A quantitative analysis method for elemental laser-induced breakdown spectroscopy on the inner wall surface of a magnetic confinement fusion device

Abstract

This invention discloses a method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy, belonging to the field of laser spectral analysis technology. This method is based on laser-induced breakdown spectral data of impurity layers on the wall material surface. According to the relationship between the intensity of spectral lines of each element in the characteristic spectral data, a pre-classification model of the deposited impurity film composition is used to predict the matrix properties of the impurity layer to be tested. Based on the matrix properties, a spectral standard sample similar to the matrix of the sample to be tested is selected for single-sample corrected spectral calculation. After correcting for characteristic spectral line errors, quantitative analysis is performed. This method enables large-scale, high-resolution quantitative measurement of the content of corrosion-redeposited impurities, wall treatment coatings, retained fuel, and other impurity elements in the wall material of the magnetic confinement device. This invention provides rich information on the compositional structure of the deposited impurity layer on the wall surface, which can provide important basis for fuel injection, wall treatment maintenance, and high-parameter plasma control in the operation of magnetic confinement fusion devices.

Description

Technical Field

[0001] This invention belongs to the field of laser spectral analysis technology, specifically relating to a method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy. Background Technology

[0002] Magnetic confinement fusion is currently the most promising method for achieving controlled thermonuclear fusion. Research both domestically and internationally is focused on the long-pulse, high-parameter operation of magnetic confinement fusion devices. During high-parameter operation, the interaction between plasma and wall materials affects the lifespan of critical materials such as the divertor target plate and the first wall. Simultaneously, the generated high-quality ordinal metallic impurities (e.g., tungsten) can contaminate the core plasma, triggering plasma fracture and affecting the stable operation of the device. Developing quantitative online analysis techniques for wall surface composition is crucial for a deeper understanding of the plasma-wall material interaction mechanism and for developing effective control methods. Laser-induced breakdown spectroscopy (LIBS) offers advantages such as in-situ, online, real-time, and simultaneous full-element analysis, making it a highly promising in-situ diagnostic technique for magnetic confinement fusion device wall materials. It primarily generates laser-induced plasma by ablating the sample surface with high-energy laser pulses, and calculates the content of each element based on the plasma emission spectrum. Traditional external standard methods are limited by the difficulty of online measurement of batch standard samples, hindering precise quantitative analysis. Traditional calibration-free laser-induced breakdown spectroscopy (CF-LIBS) acquires the spectra of laser-ablated plasma in a state of local thermal equilibrium. Based on the intensity of the characteristic lines of the laser-ablated plasma and plasma parameters (plasma electron density and temperature), a Boltzmann slope diagram is constructed. The relative proportions of each element are calculated by fitting the intercept of the fitted line based on the distribution of characteristic spectral data points for each species, thus determining the elemental content. However, in practice, it has been found that the traditional CF-LIBS method suffers from poor quantitative analysis accuracy due to errors caused by variations in the response efficiency of the plasma emission spectroscopy optical collection system at different wavelengths, spectral parameters, and self-absorption. This makes it unsuitable for precise quantitative analysis of elements in wall surface deposits under vacuum, far-field, and other conditions. One-point calibration LIBS (OPC-LIBS) is a method that, based on CF-LIBS, corrects the calculation errors of CF-LIBS by using a single spectral standard with known composition that is consistent with or similar to the matrix of the sample being tested. The principle is to compare the true values ​​of each element content in the reference spectral standard with the predicted values ​​of each content in CF-LIBS. By calculating the difference between the predicted and true values, a correction coefficient for the characteristic spectrum of each element is obtained. Under the premise of consistent matrix, this correction coefficient can comprehensively correct for errors caused by optical collection system, spectral parameters, and self-absorption. However, in practical applications of OPC-LIBS, the selected spectral standard and the matrix of the sample to be tested are not necessarily the same or similar, which may not be the case.For example, when the elemental content of the sample varies widely, it is impossible to find a single spectral standard applicable to all samples. Experimental results show that the quantitative accuracy of OPC-LIBS varies with the content of each element; the greater the difference from the spectral standard, the greater the error in its quantitative analysis. Based on the wall material, structure, and operating parameters of the magnetic confinement fusion device, the composition of the impurity layer deposited on the wall surface during operation mainly comes from the elements in the wall treatment coating (boron, lithium, etc.), the impurity elements deposited in the wall material (tungsten, molybdenum, carbon, iron, etc.), and the retained fuel (deuterium, tritium) and reaction products (helium). During LIBS quantitative analysis, the differences in the impurity composition of the wall material deposition layer make external standard method, CF-LIBS, and OPC-LIBS unable to meet the requirements for accurate quantitative analysis of multiple elements over a wide range. CF-LIBS has poor accuracy. Both the external standard method and OPC-LIBS require the consistency of the matrix (physicochemical properties of the material) of the analyzed impurity layer to be applicable. However, the interaction between plasma and wall materials during magnetic confinement fusion is extremely complex. The composition of migrating impurities deposited under different discharge types, parameters, and spatial locations is highly variable, although the types of elements they contain are relatively fixed. For example, on the Experimental Superconducting Tokamak (EAST) nuclear fusion device, there are significant differences in impurities deposited at different locations in the divertor region. At the impact point, the tungsten divertor target plate is severely ablated, resulting in a higher tungsten content in the nearby deposits. In the dome region, transport impurities are more severely deposited, with higher contents of wall-treated elements such as boron and lithium. Deposits with tungsten and boron as the main components show significant differences in ablation quality, plasma size, plasma temperature, and density when ablated using the same nanosecond laser pulse. This matrix effect significantly impacts the quantitative analysis of laser-induced plasma emission. Traditional external standard methods, CF-LIBS, and OPC-LIBS cannot meet the requirements for high-precision quantitative measurement under conditions of large variations in elemental content. Therefore, there is an urgent need to further develop high-precision LIBS quantitative analysis methods. Summary of the Invention

[0003] The purpose of this invention is to propose an in-situ, online, rapid, and high-precision quantitative analysis method for the composition of impurity layers deposited on the surface of reactor inner wall materials in magnetic confinement fusion devices and future magnetic confinement nuclear fusion power plants during operation.

[0004] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0005] A method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy, comprising:

[0006] Step 1: Optimize the experimental parameters of laser-induced breakdown spectroscopy under vacuum and strong magnetic field conditions.

[0007] To address the high vacuum and strong magnetic field environment inside the vacuum chamber of the magnetically confined polymerization device, the optimal parameters for the LIBS experiment were adjusted, including: adjusting the energy density of the incident laser so that the laser ablates the impurity film, and the resulting plasma is chemically ablated, effectively exciting all elements in the impurity film, and ensuring that the luminescent elements in the laser ablation plasma are consistent with the elements in the impurity film; and adjusting the gate delay and gate width of the spectrometer so that the laser ablation plasma is in a state of local thermodynamic equilibrium.

[0008] Based on the optimization of laser energy density and spectrometer acquisition time, the types of characteristic spectra of laser ablation plasma radiation are consistent with the types of elements in the impurity film, the intensity of characteristic spectral lines is related to the element content of the film, and the intensity of a series of characteristic spectra generated by the transition process between different energy levels of each element satisfies the Boltzmann distribution law.

[0009] Step 2: Establish a pre-classification model for the composition of deposited impurity films.

[0010] During the operation of a magnetic confinement fusion device, the deposited impurity films on the wall material surface are primarily composed of the erosion, transport, and redeposition of the wall material (tungsten, molybdenum, carbon, iron, etc.), as well as the coating elements (boron, lithium, etc.) used in the wall treatment process and their erosion, transport, and redeposition. The deposited impurity films on the wall material surface vary significantly depending on the location of the magnetic confinement device and the operating conditions of different fusion plasmas, but are mainly combinations of these two types of elements. Collecting real impurity deposited film samples or preparing simulated samples in the laboratory reveals that the differences in the matrix lead to significant variations in laser absorption, heat conduction, plasma generation, and the plasma-laser interaction process during the interaction between the pulsed laser and the impurity film, affecting subsequent quantitative classification of characteristic spectra. Therefore, classifying the impurity film composition quantifies this difference in matrix effect. After classification, the differences in matrix effect within each subset can be ignored, and they are considered to be approximately of the same matrix.

[0011] The pre-classification model for the composition of deposited impurity films classifies the matrix properties of samples based on LIBS characteristic spectral line analysis of the impurity films, with each classification being a subset of the same matrix as a co-deposited film.

[0012] Step 3: Establish a database of spectral correction factors for characteristic spectral lines of each element.

[0013] Standard film samples were selected from each co-deposited film substrate subset, and the LIBS characteristic spectra of each standard film sample were collected. Based on the LIBS characteristic spectra, a database of characteristic spectral correction factors was obtained through a single standard sample correction model.

[0014] Step 4: Online Measurement of the LIBS Magnetic Confinement Fusion Device

[0015] Based on the optimized parameter conditions, the LIBS characteristic spectra of the impurity deposition layer are acquired using an online LIBS measurement system; the matrix properties of the co-deposited film are determined using the pre-classification model of the deposited impurity film components; the corresponding characteristic spectral correction coefficients are read from the characteristic spectral correction factor database according to the matrix properties; and CF-LIBS calculation is performed after multiplying the characteristic spectral lines in the online LIBS spectrum by the correction coefficients to obtain the quantitative analysis results of LIBS.

[0016] Step 5: Quantitative analysis of the three-dimensional spatial distribution of impurity layer composition on the wall material surface

[0017] The LIBS characteristic spectra of different points on the wall material are collected by scanning in three-dimensional space using an online LIBS measurement system; the matrix properties are determined according to the pre-classification model of the deposited impurity film composition, and the corresponding characteristic spectrum correction coefficients are selected from the characteristic spectrum correction factor database based on the matrix properties; then CF-LIBS calculation is performed to obtain the content values ​​of the elements contained at each point, and the spatial distribution relationship of each element is reconstructed.

[0018] Furthermore, in step 1, a nanosecond laser pulse with a wavelength of 1064 nm is used to irradiate the surface of the impurity film with an energy density higher than 5 J / cm². 2 .

[0019] Furthermore, in step 1, the spectrometer uses a gate delay time of 100-200 ns and a gate width time of 100-200 ns.

[0020] Furthermore, in step 2, the pre-classification model for the composition of the deposited impurity film is established as follows:

[0021] Step 2.1: Collect or prepare several impurity film samples;

[0022] Step 2.2: Measure the content of each element in all impurity film samples using detection methods such as SIMS and ICP-MS;

[0023] Step 2.3: Based on the measured element content in the impurity film samples, classify the impurity film samples as follows: 1) Samples with only one element content greater than 60% are classified as "monometallic" samples, and further subdivided into tungsten-based, molybdenum-based, boron-based, lithium-based, etc., according to the major element; 2) Samples with two elements content greater than 40% are classified as "binary" samples, and further subdivided into tungsten-molybdenum-based, tungsten-boron-based, molybdenum-lithium-based, etc., according to the two major elements; 3) Samples with three elements content greater than 30% are classified as "ternary" samples, and further subdivided into tungsten-molybdenum-boron-based, tungsten-iron-lithium-based, etc., according to the three major elements; Each type of impurity film sample is treated as a subset of the same substrate for co-deposited films.

[0024] Step 2.4: Collect LIBS spectra of all impurity film samples;

[0025] Step 2.5: Based on the intensity of the characteristic spectral lines of each element in the LIBS spectrum, establish the relationship between the content ratio of elements and the intensity ratio of the corresponding characteristic spectral lines in the LIBS spectrum; specifically, in an impurity film sample composed of n elements, the intensity of the characteristic spectral lines of the major element is compared with the intensity of the characteristic spectral lines of the other elements, and the ratio should be within an interval M. n Inside, M n It is an n-dimensional array, and this array serves as a dividing line indicating whether each value is an upper or lower limit. In subsequent analysis of unknown thin film samples, based on characteristic spectral data, the characteristic spectral line ratios among these deposited impurity elements are calculated to determine the major element attribution and confirm the classification of the impurity film.

[0026] Furthermore, in step 2, the method for establishing the pre-classification model of the deposited impurity film composition also includes multivariate statistical methods and artificial intelligence algorithms; wherein, the multivariate statistical methods can perform classification modeling based on models such as PCA and PLS, and by inputting spectral data, establish the mapping relationship between classification features based on the intensity information of characteristic spectra, and give the judgment value of the matrix properties of the impurity film.

[0027] Furthermore, in step 3, the specific process for establishing the database of spectral correction factors for characteristic spectral lines of each element is as follows:

[0028] Step 3.1: Select one standard film sample from each substrate subset of co-deposited films. Under the vacuum, strong magnetic field, and optical path conditions of a 1:1 simulated fusion device, set the parameters of the laser and spectrometer of the LIBS online measurement system to be consistent with the optimized parameters set in Step 1, so that the LIBS analysis process meets the conditions of chemical dose ablation and local thermal equilibrium. Then measure the LIBS characteristic spectrum of each standard film sample.

[0029] Step 3.2: The plasma temperature generated by laser ablation of standard thin film samples under LIBS optimized experimental conditions is measured using the Thomson scattering method. The reciprocal of the plasma temperature is used as a reference value for the slope fitting of the subsequent Boltzmann distribution diagram, correcting the deviation of plasma temperature calculation by the traditional Boltzmann and Saha-Boltzmann methods and improving the accuracy of composition calculation.

[0030] Step 3.3: Perform CF-LIBS quantitative analysis on the characteristic spectra of each collected standard thin film sample, and compare the calculation results with the elemental content values ​​of the corresponding standard thin film samples to determine the deviation between the calculated and theoretical values. Calculate the intercept of the linear distribution of the characteristic spectral data points of each element in the Boltzmann slope diagram using the actual content, and perform regression correction on the Boltzmann slope diagram with reference to the calculated actual content values ​​to obtain the correction coefficients for all elemental characteristic spectra of the subset of substrates co-deposited thin films. The correction coefficients for all elemental characteristic spectra of each subset of substrates co-deposited thin films together form a characteristic spectral correction factor database. These correction coefficients are the corresponding spectral correction coefficients for LIBS analysis of each subset of substrates co-deposited thin films, and these coefficients have comprehensively corrected for optical instrument parameters, spectroscopic parameters, and the self-absorption coefficients of characteristic spectra in each matrix.

[0031] Furthermore, in step 3, the selection criterion for standard thin film samples is that the content values ​​of each component in the corresponding substrate subset of the co-deposited thin film are in the middle of the corresponding range.

[0032] The beneficial effects of this invention are as follows: The method described in this invention enables remote online quantitative measurement of the composition of co-deposited impurity films (tens of nanometers or more thick) under extreme measurement conditions such as high vacuum and strong magnetic fields, and simultaneously quantitatively analyzes the content of elements such as tungsten, molybdenum, iron, carbon, boron, lithium, deuterium, tritium, and helium in the impurity films. It allows for large-scale, high-resolution quantitative measurement of impurity films deposited on the surface of wall materials, which is of great significance for magnetic confinement fusion research and provides important reference for online measurement work in other fields. This invention proposes for the first time the idea and method of impurity film matrix classification. By pre-classifying the samples to be tested and establishing correction factors for factors such as optical system, spectroscopic parameters, and self-absorption under the same matrix conditions, the quantitative accuracy of LIBS under extreme conditions can be significantly improved, which is of great value and significance for the promotion of LIBS technology. Attached Figure Description

[0033] Figure 1 This is a flowchart of the screening-type single-standard modified laser-induced breakdown spectroscopy quantitative analysis method according to an embodiment of the present invention.

[0034] Figure 2 This is a graph showing the relationship between the spectral line ratio and the elemental content ratio in an embodiment of the present invention.

[0035] Figure 3 These are Boltzmann slope diagrams of standard thin film samples in the embodiments of the present invention; where (a) is CF-LIBS and (b) is OPC-LIBS.

[0036] Figure 4This is a comparison of the quantitative analysis results of the embodiments of the present invention using traditional CF-LIBS, OPC-LIBS and COPC-LIBS (the method of the present invention). Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0038] like Figure 1 As shown, this embodiment of the invention provides a method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy, comprising the following steps:

[0039] Step 1) Set the instrument parameters of the LIBS prior measurement system, wherein the laser output energy is higher than 5 J / cm². 2 The spectrometer uses a gate delay time of 100 ns and a gate width of 200 ns to ensure that the pulsed laser ablation of the impurity film is stoichiometric ablation, and that the laser ablation plasma is in a high-temperature, high-density local thermal equilibrium state at the time of spectral acquisition.

[0040] Step 2) At the moment of spectral acquisition, the temperature and density of the plasma generated by the ablation of the impurity film are simultaneously measured using a Thomson scattering spectrometer.

[0041] Step 3) Collect or prepare impurity film samples composed of multiple elements such as tungsten, molybdenum, boron, lithium, and iron. Quantitatively analyze the content of each element in the impurity film sample using inductively coupled plasma mass spectrometry or spectroscopy. Perform LIBS measurement of the impurity film sample under vacuum and magnetic field conditions and store the spectral data.

[0042] Step 4) Establish an array of intervals dividing the co-deposited thin films into different substrates based on the ratio of characteristic spectral line intensities. For example... Figure 2 As shown, co-deposited impurity films with molybdenum and tungsten as the main elements are classified into three segments by comparing the ratio of characteristic spectral lines of molybdenum and tungsten: <0.6, >0.6 and <1.75, and >1.75. These segments correspond to tungsten-based, tungsten-molybdenum-based, and molybdenum-based samples, respectively. The molybdenum-tungsten characteristic peak ratio of an unknown sample can be used to classify it. In practice, the intensity ratio of LIBS characteristic spectral lines among the elements should be considered based on the types and number of elements present, and the sample types should be classified in an array format.

[0043] Step 5) Within each of the three sub-intervals, samples with tungsten and molybdenum contents distributed in the middle range are selected as spectral standard thin film samples for the single-standard correction model. The true content of each element is determined by inductively coupled plasma mass spectrometry or other spectroscopic methods. Specific examples include... Figure 3 As shown in the figure, the molybdenum-tungsten ratio relationship is selected for ease of display only. Figure 3 In the middle (a), the Boltzmann slope diagram of the CF-LIBS quantitative analysis of the standard thin film sample is shown. Each element has a corresponding spectral data distribution scatter plot. The relative content of each element is obtained based on the intercept of the fitted line. Figure 3 (b) shows the Boltzmann slope plot for OPC-LIBS quantitative analysis of the spectral standard thin film sample. The slope can be referenced to the plasma temperature measured by Thomson spectroscopy, and the intercept can be calculated based on the actual content of each element. In this plot, the characteristic spectral data points of each element are in an ideal linear distribution. Figure 3 In (a) the data point moves to Figure 3 The coordinates of (b) in the diagram allow for the calculation of the spectral intensity correction factor. This correction factor comprehensively corrects for errors caused by the optical collection system, spectral parameters, and self-absorption, significantly improving quantitative accuracy.

[0044] Step 6) Reference Figure 2 Three subsets were selected, and three spectral standard thin film samples were chosen to establish three sets of characteristic spectral coefficients.

[0045] Step 7) In the online LIBS experiment of the magnetic confinement fusion device, the laser and spectrometer are both operating under optimal experimental conditions (laser energy density 5 J / cm²). 2 The spectrometer has a gate delay of 100 ns and a gate width of 200 ns. The acquired LIBS spectra are analyzed, and the ratio of characteristic spectral intensities of each element is used to determine the ratio of molybdenum and tungsten content. Based on the classification criteria, the matrix properties are classified.

[0046] Based on matrix property classification, the corresponding characteristic spectral correction coefficients are read, the spectral intensity of the spectral data to be analyzed is corrected, and then CF-LIBS calculation is performed to obtain high-precision quantitative analysis results. Figure 4 The accuracy of online LIBS quantitative analysis under a wide range of tungsten (10%–92%) and molybdenum (2%–71%) elemental content is presented. The absolute errors of tungsten content quantitative analysis using different methods are compared: traditional CF-LIBS has an error of 13.07%, OPC-LIBS has an error of 9.66%, while the absolute error of the proposed method—selecting spectral standards similar to the matrix of the sample under test based on attribute classification for single-standard correction spectral calculation—is only 4.34%, significantly improving the quantitative accuracy of online LIBS measurements in magnetic confinement fusion devices.

[0047] Finally, it should be noted that the above embodiments are intended to illustrate the technical solutions of the present invention and do not constitute any limitation on the present invention. Those skilled in the art should fully understand that modifications to the technical solutions described in the foregoing embodiments or equivalent substitutions for any part or all of the technical features are entirely feasible. Such modifications or substitutions, as long as they do not depart from the scope of protection defined by the claims of the present invention, should be considered reasonable extensions of the present invention.

Claims

1. A method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy, characterized in that, Includes the following steps: Optimize the experimental parameters of laser-induced breakdown spectroscopy under vacuum and strong magnetic field conditions, including: adjusting the energy density of the incident laser so that the laser ablates the impurity film and the resulting plasma is chemically induced ablation, and the luminescent elements in the laser ablation plasma are consistent with the elements in the impurity film; and adjusting the gate delay and gate width time of the spectrometer so that the laser ablation plasma is in a state of local thermodynamic equilibrium. A pre-classification model for the composition of deposited impurity films is established. The pre-classification model classifies the matrix properties of samples based on LIBS characteristic spectral line analysis of impurity films, and each classification is a subset of the same matrix as a co-deposited film. Standard film samples were selected from each co-deposited film substrate subset, and the LIBS characteristic spectra of each standard film sample were collected. Based on the LIBS characteristic spectra, a database of characteristic spectral correction factors was obtained through a single standard sample correction model. Based on the optimized laser-induced breakdown spectroscopy experimental parameters, the LIBS characteristic spectra of the impurity deposition layer were acquired using an online LIBS measurement system. The matrix properties of the co-deposited film were determined using the pre-classification model of the deposited impurity film components. The corresponding characteristic spectral correction coefficients in the characteristic spectral correction factor database were read according to the matrix properties. After multiplying the characteristic spectral lines in the online LIBS spectrum by the correction coefficients, CF-LIBS calculations were performed to obtain the quantitative analysis results of LIBS.

2. The method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to claim 1, characterized in that, The process of establishing the database of characteristic spectral line spectral correction factors is as follows: In each subset of co-deposited films, a standard film sample was selected. Under the vacuum, strong magnetic field, and optical path conditions of a 1:1 simulated fusion device, the parameters of the laser and spectrometer of the LIBS online measurement system were set to be consistent with the set optimized parameters, and the LIBS characteristic spectra of each standard film sample were measured. The plasma temperature generated by laser ablation of standard thin film samples under LIBS optimized parameter experimental conditions was measured using the Thomson scattering method. The reciprocal of the plasma temperature was used as a reference value for the slope fitting of the subsequent Boltzmann distribution plot. The characteristic spectra of each collected standard thin film sample were quantitatively analyzed by CF-LIBS, and the calculation results were compared with the elemental content values ​​of the corresponding standard thin film sample to determine the deviation between the calculated and theoretical values. The intercepts of the linear distribution of the characteristic spectral data points of each element in the Boltzmann slope diagram were calculated using the actual content, and regression correction was performed on the Boltzmann slope diagram with reference to the calculated values ​​of the actual content to obtain the correction coefficients for the characteristic spectra of all elements of the same matrix subset of the co-deposited thin film.

3. The method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to claim 2, characterized in that, The selection criterion for the standard thin film sample is that the content values ​​of each component in the same matrix subset of the co-deposited thin film are in the middle of the corresponding range.

4. The method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to claim 1, characterized in that, A nanosecond laser pulse with a wavelength of 1064 nm was used to irradiate the surface of the impurity film with an energy density exceeding 5 J / cm². 2 .

5. The method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to claim 1, characterized in that, The spectrometer uses a gate delay time of 100-200 ns and a gate width time of 100-200 ns.

6. The method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to claim 1, characterized in that, The method for establishing the pre-classification model of the deposited impurity film composition includes multivariate statistical methods and artificial intelligence algorithms; wherein, the multivariate statistical methods perform classification modeling based on PCA or PLS models, and by inputting spectral data, establish the mapping relationship between classification features based on the intensity information of characteristic spectra, and give the judgment value of the matrix properties of the impurity film.

7. A method for quantitative analysis of elements on the inner wall surface of a magnetic confinement fusion device using laser-induced breakdown spectroscopy according to any one of claims 1-6, characterized in that, The LIBS characteristic spectra of the wall material at different locations were collected by scanning in three-dimensional space using an online LIBS measurement system. The matrix properties are determined based on the pre-classification model of the deposited impurity film components, and the corresponding characteristic spectral correction coefficients are selected from the characteristic spectral correction factor database based on the matrix properties; then, CF-LIBS calculation is performed to obtain the content values ​​of the elements contained at each point, and the spatial distribution relationship of each element is reconstructed.

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