Method for quickly and adaptively matching spectrum background by utilizing spectrum peak fitting

Abstract

The invention belongs to the related technical field of laser probe element analysis, and provides a method for quickly and adaptively matching a spectrum background by utilizing spectrum peak fitting, which comprises the following steps: acquiring an LIBS spectrum to obtain plasma spectrum data; selecting the spectral peak intensity and the spectral peak width of a plurality of spectral peaks in the wave band of the to-be-matched spectral peak to obtain a fitting equation; utilizing the equation to obtain the width of a spectrum peak to be matched, and setting the single-side scanning times, the background length and the step length; background noise is scanned towards the left side and the right side according to the set background length and step length; in all background noise values obtained by scanning, selecting a background spectrum segment with the minimum noise value as the background of the spectrum peak, taking the value of the background spectrum segment as the noise value of the spectrum peak, and taking the average value of the intensity of the spectrum segment as the background value; and calculating the signal-to-noise ratio and the signal-to-background ratio of each spectrum peak in combination with the spectrum peak intensity. According to the method, the spectrum peak width is automatically estimated through spectrum peak fitting, so that rapid self-adaptive identification and matching of the spectrum peak background are realized, and the analysis efficiency of the laser probe technology is improved.

Description

Technical Field

[0001] The invention belongs to the field related to laser probe spectral analysis, and more specifically, relates to a method for fast and adaptive matching of spectral background by using spectral peak fitting. Background Art

[0002] Laser probe technology is laser-induced breakdown spectroscopy (LIBS) or LIBS technology for short. Currently, this technology has been widely used in industrial production, deep sea, deep space exploration and other fields.

[0003] The basic principle of LIBS technology is that the content of a specific element in the sample to be tested is usually proportional to the intensity of its laser-induced plasma emission spectrum. Therefore, when using LIBS technology for qualitative or quantitative analysis, it is generally necessary to first extract the spectral intensity of the element to be tested, or the spectral intensity of the analytical lines of multiple elements, and also to conduct a quality assessment of the analytical lines to ensure their characterization performance. The quality of the analytical line can generally be characterized by indicators such as spectral intensity, signal-to-noise ratio, and signal-to-background ratio. Usually, in a known spectrum, the spectral intensity of a specific peak is fixed, but its signal-to-noise ratio and signal-to-background ratio depend on the selection of the background band, and almost every analyst will have a certain gap in the length, strength, range, etc., which makes the selection and evaluation of the analytical line produce a lot of uncertainty, which is not conducive to the standardization and generalization of the analysis model.

[0004] At present, whether it is qualitative analysis or quantitative analysis, when selecting the analysis line, the evaluation calculation is usually carried out by manually selecting the background, or by roughly specifying a specific distance and number of pixels next to the spectral peak as the spectral peak background. Although the former can ensure accuracy, the efficiency is not satisfactory; although the latter can achieve automatic selection, the accuracy is difficult to guarantee. Summary of the invention

[0005] In view of the shortcomings of the existing laser probe spectral analysis technology, the present invention provides a method for quickly and adaptively matching the spectral background by using spectral peak fitting, and automatically estimates the spectral peak width by using spectral peak fitting, thereby achieving fast and adaptive recognition and matching of the laser probe spectral background.

[0006] The present invention provides a method for quickly and adaptively matching spectral background by using spectral peak fitting, comprising: Step S1, collecting LIBS spectra to obtain plasma original spectra; Step S2, selecting multiple spectrum peak positions in the spectrum peak band to be matched, obtaining the spectrum peak intensity value and the spectrum peak width value of each spectrum peak position, fitting the spectrum peak intensity values ​​and the spectrum peak width values ​​of the multiple spectrum peak positions to obtain a fitting equation; Step S3, obtaining the peak intensity value of the to-be-matched peak, obtaining the peak width value of the to-be-matched peak according to the fitting equation, and setting the number of single-side scans, background length and step length according to the peak width value of the to-be-matched peak; Step S4, determining the left and right scanning starting points according to the wavelength index value and the spectrum peak width of the spectrum peak to be matched, and scanning the background noise to the left and right sides of the original spectrum respectively from the scanning starting point with the set background length and step length; Step S5, among all the background noises obtained by scanning, the background spectrum segment with the smallest noise value is selected as the background of the spectrum peak to be matched, the minimum noise value is taken as the noise value of the spectrum peak to be matched, and the average value of the spectral intensity of the background spectrum segment is taken as the background value of the spectrum peak to be matched; Step S6, calculating the signal-to-noise ratio and signal-to-background ratio of the spectral peak to be matched according to the background value of the spectral peak to be matched.

[0007] Based on the above technical solution, the present invention can also make the following improvements.

[0008] Optionally, the step S2, selecting multiple spectrum peak positions within the spectrum peak band to be matched, and obtaining the spectrum peak intensity and spectrum peak width of each spectrum peak position, includes: According to the spectral band where the spectral peak to be matched is located, multiple spectral peak positions with relatively complete and symmetrical spectral peak shapes in the spectral band are selected, and the spectral intensity value of each spectral peak position is extracted, as well as the number of pixels from the central wavelength position of the spectral peak to the lowest point on the leftmost side of the spectral peak and the number of pixels from the central wavelength position of the spectral peak to the lowest point on the rightmost side of the spectral peak are extracted, and recorded as the left half-peak width and the right half-peak width. The smaller value of the left half-peak width and the right half-peak width is taken as the width value of the highest spectral peak.

[0009] Optionally, according to the spectral band where the spectral peak to be matched is located, multiple spectral peak positions with relatively complete and symmetrical spectral peak shapes in the spectral band are selected, including: According to the spectral band where the spectral peak to be matched is located, the maximum spectral peak position, the middle spectral peak position and the minimum spectral peak position with relatively complete and symmetrical spectral peak shapes in the spectral band are selected.

[0010] Optionally, according to the spectral band where the spectral peak to be matched is located, multiple spectral peak positions with relatively complete and symmetrical spectral peak shapes in the spectral band are selected, including: According to the spectral band where the spectral peak to be matched is located, the maximum spectral peak position, the middle spectral peak position and the minimum spectral peak position with relatively complete and symmetrical spectral peak shapes in the spectral band are selected.

[0011] Optionally, the fitting equation is a linear equation, a quadratic or higher polynomial equation, an exponential function equation, a logarithmic function equation or a composite function equation.

[0012] Optionally, the step S3, obtaining the peak intensity value of the to-be-matched peak, obtaining the peak width value of the to-be-matched peak according to the fitting equation, and setting the number of single-side scans, background length and step length according to the peak width value of the to-be-matched peak, comprises: Step S31, substituting the peak intensity value of the to-be-matched peak i into the fitting equation to obtain the peak width value W of the to-be-matched peak i i , peak width value W i It is the starting basis for the adaptive search background; Step S32, according to the peak width value W i , set the single-side scan times K, background length L and step length S of the peak i to be matched, where the K value should be greater than or equal to the peak width value W i The sum of the maximum value of and the background length L.

[0013] Optionally, the step S4, determining the left and right scanning starting points according to the wavelength index value and the spectrum peak width of the spectrum peak to be matched, and scanning the background noise to the left and right sides of the original spectrum respectively from the scanning starting point with the set background length and step length, includes: The wavelength index value of the spectrum peak to be matched minus the spectrum peak width value Wi is taken as the actual adaptive starting point on the left side of the spectrum peak, and the wavelength index value of the spectrum peak to be matched plus the spectrum peak width value Wi is taken as the actual adaptive starting point on the right side of the spectrum peak. With the background length as L and the step length as S, the background noise is scanned (K - Wi) times to the left and right respectively to obtain Nscan = 2*(K - Wi) background noise values.

[0014] Optionally, the step S5, among all the background noises obtained by scanning, selects the background spectrum segment with the smallest noise value as the background of the spectrum peak to be matched, takes the smallest noise value as the noise value of the spectrum peak to be matched, and takes the average value of the spectral intensity of the background spectrum segment as the background value of the spectrum peak to be matched, including: In the obtained N scan Among the background noise values, select the background spectrum segment S with the smallest noise value. min is the background of the peak to be matched, with its noise value N min is the noise value of the peak to be matched, and the average value of the intensity value of the background spectrum is B min is the background value.

[0015] Optionally, the step S6, calculating the signal-to-noise ratio and signal-to-background ratio of the spectral peak to be matched according to the background value of the spectral peak to be matched, comprises: According to the intensity value I of the peak to be matched m , calculate the signal-to-noise ratio and signal-to-background ratio of the peak to be matched, where the signal-to-noise ratio SNR = I m / S min , signal-to-background ratio SBR = I m / Bmin .

[0016] The present invention provides a method for quickly and adaptively matching spectral background using spectral peak fitting, which has the following advantages and effects: (1) The method proposed in the present invention can batch identify and match the most suitable spectral background near the spectral peaks in the LIBS spectrum. The background length, search range, search efficiency, etc. are directly controlled by relevant parameters, and the adjustment is convenient and fast.

[0017] (2) Through the automatic and rapid identification and matching of the background, the LIBS spectral peak quality evaluation parameters such as noise, background, signal-to-noise ratio and signal-to-background ratio can be quickly calculated.

[0018] (3) The method proposed in the present invention can accurately and quantitatively identify, match and evaluate the spectral background of a specific spectral peak, greatly reducing the manual intervention process, thus ensuring the reliability and uniqueness of the analysis model during LIBS qualitative and quantitative analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of a method for fast adaptive matching of spectral background using spectral peak fitting provided by the present invention; Figure 2 The average spectrum band and main peak position of the igneous rock sample to be identified; Figure 3 Fitting points and obtained fitting equations of spectral peak intensity and width. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention can be arbitrarily combined with each other to form a feasible technical solution. This combination is not subject to the constraints of the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0021] Figure 1 A flow chart of a method for fast adaptive matching of spectral background using spectral peak fitting provided by the present invention is as follows: Figure 1 As shown, the method includes: Step S1, collecting LIBS spectra to obtain plasma original spectra.

[0022] It can be understood that the LIBS spectrum is first collected to obtain plasma spectrum data, which is recorded as N mⅹn , n=2, where the first column is the wavelength column, the second column is the spectral intensity value corresponding to each wavelength, and m represents the number of wavelengths.

[0023] Step S2, selecting multiple spectrum peak positions in the spectrum peak band to be matched, obtaining the spectrum peak intensity value and spectrum peak width value of each spectrum peak position, fitting the spectrum peak intensity values ​​and spectrum peak width values ​​of the multiple spectrum peak positions to obtain a fitting equation.

[0024] Step S21, in the spectral band where the spectrum peak to be matched is located, select the highest peak with a relatively complete and symmetrical spectrum peak shape, extract its spectral intensity, and the number of pixels from the center wavelength position of the highest spectrum peak to the lowest point position of the spectrum peak on the left (right) side, and record it as the spectrum peak width, and take the smaller one of the width values ​​on the left and right sides as the final width value. Then extract the intensity value and width value of the intermediate spectrum peak and the smaller spectrum peak in this way.

[0025] Specifically, in step S21, the maximum value, the middle value and the smaller value (P max , P mid and P min The three points of the spectrum are denoted as A, B, and C, and their peak widths can be obtained from the original spectrum and are denoted as W. max , W mid , W min , then the coordinates of the three points are (P max , W max )、(P mid , W mid )、(P min , W min ).

[0026] Fitting is performed based on the coordinates of three or more points to obtain a fitting equation, which represents the functional relationship between the intensity value and the width value of the spectrum peak.

[0027] Specifically, in step S21, the independent variable selected in the spectrum segment for fitting can be the intensity of the spectrum peak, or the area, intensity ratio, half-width, and contour shape of the spectrum peak; the extracted spectrum peak intensity can be the intensity value and width of three points of maximum value, middle value and minimum value, or other spectrum peaks that conform to the law of intensity and width variation, which can be three points or more than three points, and the same applies to other independent variables.

[0028] Step S22, establishing a fitting equation based on the variation trends of the intensity values ​​and width values ​​of the maximum, middle and smaller spectral peaks, and the obtained equation is recorded as F(X).

[0029] Specifically, in step S22, the equation used to fit the trend of changes in spectral peak intensity and width can be a linear equation, or a polynomial of quadratic or higher, an exponential function, a logarithmic function, or a composite function; it can be one fitting equation within a spectral segment, or it can be a segmented fitting of multiple fitting equations within a spectral segment according to the background conditions of the spectral segment.

[0030] Step S3, obtaining the peak intensity value of the to-be-matched peak, obtaining the peak width value of the to-be-matched peak according to the fitting equation, and setting the number of single-side scans, background length and step length according to the peak width value of the to-be-matched peak.

[0031] Wherein, step S3 specifically includes: Step S31, using the obtained fitting equation F(X), the intensity value of the to-be-matched spectral peak is substituted into the fitting equation to calculate the width value of the to-be-matched spectral peak, where the width value of the i-th to-be-matched spectral peak is recorded as W i , the width value is the starting basis for the adaptive search background.

[0032] Step S32, according to the obtained spectrum peak width W i , set the number of single-side scans K, background length L and step length S for each peak, where the K value should be greater than or equal to the peak width W i The sum of the maximum value of and the background length L.

[0033] Step S4, determining the left and right scanning starting points according to the wavelength index value and the spectrum peak width of the spectrum peak to be matched, and scanning the background noise to the left and right sides of the original spectrum respectively from the scanning starting point with the set background length and step length.

[0034] Specifically, the wavelength index value of the peak to be matched is subtracted (added) by the width W i The actual adaptive starting point of the left (right) peak, with the background length as L and the step length as S, scans to the left (right) (K - W i ) times the background noise, we get N scan = 2*(K - W i ) background noise value.

[0035] Step S5, among all the background noises obtained by scanning, select the background spectrum segment with the smallest noise value as the background of the spectrum peak to be matched, take the smallest noise value as the noise value of the spectrum peak to be matched, and take the average value of the spectral intensity of the background spectrum segment as the background value of the spectrum peak to be matched.

[0036] Specifically, in the obtained N scanAmong the background noise values, select the background spectrum segment S with the smallest noise value. min is the background of the peak to be matched, with its noise value N min is the noise value of the peak to be matched, and the average value of the intensity value of the background spectrum is B min is the background value.

[0037] Step S6, calculating the signal-to-noise ratio and signal-to-background ratio of the spectral peak to be matched according to the background value of the spectral peak to be matched.

[0038] Specifically, according to the intensity value I of the peak to be matched m As well as its noise value and background paper, calculate the signal-to-noise ratio and signal-to-background ratio of the spectrum peak to be matched, where the signal-to-noise ratio SNR = I m / S min , signal-to-background ratio SBR = I m / B min .

[0039] The method for fast adaptive matching of spectral background by using spectral peak fitting provided by the present invention is described below with a specific embodiment, which mainly includes the following steps: Step 1: Collect plasma spectrum. In this example, a spectrum from the average spectrum of 12 igneous rock samples is taken as an example to perform fast adaptive matching of the spectrum peak background. The selected spectral range is 334.53 - 363.68 nm, and the spectral data matrix N mⅹn = N 679ⅹ2 The peaks to be background matched are the 42 peaks in this spectrum segment, covering most of the more significant peaks in this spectrum segment, such as Figure 2 shown.

[0040] Step 2: Establish the functional relationship between the peak intensity and the peak width. Figure 2 In the spectral range shown, three peaks of maximum value, middle value and minimum value are selected and recorded as points A, B and C. The coordinates of the three points are (3904.8, 8), (2468.1, 4) and (1453.9, 3) respectively. According to the distribution trend of the three points, fuzzy fitting is performed by linear fitting (it does not require high fitting accuracy, as long as it conforms to the general trend), and the fitting equation F(X) = 0.002X – 0.45 is obtained, as shown in Figure 3 shown.

[0041] Step 3: Calculate the background scanning parameters. First, according to the fitting equation obtained in step 2, input the intensity values ​​of all the peaks to be matched I = [3904.8, 1672.3,…, 1358.9], calculate the peak width W = [7, 2, 5,…, 2] corresponding to each peak to be matched, and use the width as the starting basis for the adaptive background search. At the same time, set the number of single-side scans K for each peak temp = 70, the background length is 7 pixels, and the step length is 1 pixel.

[0042] Step 4: Scan all spectral backgrounds on both sides of the central wavelength of the spectrum peak. Table 1 shows the background matching results and spectrum peak quality evaluation table obtained by the method of the present invention.

[0043] Table 1 Background matching results and spectrum peak quality evaluation table obtained by the method of the present invention

[0044] Table 1 or Figure 2 Taking the first spectrum peak λ = 334.88 nm shown as an example, the index value of the spectrum peak wavelength is 9 (that is, it is located at the 9th pixel in the entire spectrum), and its spectrum peak width W1 = 7. Therefore, the actual adaptive starting position of the right scan should be 16, the background length is 7, and the step length is 1. First, scan the background noise to the right K1 = (70 – 7) = 63 times, and move one step to the right each time with the background length, and calculate the noise value of the background spectrum segment. Similarly, scan the left side of the center wavelength of the spectrum peak. Since the left side is close to the spectrum segment boundary, it can only be scanned once according to the above configuration. Therefore, the left and right sides of the spectrum peak are scanned 64 times in total, and 64 background noises are obtained. (Note 1: When the left and right sides are close to the spectrum segment boundary, the background spectrum segment selection is based on the actual length to the boundary. If it is less than one background length, it is calculated as an approximate length; Note 2: If it is not close to the spectrum segment boundary, the left and right sides should be scanned N times in total. scan =2*(70 - 7) = 126 times).

[0045] Step 5: Select the band corresponding to the minimum noise value as the target background band. Among all the background noise values ​​scanned in step 4, select the one with the smallest value as the actual background noise corresponding to the spectrum peak. Taking the spectrum peak of λ = 334.88nm as an example, its minimum noise value N min = 21.3, the background band S corresponding to this noise value min = 336.55 -336.81 nm, and the average intensity of the background band is taken as the background value, then the background value B min = 1450.7.

[0046] Step 6: Calculate the peak evaluation index. Combined with the peak intensity I m, calculate the signal-to-noise ratio and signal-to-background ratio of each spectral peak, where the signal-to-noise ratio SNR = I m / S min , signal-to-background ratio SBR = I m / B min In this embodiment, the intensity value I of the spectral peak λ = 334.88 nm m = 3904.8, and the noise value and background value obtained in step 5 are 21.3 and 1450.7 respectively. Therefore, according to the signal-to-noise ratio and signal-to-background ratio formula, the signal-to-noise ratio and signal-to-background ratio can be obtained as 183.4 and 2.7 respectively. The calculation results of the spectrum peak evaluation index are shown in Table 2. Table 2 takes the first three spectrum peaks in Table 1 as an example, and uses the traditional manual method to match the background and spectrum peak quality evaluation table.

[0047] Table 2 Background and peak quality evaluation table matched by traditional manual methods

[0048] Taking the first three peaks in Table 1 as an example, the peak background matching was performed using the traditional manual background matching method. It can be seen from Tables 1 and 2 that the matching results of the first two peaks are significantly different from the matching results of the method provided by the present invention, mainly because the background spectrum segments selected by them are not the same spectrum segment. The signal-to-noise ratio and signal-to-background ratio obtained by the manual method are significantly weaker than the results matched by the method of the present invention. This is because, when the manual method is used, the relatively flat background spectrum segment around the peak is generally selected based on the visual effect of the spectrum, but the visual effect of the spectrum is not necessarily the optimal effect within a specific range. In addition, when manual matching is used, the matching results of each person may be different, so there is still a problem of uncertainty. Furthermore, for the third peak (336.11 nm) in Table 2, since there is a relatively obvious flat background spectrum segment in the vicinity of the peak, the visual effect is more obvious, so the matching results of the method of the present invention and the manual method are consistent. However, there is still a huge gap in matching efficiency between the two methods. When the background matching of a specific spectral peak is realized by manual method, the matching time of a single spectral peak is about several minutes (slightly reduced when several spectral peaks use the same background, but the average time is also in the order of minutes), while the batch adaptive matching by the method of the present invention only takes a few seconds. Taking the 42 spectral peaks in this embodiment as an example, the execution time of the automated program is only about 6-7 seconds, and the matching model and program are universal. Therefore, the method of the present invention for fast adaptive matching of spectral background by using spectral peak fitting and the traditional method of artificial matching of background have obvious advantages in matching accuracy and matching efficiency.

[0049] The embodiment of the present invention provides a method for fast adaptive matching of spectral background using spectral peak fitting, LIBS spectrum acquisition, plasma spectral data; select the spectral peak intensity and spectral peak width of multiple spectral peaks in the band where the spectral peak to be matched is located, and obtain a fitting equation; use the equation to obtain the width of the spectral peak to be matched, and set the number of single-sided scans, background length and step length at the same time; scan the background noise to the left and right sides with the set background length and step length; among all the background noise values ​​obtained by scanning, select the background spectrum segment with the smallest noise value as the background of the spectral peak, use its value as the noise value of the spectral peak, and use the average value of the spectral segment intensity as the background value; combine the spectral peak intensity, calculate the signal-to-noise ratio and signal-to-background ratio of each spectral peak. The present invention automatically estimates the spectral peak width through spectral peak fitting to achieve fast adaptive recognition and matching of the spectral peak background, and improve the analysis efficiency of laser probe technology.

[0050] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0051] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0052] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for fast adaptive matching of spectral background using spectral peak fitting, characterized in that: include: Step S1, collecting LIBS spectra to obtain plasma original spectra; Step S2, selecting multiple spectrum peak positions in the spectrum peak band to be matched, obtaining the spectrum peak intensity value and the spectrum peak width value of each spectrum peak position, fitting the spectrum peak intensity values ​​and the spectrum peak width values ​​of the multiple spectrum peak positions to obtain a fitting equation; Step S3, obtaining the peak intensity value of the to-be-matched peak, obtaining the peak width value of the to-be-matched peak according to the fitting equation, and setting the number of single-side scans, background length and step length according to the peak width value of the to-be-matched peak; Step S4, determining the left and right scanning starting points according to the wavelength index value and the spectrum peak width of the spectrum peak to be matched, and scanning the background noise to the left and right sides of the original spectrum respectively from the scanning starting point with the set background length and step length; Step S5, among all the background noises obtained by scanning, the background spectrum segment with the smallest noise value is selected as the background of the spectrum peak to be matched, the minimum noise value is taken as the noise value of the spectrum peak to be matched, and the average value of the spectral intensity of the background spectrum segment is taken as the background value of the spectrum peak to be matched; Step S6, calculating the signal-to-noise ratio and signal-to-background ratio of the spectral peak to be matched according to the background value of the spectral peak to be matched.

2. The method according to claim 1, characterized in that The step S2, selecting a plurality of spectrum peak positions within the spectrum peak band to be matched, and obtaining the spectrum peak intensity and spectrum peak width of each spectrum peak position, includes: According to the spectral band where the spectral peak to be matched is located, multiple spectral peak positions with relatively complete and symmetrical spectral peak shapes in the spectral band are selected, and the spectral intensity value of each spectral peak position is extracted, as well as the number of pixels from the central wavelength position of the spectral peak to the lowest point on the leftmost side of the spectral peak and the number of pixels from the central wavelength position of the spectral peak to the lowest point on the rightmost side of the spectral peak are extracted, and recorded as the left half-peak width and the right half-peak width. The smaller value of the left half-peak width and the right half-peak width is taken as the width value of the highest spectral peak.

3. The method according to claim 2, characterized in that According to the spectral band where the spectral peak to be matched is located, multiple spectral peak positions with relatively complete and symmetrical spectral peak shapes in the spectral band are selected, including: According to the spectral band where the spectral peak to be matched is located, the maximum spectral peak position, the middle spectral peak position and the minimum spectral peak position with relatively complete and symmetrical spectral peak shapes in the spectral band are selected.

4. The method according to claim 1, characterized in that: The fitting equation is a linear equation, a polynomial equation of quadratic or higher, an exponential function equation, a logarithmic function equation or a composite function equation.

5. The method according to claim 1, characterized in that The step S3, obtaining the peak intensity value of the to-be-matched peak, obtaining the peak width value of the to-be-matched peak according to the fitting equation, and setting the number of single-side scans, background length and step length according to the peak width value of the to-be-matched peak, includes: Step S31, substituting the peak intensity value of the to-be-matched peak i into the fitting equation to obtain the peak width value W of the to-be-matched peak i i , peak width W i It is the starting basis for the adaptive search background; Step S32, according to the peak width value W i , set the single-side scan times K, background length L and step length S of the peak i to be matched, where the K value should be greater than or equal to the peak width value W i and the background length L, and the step size is the number of pixels moved each time when scanning to the left or right.

6. The method according to claim 5, characterized in that The step S4, determining the left and right scanning starting points according to the wavelength index value and the spectrum peak width of the spectrum peak to be matched, and scanning the background noise to the left and right sides of the original spectrum respectively from the scanning starting point with the set background length and step length, includes: The wavelength index value of the spectrum peak to be matched minus the spectrum peak width value Wi is taken as the actual adaptive starting point on the left side of the spectrum peak, and the wavelength index value of the spectrum peak to be matched plus the spectrum peak width value Wi is taken as the actual adaptive starting point on the right side of the spectrum peak. With the background length as L and the step length as S, the background noise is scanned (K - Wi) times to the left and right respectively to obtain Nscan = 2*(K - Wi) background noise values.

7. The method according to claim 6, characterized in that The step S5, among all the background noises obtained by scanning, selects the background spectrum segment with the smallest noise value as the background of the spectrum peak to be matched, takes the smallest noise value as the noise value of the spectrum peak to be matched, and takes the average value of the spectrum intensity of the background spectrum segment as the background value of the spectrum peak to be matched, including: In the obtained N scan Among the background noise values, select the background spectrum segment S with the smallest noise value. min is the background of the peak to be matched, with its noise value N min is the noise value of the peak to be matched, and the average value of the intensity value of the background spectrum is B min is the background value.

8. The method according to claim 7, characterized in that The step S6, calculating the signal-to-noise ratio and signal-to-background ratio of the spectral peak to be matched according to the background value of the spectral peak to be matched, comprises: According to the intensity value I of the peak to be matched m , calculate the signal-to-noise ratio and signal-to-background ratio of the peak to be matched, where the signal-to-noise ratio SNR = I m / S min , signal-to-background ratio SBR = I m / B min .

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