signal and a standard spectrum;

[0112] The computing module 200 is configured to perform basic data calculation on the high-frequency noise signal and the standard spectrum, and derive a global signal-to-noise ratio of the measured Raman signal based on the basic data.

[0113] The screening module 300 is configured to judge the global signal-to-noise ratio against a threshold to obtain a judgment result, determine all spectral peaks in the standard spectrum data, screen the spectral peaks according to a preset condition adjusted based on the judgment result, and obtain final spectral peaks.

[0114] In some possible embodiments, the pre-processing of the Raman spectrum can reduce additional calculation work in the peak searching process, and the processing of the signal-to-noise ratio can improve the processing efficiency and the accuracy of the spectral peak determination.

[0115] Preferably, in any of the above embodiments, the process of sequentially performing baseline removal and spectral denoising on the measured Raman signal is as follows:

[0116] The measured Raman signal is sequentially subjected to baseline removal to obtain a first signal with removed baseline, and the first signal is subjected to spectral denoising by a high-pass filter to obtain a high-frequency noise signal of the measured spectrum and a standard spectrum.

[0117] Preferably, in any of the above embodiments, the basic data calculation on the high-frequency noise signal is specifically as follows:

[0118] The standard deviation of the high-frequency noise signal is calculated, and the maximum value of the standard spectrum is calculated.

[0119] Preferably, in any of the above embodiments, the determination of all spectral peaks in the standard spectrum data is specifically as follows:

[0120] The standard spectrum data is subjected to first-order difference processing to obtain a first processing result, the first processing result is subjected to first-order difference processing to obtain a second processing result, and all spectral peaks are determined based on the second processing result.

[0121] Preferably, in any of the above embodiments, the preset condition is as follows:

[0122] Spectral peaks with a half-peak width exceeding a first threshold value and spectral peaks with a height value lower than a second threshold value are removed, and the first threshold value and the second threshold value are parameters adjusted based on the judgment result.

[0123] Another technical solution of the present application to solve the above technical problems is as follows: a storage medium, the storage medium stores instructions, when the computer reads the instructions, the computer executes the method as described in any of the above embodiments.

[0124] In some possible implementation manners, pre-processing of the Raman spectrum can reduce additional calculation work in the peak searching process, and processing of the signal-to-noise ratio can improve processing efficiency and increase the accuracy of spectrum peak determination.

[0125] Another technical solution solving the above technical problem of the present application is as follows: an electronic device comprising the above storage medium and a processor executing instructions in the above storage medium.

[0126] In some possible implementation manners, pre-processing of the Raman spectrum can reduce additional calculation work in the peak searching process, and processing of the signal-to-noise ratio can improve processing efficiency and increase the accuracy of spectrum peak determination.

[0127] It should be understood by the reader that the description in the description of the present application refers to the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like, which means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, the skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples without contradiction.

[0128] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the above-described method embodiments are only illustrative, for example, the division of steps is only a logical function division, and actual implementation can have another division manner, for example, multiple steps can be combined or integrated into another step, or some features can be ignored or not executed.

[0129] If the above method is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or all or part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0130] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of spectral peak determination, characterized by, The application relates to a system and method for determining a spectrum peak of a measured Raman signal. The application comprises the following steps: Step 1, sequentially performing baseline removal and spectrum denoising on the measured Raman signal to obtain a high-frequency noise signal and a standard spectrum; Step 2, performing basic data calculation on the high-frequency noise signal and the standard spectrum, and obtaining a global signal-to-noise ratio of the measured Raman signal based on the basic data; Step 3, judging the global signal-to-noise ratio and a threshold value to obtain a judgment result, determining all spectrum peaks in the standard spectrum data, and screening the spectrum peaks according to preset conditions adjusted based on the judgment result to obtain final spectrum peaks; The measured Raman signal S1 is baseline-removed to obtain a baseline-removed signal S2; calculating the standard deviation σ of S3 N and the maximum value S of S2 _max ; S _max igma N , the global signal-to-noise ratio SNR = S _max / sigma N of the measured Raman spectrum is obtained. S2 is subjected to high-pass filtering and spectrum denoising to retain a high-frequency noise S3; The spectrum peak searching is modularly designed, and the principle for obtaining all spectrum peaks of the spectrum data is to find out the junction points where the intensity monotonicity of the spectrum data changes, that is, the extreme values. According to the global signal-to-noise ratio SNR of the measured spectrum and the performance index of the used equipment, a corresponding peak searching height threshold value is given, and the specific formula is as follows: SNR represents the global signal-to-noise ratio of the measured Raman spectrum, and TH represents the spectrum peak height threshold value. The judgment of the spectrum peak is highly related to the SNR height. The preset conditions adjusted based on the judgment result are as follows:

2. The method of claim 1, wherein, Spectrum peaks with a half-peak width exceeding a first threshold value and spectrum peaks with a height value lower than a second threshold value are removed. The first threshold value and the second threshold value are parameters adjusted according to the judgment result. The process of sequentially performing baseline removal and spectrum denoising on the measured Raman signal is as follows:

3. The method of claim 1, wherein, The measured Raman signal is sequentially subjected to baseline removal to obtain a first signal removed of the baseline, and the first signal is subjected to spectrum denoising through a high-pass filter to obtain a high-frequency noise signal of the measured spectrum and a standard spectrum. The basic data calculation on the high-frequency noise signal is specifically as follows:

4. The method of claim 1, wherein, The standard deviation of the high-frequency noise signal is calculated, and the maximum value of the standard spectrum is calculated. The determination of all spectrum peaks in the standard spectrum data is specifically as follows:

5. A spectral peak determination system employing a spectral peak determination method as claimed in claim 1, characterized by The standard spectrum data is subjected to first-order difference processing to obtain a first processing result, the first processing result is subjected to first-order difference processing to obtain a second processing result, and all spectrum peaks are determined based on the second processing result. The system comprises: A first processing module for sequentially performing baseline removal and spectrum denoising on the measured Raman signal to obtain a high-frequency noise signal and a standard spectrum; A calculation module for performing basic data calculation on the high-frequency noise signal and the standard spectrum, and obtaining a global signal-to-noise ratio of the measured Raman signal based on the basic data; 6. A spectral peak determination system according to claim 5, characterized in that A screening module for judging the global signal-to-noise ratio and a threshold value to obtain a judgment result, determining all spectrum peaks in the standard spectrum data, and screening the spectrum peaks according to preset conditions adjusted based on the judgment result to obtain final spectrum peaks. The process of sequentially performing baseline removal and spectrum denoising on the measured Raman signal is as follows: The measured Raman signal is sequentially subjected to baseline removal to obtain a first signal without baseline, and the first signal is subjected to spectral denoising processing through a high-pass filter to obtain a high-frequency noise signal of the measured spectrum and a standard spectrum.

7. A system for spectral peak determination according to claim 5, wherein, The basis data calculation of the high-frequency noise signal specifically includes: calculating the standard deviation of the high-frequency noise signal and calculating the maximum value of the standard spectrum.

8. A storage medium, characterized by The medium stores instructions, and when the computer reads the instructions, the computer executes the method in any one of claims 1 to 4.

9. An electronic device, comprising: The storage medium of claim 8, a processor executing instructions in the storage medium.

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