A method for correction of saturated line intensity in laser spectroscopy

Abstract

The application discloses a correction method for saturated spectral line intensity in laser spectroscopy, and relates to the technical field of spectral data analysis, wherein saturated characteristics in a spectrum are identified, a saturated point is determined based on an intensity threshold, and the original intensity of the saturated point is recorded; the wavelength range of a target spectral peak containing the saturated point is determined; the saturated point is removed from the wavelength range of the target spectral peak, and the unsaturated point is reserved; the unsaturated point is fitted through a nonlinear function, and the maximum intensity of the fitting is obtained; if the maximum intensity of the fitting is lower than the original intensity, the intensity is corrected in a linear extension mode based on the unsaturated point, otherwise, the intensity is directly corrected based on the fitting model; the corrected spectral intensity data are output, and the maximum intensity of the spectral peak and the integral area of the spectral peak are calculated. The application improves the accuracy of saturated determination and the reliability of correction results, and provides direct intensity data basis and core derivative parameters for quantitative analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spectral data analysis, and particularly relates to a correction method for saturated spectral line intensity in laser spectroscopy. BACKGROUND

[0002] As a kind of high-precision spectral analysis technology based on laser and matter interaction (absorption, emission, scattering, etc.), laser spectroscopy technology covers multiple branches such as laser-induced breakdown spectroscopy (LIBS), laser-induced fluorescence spectroscopy (LIF), laser Raman spectroscopy (LRS), and laser absorption spectroscopy (LAS). With the core advantages of high resolution, high sensitivity, fast response, and multi-component synchronous detection, laser spectroscopy technology has been widely applied in multiple key fields: in the biomedical field, LIF can be used to realize in-situ imaging and quantification of active molecules (such as ATP and active oxygen) in cells; in the field of food safety, LRS is used to quickly identify the molecular structure of pesticide residues and illegal additives in food; in the semiconductor industry, LAS is used to accurately detect the content of trace impurities (such as O and C) in the chip manufacturing process; in geological exploration and environmental monitoring, LIBS combined with LRS can realize on-site rapid screening of ore composition, soil heavy metals, and atmospheric pollutants; in the field of new energy, laser spectroscopy is used for element distribution and crystal structure analysis of lithium battery materials and photovoltaic materials.

[0003] In the actual detection scene of laser spectroscopy, for the detection needs of low-concentration components (such as trace markers in biological samples and trace pollutants in the environment), multi-dimensional means are needed to enhance the weak signal to break through the detection limit and improve the signal-to-noise ratio. Common signal enhancement strategies include:

[0004] 1. Optimizing laser source parameters: using narrow linewidth and high power stability lasers (such as Q-switched pulsed lasers and continuous wave single frequency lasers), or improving the interaction efficiency of laser and matter through laser focusing technology (such as confocal optical system) to strengthen the excitation intensity of target signal;

[0005] 2. Upgrading signal detection system: selecting high-sensitivity detection devices (such as photomultiplier tubes PMT, avalanche photodiodes APD, and high-resolution CCD / CMOS arrays), and matching signal amplification modules (such as lock-in amplifiers) to suppress the masking of weak signals by background noise;

[0006] 3. Improving optical collection and processing: using high numerical aperture (NA) optical lenses and multi-channel fiber coupling systems to maximize the collection of target spectral signals; in some scenarios, surface enhancement technology (such as surface-enhanced Raman SERS and surface-enhanced fluorescence SEF) is combined to amplify the local signal intensity through nanostructured substrates.

[0007] However, the above signal enhancement means in improving the low concentration component signal detection ability, easy to cause the saturation effect of laser spectrum, this problem is not limited to a single spectrum type, but the common challenge in the field of laser spectrum: for LIBS and LAS, high intensity excitation easy to lead to the emission / absorption spectrum line intensity of major component exceeds the dynamic range of detector, form "platform area" (the intensity of multi-wavelength point tends to be consistent); for LIF, the over-strong excitation light can make the fluorescent molecule enter the excited state saturation, so that the fluorescence intensity no longer increases with the increase of excitation power, and "fluorescence saturation" appears; for LRS, high-power laser can enhance the Raman scattering signal, but may cause local overheating of the sample, molecular vibration energy level transition saturation, and even lead to Raman peak distortion and signal nonlinear distortion. The existing technology has obvious limitations in dealing with laser spectrum saturation:

[0008] 1. Saturation determination is single: it mainly depends on the single standard of "detector dynamic range threshold" or "excitation power threshold", and does not consider the difference of saturation mechanism of different laser spectrum types (such as power dependence of fluorescence saturation and sample specificity of Raman saturation), which is easy to cause misjudgment or omission due to noise fluctuation and sample matrix interference (such as light scattering of complex matrix);

[0009] 2. There are contradictions in the solutions: if the laser power is reduced and the excitation intensity is weakened to avoid saturation, the signal sensitivity of low concentration component will be directly sacrificed, and the weak target signal will be covered by background noise; if the saturated spectrum segment is directly removed, the key spectral information of major component and high concentration target (such as characteristic peak of major element in LIBS and molecular structure peak of strong scattering component in LRS) will be lost. SUMMARY

[0010] In order to overcome the defects in the prior art, the present application provides a correction method for saturated spectral line intensity in laser spectrum, which improves the accuracy of saturation determination and the reliability of correction results, and provides direct intensity data basis for quantitative analysis.

[0011] In order to achieve the above purpose, the present application adopts the following technical scheme, comprising:

[0012] A correction method for saturated spectral line intensity in laser spectrum, comprising the following steps:

[0013] S1, identifying the saturation characteristics in the spectrum and determining the saturation point based on the intensity threshold, and recording the original intensity I 原始 of the saturation point;

[0014] S2, determining the target spectral peak wavelength range containing the saturation point;

[0015] S3, removing the saturation point from the target spectral peak wavelength range and retaining the unsaturated point;

[0016] S4, fitting the unsaturated points by a nonlinear function to obtain a fitted maximum intensity I of the target spectral peak 拟合 , central wavelength λ0 and half-peak width γ.

[0017] S5, intensity correction:

[0018] If I 拟合 ≥ I 原始 , then calculate the estimated intensity of the saturated point based on the nonlinear function;

[0019] If I 拟合 < I 原始 , then select N unsaturated points close to the saturated region to establish a linear equation of wavelength and intensity, and substitute the wavelength of the saturated point into the linear equation to calculate the estimated intensity of the saturated point;

[0020] S6, form the corrected spectral intensity data based on the estimation result, and the corrected spectral intensity data contains the original intensity of the unsaturated points and the estimated intensity of the saturated point within the wavelength range of the target spectral peak.

[0021] Preferably, in step S1, the saturated characteristics in the spectrum are identified in the following specific manner: extract the first M maximum intensity values in the spectral intensity data, count the number of identical values among the first M maximum intensity values, and if the number of identical values exceeds a set number m, it is determined that the spectrum has saturation phenomenon; the identical value refers to an approximately identical value with an intensity difference less than a set value.

[0022] Preferably, M≥m≥3.

[0023] Preferably, in step S1, the saturated points are determined in the following manner: mark the wavelength points in the spectrum with intensity exceeding an intensity threshold value as saturated points, and record the original intensity I 原始 of each saturated point.

[0024] The intensity threshold value is selected in the following manner:

[0025] Take the identical value among the first M maximum intensity values as the intensity threshold value.

[0026] Preferably, in step S2, the determination of the wavelength range of the target spectral peak is based on at least one of the following: the change characteristics of the spectral line derivative, the estimated result of the spectral peak half-peak width, and the standard spectral line database of known elements.

[0027] Preferably, in step S4, the nonlinear function adopts a Lorentz function, a Vogit function or a Gaussian function.

[0028] Preferably, in step S5, the linear equation of wavelength and intensity is established by least square method, and N unsaturated points near the saturation region are selected to ensure continuous distribution and the intensity difference from the intensity threshold is not more than a set range, so as to avoid noise interference on the linear fitting accuracy.

[0029] Preferably, the maximum intensity of the spectral peak and the integral area of the spectral peak are calculated based on the corrected spectral intensity data.

[0030] The application also provides an electronic device, which comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor implements the method for correcting the intensity of a saturated spectral line in laser spectroscopy when executing the computer program.

[0031] The application also provides a computer program product, which comprises computer programs / instructions, and the computer programs / instructions implement the method for correcting the intensity of a saturated spectral line in laser spectroscopy when executed by a processor.

[0032] The application has the following advantages:

[0033] (1) The application avoids the underestimation of the fitting intensity, calculates the true intensity of the saturated point, takes the corrected spectral intensity as the core output, provides direct data support for quantitative analysis, and finally achieves the four goals of enhancing the signal of trace elements, ensuring the quantitative accuracy of major elements, avoiding the underestimation error of intensity, and optimizing the input of analysis data.

[0034] (2) The application adds the saturation identification rule that there are m or more identical values in the first M maximum intensity values, solves the problem of easy misjudgment of the traditional single threshold, more accurately identifies the saturation characteristics (not accidental consistency caused by noise), avoids missed or misjudgment, and improves the accuracy of saturation determination.

[0035] (3) The application supplements the correction logic that the linear extension is used when the fitting intensity is lower than the original intensity, avoids the quantitative error of major elements caused by the underestimation of the fitting value, and further improves the analysis accuracy.

[0036] (4) The application does not need to remove the saturated spectral line, completely retains the spectral information, and significantly improves the accuracy of the quantitative results of major elements and the stability of long-term detection.

[0037] (5) The application takes the corrected spectral intensity data as the core output, directly provides the basic intensity data required for quantitative analysis, avoids the tedious secondary derivation in subsequent analysis, and improves the analysis efficiency.

[0038] (6) The present application also calculates the maximum intensity of the spectral peak and the integral area of the spectral peak based on the corrected spectral intensity data, as the core derived parameters for quantitative analysis, to provide complete data support for subsequent simultaneous quantitative analysis of major elements and trace elements.

[0039] (7) The present application can correct the saturated spectral line of the major element efficiently under the premise of ensuring the sensitivity of trace element detection, taking into account the detection sensitivity and result accuracy, avoiding loss of spectral information, and significantly improving the stability and reliability of quantitative analysis.

[0040] (8) The present application can realize simultaneous signal enhancement of trace elements, correction of saturated spectral line of major elements, avoidance of intensity underestimation, and optimized output of analysis data under the premise of using signal enhancement means (such as double-pulse excitation and inert atmosphere), without sacrificing any index. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 A flowchart of a method for correcting the intensity of saturated spectral line in laser spectroscopy according to the present application.

[0042] Figure 2 A schematic diagram of the LIBS original spectrum of lithium ore composition analysis standard material GBW07153 according to the embodiment of the present application.

[0043] Figure 3 A schematic diagram of the extraction of the first 10 maximum intensity values of the LIBS original spectrum according to the embodiment of the present application Figure 1 .

[0044] Figure 4 A schematic diagram of the extraction of the first 10 maximum intensity values of the LIBS original spectrum according to the embodiment of the present application Figure 2 .

[0045] Figure 5 A schematic diagram of the spectral peak wavelength range of the first saturated region according to the embodiment of the present application.

[0046] Figure 6 A schematic diagram of the spectral peak wavelength range of the second saturated region according to the embodiment of the present application.

[0047] Figure 7 A schematic diagram of the spectral peak wavelength range of the third saturated region according to the embodiment of the present application.

[0048] Figure 8 A schematic diagram of the spectral peak wavelength range of the fourth saturated region according to the embodiment of the present application. DETAILED DESCRIPTION

[0049] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of the present application.

[0050] As shown in FIG. 1, Figure 1 The present application provides a correction method for saturated spectral line intensity in laser spectroscopy, specifically comprising the following steps:

[0051] S1, saturated feature recognition and intensity threshold setting.

[0052] Read the original spectral data, sort the spectral intensity values in descending order, and extract the top 10 maximum intensity values;

[0053] Count the number of identical values in the top 10 maximum intensity values. If the number of identical values is greater than or equal to 3, it is determined that the target spectral line has a saturation phenomenon. In the present application, considering the measurement noise, the identical value is defined as an approximately identical value with an intensity difference less than a set value (1% of the maximum value).

[0054] Determine the intensity threshold value in combination with the dynamic range characteristics of the detector, mark the wavelength points in the spectrum with intensity exceeding the intensity threshold value as saturated points, and record the original intensity (denoted as I 原始 ).

[0055] The intensity threshold value is set as follows: the identical value in the top M maximum intensity values is taken as the intensity threshold value, and the minimum value of the approximately identical value can be taken as the intensity threshold value.

[0056] S2, peak interval determination.

[0057] Determine the wavelength range of the target spectral peak containing the saturated point in combination with the derivative change characteristics of the spectral line (such as the inflection point where the derivative changes from positive to negative), the half-peak width estimation result of the spectral peak, or the reference to the standard spectral line database of known elements.

[0058] S3, data extraction.

[0059] From the above determined target spectral peak wavelength range, remove all marked saturated points, only keep (extract) unsaturated points with intensity not exceeding the intensity threshold value, and take the extracted unsaturated points as the input data for subsequent fitting analysis.

[0060] Among them, the unsaturated points close to the saturated region (i.e. the intensity close to the intensity threshold value) and without noise interference are preferentially kept for subsequent linear extension calculation.

[0061] S4, fitting modeling.

[0062] The extracted unsaturated points are nonlinearly fitted by using a nonlinear function, and the key parameters of the target spectral peak are solved by iterative calculation (such as the least square method), including the peak center wavelength (λ0), the half-peak width (γ) and the peak maximum intensity (denoted as I 拟合 ).

[0063] The nonlinear function can be a Lorentz function, a Vogit function, a Gaussian function, etc. In this embodiment, the Lorentz function is used, and the expression is as follows:

[0064] I(λ)=I0 / [1+((λ-λ0) / γ) 2 ]

[0065] Wherein, I(λ) is the spectral line intensity at wavelength λ, I0 is the spectral line intensity corresponding to the center wavelength, λ0 is the center wavelength of the target spectral peak, and γ is the half-peak width of the target spectral peak.

[0066] S5, intensity correction (combination of fitting and linear extension).

[0067] The peak maximum intensity I 拟合 obtained by fitting is compared with the original intensity I 原始 of the saturated point:

[0068] If I 拟合 ≥ I 原始 (within 5% measurement error allowed), the calculated intensity of each saturated point is directly calculated based on the fitting model (Lorentz function model) by substituting the wavelength value of each saturated point;

[0069] If I 拟合 < I 原始 (the fitted intensity is lower than the original intensity, there is a risk of underestimation), the linear extension method is used for correction: select 2-3 consecutive points (denoted as reference points, their wavelengths are λ1, λ2, λ3, and their intensities are I1, I2, I3) near the saturated area in the unsaturated points, establish a linear equation of wavelength-intensity (I=kλ+b, where k is the slope and b is the intercept) based on the least square method, and substitute the wavelength value of each saturated point to calculate the calculated intensity of each saturated point.

[0070] Based on the above calculation results, the intensity values of all wavelength points in the wavelength range of the target spectral peak are completed to form the corrected spectral intensity data which is complete, without saturation distortion and without intensity underestimation, containing the original intensity of the unsaturated point and the calculated intensity of the saturated point.

[0071] S6, result output.

[0072] Core output: the spectral intensity corresponding to all wavelength points in the wavelength range of the target spectral peak (containing the original intensity of the unsaturated point and the calculated intensity of the saturated point), which provides a direct intensity data basis for subsequent quantitative analysis.

[0073] Auxiliary output: the maximum intensity of the spectral peak (the maximum intensity value in the target spectral peak wavelength range) and the integral area of the spectral peak (the result of integrating the corrected spectral intensity in the target spectral peak wavelength range) calculated based on the corrected spectral intensity data, as the core derived parameters for quantitative analysis.

[0074] The above output data collectively provide complete data support for subsequent simultaneous quantitative analysis of major elements and trace elements.

[0075] Example 1: Spectral pretreatment of GBW07153 lithium ore composition analysis standard material

[0076] The standard material GBW07153 (lithium ore composition analysis standard material, with major elements Si, Li and trace elements Cs, Rb, etc.) was used for LIBS spectral detection, and the LIBS raw spectral data of GBW07153 were obtained, as shown in Figure 2

[0077] The experimental device and parameter settings are as follows:

[0078] Laser parameters: Q-switched pulsed Nd:YAG laser with output energy of 6 mJ and repetition frequency of 10 Hz; the laser beam is expanded by a beam expansion system and focused on the surface of the standard material sample (the sample is pretreated as a 200-mesh powder tablet with a thickness of 3 mm) through a quartz focusing lens with a focal length of 75 mm, ensuring stable plasma generation and uniform spot;

[0079] Collection method: 3-side collection optical path design (3 optical fiber probes are evenly distributed along the plasma central axis at 120°), fiber core diameter of 200 μm, numerical aperture of 0.22, to reduce plasma self-absorption effect and background noise interference and improve signal collection uniformity;

[0080] Collection parameters: collection delay is set to 1.28 μs (to avoid strong background noise generated by initial electron collision of plasma), integration time is 1.05 ms (to balance signal intensity and noise suppression and ensure complete capture of trace element signals); spectral collection range covers 270-830 nm.

[0081] The correction process of this example 1 is as follows:

[0082] S101, saturated feature recognition and intensity threshold setting.

[0083] As shown in Figure 3 and Figure 4 , wherein Figure 3 shows the raw spectral data in the wavelength range of 392-398 nm, Figure 4 ​The original spectral data in the wavelength range of 585-615 nm is shown, the original spectral data of the standard substance GBW07153 is read, the intensity values are sorted in descending order, and the top 10 maximum intensity values are extracted as:

[0084] [16338.701, 16338.701, 16338.701, 16338.701, 16338.701, 16338.701, 16338.701, 16338.701, 16338.701, 16338.701].

[0085] Statistical same value (considering measurement noise, define "same value" as approximately same value with intensity difference ≤1% of maximum value): 16338.701 appears 10 times, which meets the determination condition of the number of same values ≥3, and it is confirmed that there is a saturation phenomenon.

[0086] Determine the intensity threshold value in combination with the dynamic range characteristics of the detector, mark the wavelength points in the spectrum whose intensity exceeds the threshold value as saturation points, mark 10 saturation points, such as Figure 3 and Figure 4 The 10 saturation points are selected in the frame, and the wavelengths are 394.27 nm, 394.414 nm, 395.857 nm, 396.001 nm, 396.146 nm, 396.29 nm, 588.835 nm, 588.972 nm, 589.519 nm, and 610.222 nm. The original intensity I 原始 of each saturation point is 16338.701, and the intensity threshold value is 16338.701.

[0087] S102, peak interval determination.

[0088] Take the continuous saturation points as a group, and determine the target spectral peak wavelength range containing the group of saturation points for each group of saturation points.

[0089] Extraction of initial spectral peak range: first, for each group of saturation points, take the left first saturation point and the right first saturation point as the benchmark, and expand the range of 20 nm to the left and right as the initial analysis area. This can ensure that the complete saturation peak and its surrounding normal spectral region are included.

[0090] Derivative analysis: in order to find the characteristic boundary of the spectral peak, the first derivative of the spectral intensity is calculated, and the change point of the derivative can help identify the inflection point of the spectral curve. These inflection points usually correspond to the natural boundary of the spectral peak.

[0091] Left boundary determination: The determination of the left boundary adopts a search strategy from right to left: first, determine the left starting position of the saturated peak (the first left saturated peak), and then find the derivative change point from right to left at the left starting position. The derivative change point is defined as the position where the derivative sign changes (such as from negative to positive or from positive to negative), and all derivative change points (valid points) that meet the conditions are recorded. The point closest to the left first saturated peak is selected as the left boundary from these valid points. If no suitable derivative change point is found, the left first saturated point is extended by 10 nm to the left by default.

[0092] Right boundary determination: The determination of the right boundary adopts a search strategy from left to right: first, determine the right starting position of the saturated peak (the first right saturated peak), and then find the derivative change point from left to right at the right starting position. Similarly, record the right wavelength positions of all derivative change points (valid points) that meet the conditions. The point closest to the right first saturated peak is selected as the right boundary from these valid points. If no suitable derivative change point is found, the right first saturated point is extended by 10 nm to the right by default.

[0093] As shown in Figures 5-8 , the final determination of the spectral peak wavelength range of the four saturated regions (saturated peak 1-saturated peak 4) is: 393.693-395.28 nm, 395.28-398.885 nm, 585.552-593.343 nm, and 606.283-615.646 nm.

[0094] S103, data extraction.

[0095] Spectrum peak wavelength range management and data filtering: First, add the previously determined left and right boundaries to the target range list; then, filter out all data points in the range, which will be used for subsequent fitting analysis. This step ensures that only the key data region related to the saturated peak is processed, improving the calculation efficiency and accuracy.

[0096] Intelligent separation of saturated points and non-saturated points: In order to accurately fit the spectral peak shape, the data is divided into two categories: saturated points and non-saturated points. All saturated points are excluded, and only non-saturated points are used to construct the fitting model to avoid interference caused by saturated values to the model. At the same time, the actual observation values of all saturated points (i.e. I 原始 ) are recorded as reference standards for subsequent verification.

[0097] S104, fitting modeling.

[0098] Adopting an intelligent adaptive fitting mechanism, the most suitable fitting method is automatically selected according to the number of data points:

[0099] When the data points in the spectral peak wavelength range are less than 5, the linear extension method is directly used for fitting. This is because too few data points may cause overfitting with complex models, while the linear model is more robust.

[0100] When the data points in the spectral peak wavelength range are sufficient (5 or more), the nonlinear function fitting method is preferred. The Lorentz function is a commonly used peak shape model in spectral analysis, which can better simulate the shape characteristics of real spectral peaks. Before fitting, reasonable initial parameter estimation is made based on data characteristics, including amplitude, center position, half-height width and baseline offset, etc. These estimates help improve the success rate and accuracy of fitting.

[0101] S105, strict verification and correction of fitting results.

[0102] An intelligent verification mechanism is used to ensure the physical reasonableness of the fitting results. Check if the saturation value (i.e. I 拟合 ) fitted by the fitting model is lower than the actual observed saturation value (i.e. I 原始 ). If this is the case, the fitting result may be unreliable, and the system will automatically switch to the linear extension method to recalculate the saturation value (estimated intensity of the saturation point). Finally, regardless of which method is used, the system will ensure that all fitted saturation values are not lower than the actual observed saturation value, avoiding physically unreasonable results.

[0103] S106, result output.

[0104] After completing the fitting calculation of the saturation value, the wavelength position of each saturated peak in the original data array is accurately located, and the corrected saturation value is used to replace the original saturation value. The nearest neighbor search algorithm is used to ensure accurate positioning in the original array, ensuring the accuracy of data replacement.

[0105] The above is only a preferred embodiment of the present invention, and does not limit the present invention. Any modification, equivalent replacement and improvement within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for correcting the intensity of saturated spectral lines in laser spectra, characterized in that, Includes the following steps: S1, identify saturation features in the spectrum and determine the saturation point based on the intensity threshold, and record the original intensity I of the saturation point. 原始 ; S2, determine the target spectral peak wavelength range that includes the saturation point; S3, remove saturated points from the target spectral peak wavelength range and retain unsaturated points; S4, the unsaturated point is fitted using a nonlinear function to obtain the maximum intensity I of the fitted target spectral peak. 拟合 , center wavelength λ0 and full width at half maximum γ; S5, Intensity Correction: If I 拟合 ≥I 原始 Then, based on the nonlinear function, the inferred intensity of the saturation point is calculated; If I 拟合 <I 原始 Then, select N unsaturated points close to the saturation region to establish a linear equation between wavelength and intensity, substitute the wavelength of the saturation point into the linear equation, and calculate the estimated intensity of the saturation point. S6. Based on the calculation results, the corrected spectral intensity data is generated. The corrected spectral intensity data includes the original intensity of the unsaturated point and the calculated intensity of the saturated point within the wavelength range of the target spectral peak.

2. The method for correcting the intensity of saturated spectral lines in laser spectra according to claim 1, characterized in that, In step S1, the identification of saturation features in the spectrum is specifically carried out as follows: extract the first M maximum intensity values ​​from the spectral intensity data, count the number of identical values ​​among the first M maximum intensity values, and if the number of identical values ​​exceeds a set number m, it is determined that the spectrum is saturated; the identical value refers to approximately identical values ​​with an intensity difference less than a set value.

3. The method for correcting the intensity of saturated spectral lines in laser spectra according to claim 2, characterized in that, M≥m≥3.

4. The method for correcting the intensity of saturated spectral lines in a laser spectrum according to claim 2, characterized in that, In step S1, the saturation point is determined as follows: the wavelength points in the spectrum whose intensity exceeds the intensity threshold are marked as saturation points, and the original intensity I of each saturation point is recorded. 原始 ; The intensity threshold is selected as follows: The intensity threshold is determined by taking the common value among the first M maximum intensity values.

5. The method for correcting the intensity of saturated spectral lines in a laser spectrum according to claim 1, characterized in that, In step S2, the determination of the target spectral peak wavelength range is based on at least one of the following: the variation characteristics of the spectral line derivative, the estimation results of the spectral peak half-width, and the standard spectral line database of known elements.

6. The method for correcting the intensity of saturated spectral lines in a laser spectrum according to claim 1, characterized in that, In step S4, the nonlinear function is a Lorentz function, a Vogit function, or a Gaussian function.

7. The method for correcting the intensity of saturated spectral lines in laser spectra according to claim 1, characterized in that, In step S5, the linear equation between wavelength and intensity is established by the least squares method. The selected N unsaturated points near the saturation region are required to be continuously distributed, and the difference between the intensity and the intensity threshold is not more than a set range, so as to avoid noise interference with the accuracy of linear fitting.

8. The method for correcting the intensity of saturated spectral lines in laser spectra according to claim 1, characterized in that, Based on the corrected spectral intensity data, the maximum intensity of the spectral peak and the integral area of ​​the spectral peak are calculated.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a method for correcting the intensity of saturated spectral lines in a laser spectrum as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes a computer program / instruction that, when executed by a processor, implements a method for correcting the intensity of saturated spectral lines in a laser spectrum as described in any one of claims 1 to 7.

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