Method for correcting saturation spectral line intensity in laser spectrum

Abstract

The invention discloses a correction method for saturation spectral line intensity in a laser spectrum, and relates to the technical field of spectral data analysis, the method comprises the following steps: identifying saturation characteristics in the spectrum, determining a saturation point based on an intensity threshold, and recording the original intensity of the saturation point; determining a target spectrum peak wavelength range containing a saturation point; eliminating saturation points from the wavelength range of the target spectrum peak, and retaining unsaturation points; fitting the unsaturated point through a nonlinear function to obtain the maximum fitting strength; if the maximum fitting strength is lower than the original strength, performing strength correction by adopting a linear extension mode by taking an unsaturated point as a reference, and otherwise, performing strength correction directly based on a fitting model; and outputting the corrected spectral intensity data, and calculating the maximum intensity of the spectral peak and the integral area of the spectral peak. According to the method, the accuracy of saturation judgment and the reliability of a correction result are improved, and a direct intensity data basis and core derivative parameters are provided 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: 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; 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; 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.

[0004] However, the above signal enhancement means in improving the signal detection ability of low concentration component, 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 multiple wavelength points tends to be consistent); for LIF, over strong excitation light will make the fluorescent molecule into excited state saturation, leading to the fluorescence intensity no longer increases with the increase of excitation power, appear "fluorescence saturation"; 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: 1. Saturation judgment 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); 2. There are contradictions in the solutions: if the saturation is avoided by reducing the laser power and weakening the excitation intensity, the signal sensitivity of low concentration component will be directly sacrificed, and the weak target signal will be covered by the 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

[0005] 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 judgment and the reliability of correction results, and provides direct intensity data basis for quantitative analysis.

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows: A correction method for saturated spectral line intensity in laser spectrum, comprising the following steps: S1, identifying the saturation characteristics in the spectrum and determining the saturation point based on the intensity threshold, recording the original intensity I 原始 of the saturation point; S2, determining the target spectral peak wavelength range containing the saturation point; S3, removing the saturation point from the target spectral peak wavelength range and retaining the unsaturated point; S4, fitting the unsaturated point by a nonlinear function to obtain the maximum intensity I 拟合 , center wavelength λ0 and half peak width γ of the fitted target spectral peak; 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.

[0007] Preferably, in step S1, the identification of saturation features in the spectrum is specifically carried out by: extracting the first M maximum intensity values ​​from the spectral intensity data, counting the number of identical values ​​among the first M maximum intensity values, and if the number of identical values ​​exceeds a set number m, then the spectrum is determined to have saturation; the identical value refers to approximately identical values ​​with an intensity difference less than a set value.

[0008] Preferably, M ≥ m ≥ 3.

[0009] Preferably, in step S1, the saturation point is determined by marking the wavelength points in the spectrum whose intensity exceeds the intensity threshold as saturation points, and recording the original intensity I of each saturation point. 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.

[0010] Preferably, 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.

[0011] Preferably, in step S4, the nonlinear function is a Lorentz function, a Vogit function, or a Gaussian function.

[0012] Preferably, 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, thereby avoiding noise interference with the accuracy of linear fitting.

[0013] 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.

[0014] The present invention also provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned method for correcting the intensity of saturated spectral lines in a laser spectrum.

[0015] The present invention also provides a computer program product comprising a computer program / instructions that, when executed by a processor, implement the aforementioned method for correcting the intensity of saturation spectral lines in a laser spectrum.

[0016] The advantages of this invention are: (1) This invention avoids the problem of underestimating the fitting intensity by using a three-layer logic of “accurate identification of saturation features by statistical rules - fitting and linear extension combined with correction - outputting the corrected spectral intensity”, calculates the true intensity of the saturation point, and uses the “corrected spectral intensity” as the core output to provide direct data support for quantitative analysis. In the end, it achieves the four goals of “enhancing trace element signals”, “ensuring the quantitative accuracy of major elements”, “avoiding the error of underestimating intensity” and “optimizing the input of analytical data”.

[0017] (2) The present invention adds a saturation recognition rule of “m or more identical values ​​among the first M maximum intensity values”, which solves the problem of easy misjudgment of traditional single threshold, can more accurately identify saturation features (accidental consistency caused by noise), avoid missed judgment or misjudgment, and improve the accuracy of saturation judgment.

[0018] (3) The present invention supplements the correction logic of “using linear extension when the fitting strength is lower than the original strength”, which avoids the quantitative error of principal elements caused by the underestimation of the fitting value and further improves the analysis accuracy.

[0019] (4) This invention does not require the removal of saturated spectral lines, fully preserves spectral information, and significantly improves the accuracy of quantitative results of major elements and the stability of long-term detection.

[0020] (5) The present invention uses the corrected spectral intensity data as the core output, directly providing the basic intensity data required for quantitative analysis, avoiding the tedious secondary derivation required in subsequent analysis, and improving analysis efficiency.

[0021] (6) Based on the corrected spectral intensity data, the present invention calculates the maximum intensity of the spectral peak and the integral area of ​​the spectral peak as the core derived parameters for quantitative analysis, providing complete data support for the subsequent simultaneous quantitative analysis of major and trace elements.

[0022] (7) This invention can efficiently correct the saturation spectral lines of major elements while ensuring the detection sensitivity of trace elements, taking into account both detection sensitivity and result accuracy, avoiding the loss of spectral information, and significantly improving the stability and reliability of quantitative analysis.

[0023] (8) The present invention can simultaneously achieve trace element signal enhancement, major element saturation spectral line correction, intensity underestimation avoidance and analysis data optimization output under the premise of using signal enhancement methods (such as double pulse excitation, inert atmosphere), without sacrificing any index. Attached Figure Description

[0024] Figure 1 This is a flowchart of a method for correcting the intensity of saturated spectral lines in laser spectra according to the present invention.

[0025] Figure 2 This is a schematic diagram of the raw LIBS spectrum of the lithium ore composition analysis standard material GBW07153, which is an embodiment of the present invention.

[0026] Figure 3 This is a schematic diagram illustrating the extraction of the top 10 maximum intensity values ​​from the raw LIBS spectrum in an embodiment of the present invention. Figure 1 .

[0027] Figure 4 This is a schematic diagram illustrating the extraction of the top 10 maximum intensity values ​​from the raw LIBS spectrum in an embodiment of the present invention. Figure 2 .

[0028] Figure 5 This is a schematic diagram of the spectral peak wavelength range of the first saturation region in an embodiment of the present invention.

[0029] Figure 6 This is a schematic diagram of the spectral peak wavelength range of the second saturation region in an embodiment of the present invention.

[0030] Figure 7 This is a schematic diagram of the spectral peak wavelength range of the third saturation region in an embodiment of the present invention.

[0031] Figure 8 This is a schematic diagram of the spectral peak wavelength range of the fourth saturation region in an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] Depend on Figure 1 As shown, this invention provides a method for correcting the intensity of saturated spectral lines in laser spectra, specifically including the following steps: S1, Saturation feature recognition and intensity threshold setting.

[0034] Read the raw spectral data, sort the spectral intensity values ​​in descending order, and extract the top 10 maximum intensity values; The number of identical values ​​among the top 10 maximum intensity values ​​is counted. If the number of identical values ​​is ≥3, the target spectral line is determined to have saturation. In this invention, considering measurement noise, the identical value is defined as an approximate identical value with an intensity difference ≤ 1% of the set value (maximum value).

[0035] The intensity threshold is determined by combining the dynamic range characteristics of the detector. Wavelength points in the spectrum whose intensity exceeds the intensity threshold are marked as saturation points, and the original intensity of each saturation point (denoted as I) is recorded. 原始 ).

[0036] The intensity threshold is set as follows: the same value among the first M maximum intensity values ​​is used as the intensity threshold, and the minimum value among approximately the same values ​​can be taken as the intensity threshold.

[0037] S2, peak interval determined.

[0038] Using the identified saturation point as the center, and combining the characteristics of spectral line derivative changes (such as the inflection point where the derivative changes from positive to negative), the estimated result of the peak half-width, or by referring to the standard spectral line database of known elements, determine the wavelength range of the target spectral peak that includes the saturation point.

[0039] S3, Data Extraction.

[0040] Within the target spectral peak wavelength range determined above, all marked saturation points are removed, and only unsaturated points whose intensity does not exceed the intensity threshold are retained (extracted). The extracted unsaturated points are then used as input data for subsequent fitting analysis.

[0041] Among them, unsaturated points that are close to the saturation region (i.e., whose intensity is close to the intensity threshold) and have no noise interference are preferentially retained for subsequent linear extension calculations.

[0042] S4, Fitting Modeling.

[0043] Nonlinear fitting of the extracted unsaturated points is performed using a nonlinear function, and key parameters of the target spectral peak are obtained through iterative calculation (such as the least squares method), including the peak center wavelength (λ0), half-width at half maximum (γ), and peak maximum intensity (denoted as I). 拟合 ).

[0044] Nonlinear functions can include the Lorentz function, Vogit function, Gaussian function, etc. This embodiment uses the Lorentz function, whose expression is: I(λ)=I0 / [1+((λ-λ0) / γ) 2 ] Where 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-width at half-maximum of the target spectral peak.

[0045] S5, Strength Correction (combination of fitting and linear extension).

[0046] The peak maximum intensity I obtained by comparison fitting 拟合 Original intensity I at saturation point 原始 : If I 拟合 ≥I 原始 (Allowing a measurement error of up to 5%), the calculated intensity of each saturation point is calculated directly based on the fitting model (Lorentz function model) and by substituting the wavelength values ​​of each saturation point. If I 拟合 <I 原始 (If the fitted strength is lower than the original strength, there is a risk of underestimation), then a linear extension method is used for correction: Select 2-3 consecutive points close to the saturation region among the unsaturated points (denoted as reference points, with wavelengths of λ1, λ2, and λ3, and corresponding intensities of I1, I2, and I3), establish a linear equation of wavelength-intensity based on the least squares method (I=kλ+b, where k is the slope and b is the intercept), substitute the wavelength values ​​of each saturation point, and calculate the estimated intensity of each saturation point.

[0047] Based on the above calculation results, the intensity values ​​of all wavelength points within the target spectral peak wavelength range are supplemented to form complete, corrected spectral intensity data without saturation distortion or intensity underestimation, including the original intensity of unsaturated points and the calculated intensity of saturated points.

[0048] S6, output the result.

[0049] Core output: spectral intensity of all wavelength points within the target spectral peak wavelength range (including the original intensity of unsaturated points and the estimated intensity of saturated points), providing a direct intensity data basis for subsequent quantitative analysis.

[0050] Auxiliary outputs: The maximum intensity of the spectral peak (the maximum intensity value within the wavelength range of the target spectral peak) and the integral area of ​​the spectral peak (the result of integrating the corrected spectral intensity within the wavelength range of the target spectral peak) calculated based on the corrected spectral intensity data serve as the core derived parameters for quantitative analysis.

[0051] The above output data together provide complete data support for the subsequent simultaneous quantitative analysis of major and trace elements.

[0052] Example 1: Spectral preprocessing of GBW07153 lithium ore composition analysis standard reference

[0053] LIBS spectral analysis was performed using standard reference GBW07153 (lithium ore composition analysis standard reference, with fixed components including major elements Si and Li and trace elements Cs and Rb, etc.). The raw LIBS spectral data of GBW07153 were obtained, as follows:Figure 2 As shown.

[0054] The experimental setup and parameter settings are as follows: Laser parameters: A Q-switched pulsed Nd:YAG laser is used, with an output energy of 6mJ and a repetition frequency of 10Hz. After the laser beam is expanded by the beam expansion system, it is focused on the surface of the standard material sample (the sample is pretreated by powder with a particle size ≤200 mesh and a thickness of 3mm) through a quartz focusing lens with a focal length of 75mm, to ensure stable plasma generation and uniform light spot. Acquisition method: A 3-lateral acquisition optical path design is adopted (3 fiber optic probes are evenly distributed 120° laterally along the plasma central axis), with a fiber core diameter of 200μm and a numerical aperture of 0.22, which reduces plasma self-absorption effect and background noise interference, and improves signal acquisition uniformity; Acquisition parameters: Acquisition delay is set to 1.28μs (to avoid strong background noise generated by electron collisions in the early stage of plasma), integration time is 1.05ms (to balance signal strength and noise suppression and ensure complete capture of trace element signals); spectral acquisition range covers 270-830nm.

[0055] The correction process for this embodiment 1 is as follows: S101, Saturation feature recognition and intensity threshold setting.

[0056] like Figure 3 and Figure 4 As shown, where Figure 3 The data displayed is the raw spectral data within the wavelength range of 392-398 nm. Figure 4 The displayed data is the raw spectral data within the wavelength range of 585-615nm. The raw spectral data of standard material GBW07153 was read, and the intensity values ​​were sorted in descending order. The top 10 highest intensity values ​​were extracted as follows: [16338.701,16338.701,16338.701,16338.701,16338.701,16338.701,16338.701,16338.701,16338.701,16338.701,16338.701].

[0057] The number of identical values ​​(considering measurement noise, "identical value" is defined as an approximately identical value with an intensity difference ≤ 1% of the maximum value) appeared 16338.701 10 times, which meets the judgment condition that the number of identical values ​​is ≥ 3, confirming the existence of saturation phenomenon.

[0058] Based on the detector's dynamic range characteristics, an intensity threshold is determined. Wavelength points in the spectrum where the intensity exceeds the threshold are marked as saturation points. Ten saturation points are marked, such as... Figure 3 and Figure 4The 10 saturation points selected in the middle frame have wavelengths of 394.27nm, 394.414nm, 395.857nm, 396.001nm, 396.146nm, 396.29nm, 588.835nm, 588.972nm, 589.519nm, and 610.222nm. The original intensity I at each saturation point... 原始 Both are 16338.701, and the intensity threshold is 16338.701.

[0059] S102, peak range determined.

[0060] Grouping consecutive saturation points together, we determine the target spectral peak wavelength range that includes each group of saturation points.

[0061] Extraction of initial spectral peak ranges: First, for each set of saturation points, using the first saturation point on the left and the first saturation point on the right as references, extend the range by 20 nm to the left and right respectively as the initial analysis region. This ensures that the complete saturation peak and its nearby normal spectral region are included.

[0062] Derivative analysis: In order to find the characteristic boundaries of spectral peaks, the first derivative of the spectral intensity is calculated. The points where the derivative changes can help identify the inflection points of the spectral curve. These inflection points usually correspond to the natural boundaries of the spectral peaks.

[0063] Left Boundary Determination: The left boundary is determined using a right-to-left search strategy: First, the starting position of the saturation peak on the left (the first saturation peak on the left) is identified. Then, the derivative change point is searched from right to left at the starting position on the left. The derivative change point is defined as the position where the derivative sign changes (e.g., from negative to positive or from positive to negative). The left wavelength positions corresponding to all derivative change points (effective points) that meet the conditions are recorded. The point closest to the first saturation peak on the left is selected as the left boundary from these effective points. If no suitable derivative change point is found, the boundary is extended 10nm to the left of the first saturation point on the left by default.

[0064] Right boundary determination: The right boundary was determined using a left-to-right search strategy: First, the starting position of the right side of the saturation peak (the first saturation peak on the right) was identified; then, the derivative change point was searched from left to right at the starting position on the right; similarly, the right wavelength position corresponding to all the derivative change points (effective points) that met the conditions was recorded; from these effective points, the point closest to the first saturation peak on the right was selected as the right boundary; if no suitable derivative change point was found, the boundary was extended 10nm to the right from the first saturation point on the right by default.

[0065] like Figures 5-8As shown, the wavelength ranges of the spectral peaks in the four saturation regions (saturation peak 1-saturation peak 4) were finally determined to be: 393.693-395.28nm, 395.28-398.885nm, 585.552-593.343nm, and 606.283-615.646nm.

[0066] S103, Data Extraction.

[0067] Spectral peak wavelength range management and data filtering: First, the previously determined left and right boundaries are added to the target range list; then, all data points within this range are filtered out, and these data will be used for subsequent fitting analysis. This step ensures that only key data regions related to the saturation peak are processed, improving computational efficiency and accuracy.

[0068] Intelligent separation of saturation and unsaturation points: To accurately fit the peak shape, the data is divided into two categories: saturation points and unsaturation points. All saturation points are excluded, and only unsaturation points are used to construct the fitting model, avoiding interference from saturation values. Simultaneously, the actual observed values ​​(i.e., I0) of all saturation points are recorded. 原始 (This serves as a reference standard for subsequent verification.)

[0069] S104, Fitting Modeling.

[0070] An intelligent adaptive fitting mechanism is adopted to automatically select the most suitable fitting method based on the number of data points: When there are few data points (less than 5) within the wavelength range of the spectral peak, a linear extension method is used directly for fitting. This is because when there are too few data points, complex models may lead to overfitting, while linear models are more robust.

[0071] When there are sufficient data points (5 or more) within the wavelength range of the spectral peak, nonlinear function fitting methods are preferred. The Lorentz function is a commonly used peak shape model in spectral analysis, which can simulate the shape characteristics of real spectral peaks well. Before fitting, reasonable initial parameter estimates should be made based on the data characteristics, including amplitude, center position, full width at half maximum (FWHM), and baseline shift. These estimates help improve the success rate and accuracy of fitting.

[0072] S105, rigorous verification and correction of the fitting results.

[0073] An intelligent verification mechanism is employed to ensure the physical reasonableness of the fitting results. The saturation value (i.e., Is) of the fitted model is checked. 拟合 Is it lower than the actually observed saturation value (i.e., I)? 原始If this situation exists, it indicates that the fitting results may be unreliable, and the system will automatically switch to the linear extension method to recalculate the saturation value (the estimated strength of the saturation point). Finally, regardless of the method used, the system will ensure that all fitted saturation values ​​are not lower than the actual observed saturation values ​​to avoid physically unreasonable results.

[0074] S106, Output the result.

[0075] After completing the fitting calculation of the saturation values, the wavelength position of each saturation peak is precisely located in the original data array, and the original saturation values ​​are replaced with the corrected saturation values. A nearest neighbor search algorithm is used to ensure that the corresponding position is accurately found in the original array, guaranteeing the accuracy of the data replacement.

[0076] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for correction of saturated line intensity in laser spectroscopy, characterized in that, The method comprises the following steps: S1, identify saturation features in the spectrum and determine saturation points based on an intensity threshold, record the original intensity I of the saturation points 原始 ; S2, determining a target spectral peak wavelength range containing the saturation point; S3, eliminating the saturation point from the target spectral peak wavelength range and retaining the unsaturated point; S4, fitting the unsaturated point by a nonlinear function to obtain a fitted maximum intensity I of the target spectral peak 拟合 , center wavelength λ0, and half-peak width γ; S5, intensity correction: If I 拟合 ≥ I 原始 then, based on a non-linear function, calculate the estimated intensity of the saturation point; 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, forming corrected spectral intensity data based on the calculation result, the corrected spectral intensity data containing the original intensity of the unsaturated point and the calculated intensity of the saturation point in the target spectral peak wavelength range.

2. The method for correction of saturated line intensity in laser spectroscopy according to claim 1, characterized in that, In step S1, the saturation feature in the spectrum is identified in the following manner: the first M maximum intensity values in the spectral intensity data are extracted, the number of identical values in the first M maximum intensity values is counted, 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.

3. The method for correction of saturated line intensity in laser spectroscopy according to claim 2, characterized in that, M≥m≥3.

4. The method for correction of saturated line intensity in laser spectroscopy according to claim 2, wherein, In step S1, the determination of the saturation points is as follows: the wavelength points in the spectrum whose intensities exceed an intensity threshold value are marked as saturation points, and the original intensities I of the saturation points are recorded 原始 ; The intensity threshold is selected in the following manner: The identical value in the first M maximum intensity values is used as the intensity threshold.

5. The method for correction of saturated line intensity in laser spectroscopy according to claim 1, wherein, In step S2, the determination of the target spectral peak wavelength range 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.

6. The method for correction of saturated line intensity in laser spectroscopy according to claim 1, wherein, In step S4, the nonlinear function is a Lorentz function, a Vogit function, or a Gaussian function.

7. The method for correction of saturated line intensity in laser spectroscopy according to claim 1, wherein, In step S5, the linear equation of wavelength and intensity is established by the least square method, and the selected N unsaturated points near the saturation region are required to be continuously distributed and have an intensity difference from the intensity threshold within a set range, so as to avoid noise interference on the linear fitting accuracy.

8. The method for correction of saturated line intensity in laser spectroscopy according to claim 1, wherein, 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, comprising: The method comprises a processor, a memory, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the method for correcting the intensity of a saturated spectral line in laser spectroscopy.

10. A computer program product, characterised in that, The method comprises a computer program / instruction, which is executed by a processor to implement the method for correcting the intensity of a saturated spectral line in laser spectroscopy.

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