Method and system for detecting and analyzing mixed material based on LIBS (Laser-induced Breakdown Spectroscopy) technology

Abstract

The invention belongs to the technical field of component analysis of mixed materials, particularly relates to a method and a system for detecting and analyzing mixed materials based on an LIBS (laser-induced breakdown spectroscopy) technology, and provides a method for analyzing samples which are accurate, efficient and suitable for large water content change. According to the method, the spectrum of the mixed materials with the same concentration under different water contents is detected, a standardized model is established, the spectrum change of the mixed materials with the same concentration under different water contents is analyzed, the spectrum data is corrected according to the water content of a sample to be detected, and the influence of the water content on the detection result is effectively compensated. A target-enhanced DP-LIBS method is adopted, an aluminum target is arranged on the surface of a sample, a delay pulse generator controls a first laser pulse transmitter and a second laser pulse transmitter, a first laser beam and a second laser beam which are relatively delayed are transmitted, and the target plasma and the sample plasma are mutually acted, so that the target plasma and the sample plasma can be detected. The shielding effect of water molecules on plasma is reduced, and the signal intensity of sample elements is remarkably enhanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of mixed material component analysis, and specifically relates to a mixed material detection and analysis method and system based on LIBS technology. Background Art

[0002] Laser induced breakdown spectroscopy (LIBS) technology, as a fast and non-destructive elemental analysis technology, has developed rapidly in the fields of material analysis, environmental monitoring, biomedicine, etc. in recent years. LIBS technology uses high-energy laser pulses to irradiate the sample surface to generate plasma. By analyzing the spectrum emitted by the plasma, the elements present in the sample and their content can be identified. However, the existing LIBS technology still has certain limitations when analyzing samples with large changes in water content, such as insufficient analysis accuracy and weak signal intensity.

[0003] Therefore, there is an urgent need for an analytical method that can effectively solve the influence of water content on LIBS detection results, so as to broaden the application scope of LIBS technology and enable it to be better applied to the analysis of samples with large changes in water content. Summary of the invention

[0004] The present invention overcomes the deficiencies of the prior art and provides a detection and analysis method and system for mixed materials based on LIBS technology.

[0005] To achieve the above object, the technical solution adopted by the present invention is: a detection and analysis method of mixed materials based on LIBS technology, characterized in that it comprises the following steps:

[0006] S1. Pre-treat and group the mixed materials with known element concentrations, and control the water content of each group of mixed materials to be different;

[0007] S2, perform LIBS detection on each group of mixed materials in S1, collect spectral data and preprocess;

[0008] S3, establishing a standardization model to standardize the spectral data;

[0009] S4, pre-treating the mixed material to be tested and detecting the water content of the mixed material to be tested;

[0010] S5, perform LIBS detection on the mixed material in S4, collect spectral data and pre-process;

[0011] S6. Input the spectral data in S5 into the standardized model in S3 to perform component analysis on the mixed material to be tested.

[0012] In a preferred embodiment of the present invention, in step S1, pre-processing the mixed materials with known element concentrations includes collecting materials with known concentrations, crushing and screening the materials, and mixing the materials evenly, and dividing them into several groups; detecting and adjusting the water content of each group of mixed materials, controlling the water content of each group of mixed materials to be different, and recording the element concentration and water content of each group of mixtures.

[0013] In a preferred embodiment of the present invention, the preprocessing of the spectral data includes one or more of the following methods: filtering out noise, subtracting background, correcting spectral baseline, and principal component analysis.

[0014] In a preferred embodiment of the present invention, the LIBS detection method is a double-pulse reheating orthogonal DP-LIBS detection method.

[0015] In a preferred embodiment of the present invention, the LIBS detection method is a target enhanced DP-LIBS method.

[0016] In a preferred embodiment of the present invention, the partial least squares (PLS) method is used to establish a standardized model in step S3.

[0017] In a preferred embodiment of the present invention, step S6 further comprises evaluating the standardized model by a mean square error, a root mean square error or an R square indicator.

[0018] The present invention also provides a detection and analysis system for mixed materials based on LIBS technology, which is used to implement the above method and includes the following modules:

[0019] A sample processing module, used for pre-processing samples;

[0020] Sample water sample detection module, used to detect and adjust the water content of the sample;

[0021] LISB detection module, used to perform LIBS detection and collect spectral data;

[0022] A spectral data preprocessing module, used for preprocessing the collected spectral data;

[0023] The data analysis and standardization module is used to extract characteristic spectra, establish standardization models, and output detection results.

[0024] In a preferred embodiment of the present invention, the LISB detection module includes an optical platform for placing samples, an aluminum target closely attached to the optical platform, a first laser pulse emitter and a second laser pulse emitter relatively arranged above the optical platform, a delayed pulse generator connecting the first laser pulse emitter and the second laser pulse emitter, a spectrometer for collecting and processing spectral data, and a digital computer electrically connected to the spectrometer.

[0025] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0026] (1) The present invention improves the overall efficiency and accuracy of detection and analysis by pretreating samples, detecting and adjusting the water content of samples, performing LIBS detection and collecting spectral data, preprocessing spectral data, establishing a standardized model and analyzing the detection results, so that reliable component analysis results can be obtained under different water content conditions.

[0027] (2) The present invention detects the spectra of mixed materials of the same concentration at different water contents, establishes a standardized model, analyzes the spectral changes of mixed materials of the same concentration at different water contents, describes the relationship between water content and spectral intensity and concentration, and then corrects the spectral data according to the water content of the sample to be tested, effectively compensating for the influence of water content on the test results. Compared with traditional methods, the method provided by the present invention can more accurately analyze mixed materials with large changes in water content, and is not affected by the large errors caused by water content fluctuations.

[0028] (3) The present invention adopts a target-enhanced DP-LIBS method, sets an aluminum target on the sample surface, and controls the first laser pulse emitter and the second laser pulse emitter through a delayed pulse generator to emit the first laser beam and the second laser beam with a relative delay, and utilizes the interaction between the target plasma and the sample plasma to reduce the shielding effect of water molecules on the plasma, thereby significantly enhancing the signal intensity of the sample elements. Compared with the traditional LIBS method, the method provided by the present invention reduces the interference of water content on spectral analysis, and can more effectively identify and analyze elements in mixed materials.

[0029] (4) On the one hand, the present invention establishes a standardized model to correct the spectral data according to the water content of the sample to be tested; on the other hand, by adopting the target-enhanced DP-LIBS method, the interaction between the target plasma and the sample plasma is utilized to enhance the signal intensity of the sample elements, thereby significantly reducing the error caused by the water content, achieving sensitive, accurate and reliable detection, and expanding the application scope of LIBS technology, which can be applied to different types of mixed materials, especially the trace element analysis of samples with large changes in water content. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1It is a flow chart of a method for detecting and analyzing mixed materials based on LIBS technology provided by the present invention;

[0032] Figure 2 It is a structural schematic diagram of a detection and analysis system for mixed materials based on LIBS technology provided by the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0035] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of the present application. In addition, the terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the invention, unless otherwise specified, "multiple" means two or more.

[0036] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0037] Application Overview

[0038] LIBS (Laser-Induced Breakdown Spectroscopy) is an analytical technique that uses a high-energy pulsed laser to focus on the sample surface, which instantly heats the sample surface to a high temperature and forms a plasma. In this process, the atoms in the sample are excited to a high energy state, and when these atoms return to a low energy state, they emit spectral lines of specific wavelengths. The spectral lines of each element have a specific wavelength, so by analyzing the wavelength and intensity of these spectral lines, the elemental composition of the sample can be identified and quantified.

[0039] Double-pulse LIBS (DP-LIBS) is a widely used micro-ablation high-sensitivity elemental analysis technology. The basic working process of DP-LIBS is that two laser pulses act on the sample or the plasma generated by the sample in a certain time sequence and time interval, and the plasma radiation intensity is increased by secondary excitation of the plasma or changing the sample surface environment.

[0040] However, for the DP-LIBS method, when a high-energy laser pulse hits the sample surface, the sample surface is rapidly heated to form a high-temperature plasma. This plasma consists of free electrons, ions, and neutral atoms and has a high electrical conductivity. When the second laser pulse arrives, the free electrons in the plasma are redistributed, forming charge separation, thereby generating a reverse electric field that can offset the electric field of the incident laser. This charge separation and the generation of a reverse electric field reduce the ability of the laser pulse to penetrate the plasma, thereby shielding the laser from further interaction with the sample.

[0041] In addition, if the sample has a high water content, the water will evaporate quickly under the action of the laser to form a water vapor plasma. This water vapor plasma will increase the complexity of the plasma and may change the conductivity and shielding effect of the plasma. High water content may cause the plasma volume to increase because the generation of water vapor increases the total volume of the plasma. The increased plasma volume may enhance the plasma shielding effect because there are more free electrons involved in charge separation and the generation of the reverse electric field. The enhanced plasma shielding effect may lead to a decrease in the intensity of the spectral signal because less sample material is excited. The stability and repeatability of the spectral signal may be affected because the intensity and duration of the plasma shielding effect may vary between different laser pulses.

[0042] Therefore, reducing the influence of water content in the sample is crucial to reduce the plasma shielding effect and improve the intensity and stability of the spectral signal.

[0043] Exemplary Methods

[0044] like Figure 1 As shown, a detection and analysis method for mixed materials based on LIBS technology includes the following steps:

[0045] S1. Pre-treat and group the mixed materials with known element concentrations, and control the water content of each group of mixed materials to be different;

[0046] S2, perform LIBS detection on each group of mixed materials in S1, collect spectral data and preprocess;

[0047] S3, establishing a standardization model to standardize the spectral data;

[0048] S4, pre-treating the mixed material to be tested and detecting the water content of the mixed material to be tested;

[0049] S5, perform LIBS detection on the mixed material in S4, collect spectral data and pre-process;

[0050] S6. Input the spectral data in S5 into the standardized model in S3 to perform component analysis on the mixed material to be tested.

[0051] Below, each step will be described in detail.

[0052] In step S1, pre-processing the mixed material with known concentrations of various elements includes collecting materials with known concentrations, breaking large pieces of materials into smaller particles, screening, mixing the materials evenly and dividing them into several groups.

[0053] In step S1, the water content of each group of mixed materials is detected and adjusted to control the water content of each group of mixed materials to be different, and the element concentration and water content of each group of mixtures are recorded.

[0054] In a specific embodiment, the composition of the secret brass is analyzed, and a batch of secret brass samples with known concentrations are prepared. The element contents in the secret brass samples are shown in Table 1:

[0055] Table 1 Contents of main elements in brass samples

[0056] name Cu Zn Bi Pb content(%) 59.387 35.0824 3.002 0.0054 name Fe Sn Ni Sb content(%) 0.448 1.038 0.98 0.20022

[0057] Use a jaw crusher to break the large pieces of secret brass samples into small pieces, use a ball mill to further grind the small pieces into particles with a particle size of less than 2mm, and use a screening tool with an aperture of 1mm to screen the particles. Divide the secret brass particles into 10 groups of equal volume, and then test the water content of each group of secret brass particles, and adjust the water content of each group of samples by drying and evaporation or adding water to moisten. The final results are shown in Table 2:

[0058] Table 2 Water content data of ten groups of samples

[0059] Group No. 1 2 3 4 5 6 7 8 9 10 Water content (%) 2 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10

[0060] It should be noted that the concentration value of a known element concentration can be obtained through chemical analysis.

[0061] In step S2, the LIBS detection method is specifically a double-pulse reheating orthogonal DP-LIBS detection method, which collects the composite light emitted by each group of samples, decomposes the composite light into monochromatic light, and generates a characteristic spectrum of the element.

[0062] In a specific embodiment, a cross-type double-pulse laser device is used, and the laser device emits geometrically orthogonal horizontal laser beams and vertical laser beams, which are incident parallel to the sample surface and incident perpendicular to the sample surface, respectively, and the horizontal laser beam arrives at the sample surface later than the vertical laser beam. A spectrometer is used to collect spectral signals, and the collected composite light is decomposed into monochromatic light, and the decomposed monochromatic light is converted into electrical signals through a photodetector to generate corresponding spectral data and spectral graphs.

[0063] In step S2, the collected spectral data is preprocessed, including filtering out noise, subtracting background, and correcting the spectral baseline, and the principal component analysis (PCA) method is used to extract the main components in the spectral data and remove redundant information.

[0064] In step S3, the partial least squares PLS method is used to establish a standardized model: the independent variables include spectral data and water content. This is because the spectral data (including the spectral intensity at different wavelengths) reflects the characteristic spectral information of the elements in the sample, and the water content affects the intensity and stability of the spectral data. Therefore, when constructing the independent variable matrix, each row represents a sample, and each column represents a specific independent variable (spectral intensity or water content at a certain wavelength). The dependent variable is the element concentration, which is known. When constructing the dependent variable matrix, each row represents a sample, and each column represents a specific dependent variable (the concentration of a certain element).

[0065] Set the independent variable matrix X, arrange the preprocessed spectral data (spectral intensity at different wavelengths) and water content data according to the samples to form a two-dimensional matrix. The number of rows in the matrix is ​​equal to the number of samples, and the number of columns is equal to the number of independent variables.

[0066] Set the dependent variable matrix Y, and arrange the known element concentrations according to the samples to form a two-dimensional matrix. The number of rows in the matrix is ​​equal to the number of samples, and the number of columns is equal to the number of dependent variables (the number of element types).

[0067] In a specific embodiment, 5 groups of samples are extracted, and the spectral intensity and water content at 3 different wavelengths are selected, and the obtained independent variable matrix (X) and dependent variable matrix (Y) are as follows:

[0068] The independent variable matrix (X) is expressed as

[0069] SampleWavelength 1Wavelength 2Wavelength 3Water ContentIntensityIntensity Intensity

[0070] Sample 1 100 150 200 4.5%

[0071]

[0072] The dependent variable matrix (Y) is expressed as

[0073]

[0074] In step S4, pre-processing the mixed material to be tested includes collecting the material, breaking the large pieces of material into smaller particles, sieving and mixing the material evenly, and detecting the water content of the mixed material to be tested.

[0075] In step S5, the LIBS detection method is specifically a double pulse reheating orthogonal DP-LIBS detection method, which collects the composite light emitted by each group of samples, decomposes the composite light into monochromatic light, and generates a characteristic spectrum of the element. The collected spectral data is preprocessed, including filtering out noise, subtracting background, and correcting the spectral baseline, and the main components in the spectral data are extracted by the principal component analysis (PCA) method to remove redundant information.

[0076] In a specific embodiment, the LIBS detection method in step S2 and step S5 is specifically a target enhanced DP-LIBS method. The specific steps include:

[0077] T1. Place the sample on the sample placement table and set an aluminum target horizontally near the sample surface;

[0078] T2. Set up two lasers, one laser is vertically aimed at the sample surface to emit the first laser beam, and the other laser is vertically aimed at the aluminum target surface close to the sample to emit the second laser beam;

[0079] T3. Adjust the relative delay between the first laser beam and the second laser beam for detection.

[0080] The relative delay between the first laser beam and the second laser beam is 4.0 μm.

[0081] In step S6, the spectral data in S5 is input into the standardized model in S3 to regenerate the independent variable matrix (X test ) and the dependent variable matrix (Y predicted ), using the standardized model to predict the element concentration in the mixed material to be tested.

[0082] In a specific embodiment, the sample to be tested is tested, and the spectral intensity and water content at three different wavelengths are selected to obtain the regenerated independent variable matrix (X test ) and the dependent variable matrix (Y predicted ) is as follows:

[0083] The regenerated independent variable matrix (X test ) is expressed as

[0084]

[0085] The regenerated dependent variable matrix (Y predicted ) is expressed as

[0086]

[0087] It should be noted that the dependent variable matrix (Y predicted ) is an expected format to be predicted and has not yet been calculated by the standardized model. Among them, α1, β1, and γ1 represent the predicted concentrations.

[0088] The above regenerated independent variable matrix (X test ) and the regenerated dependent variable matrix (Y predicted ) is input into the standardized model for operation, and the actual regenerated dependent variable matrix (Y predicted ).

[0089] The actual regenerated dependent variable matrix (Y predicted )The results are as follows:

[0090]

[0091]

[0092] That is, the predicted concentration of each element in the mixed material to be tested.

[0093] In step S3, the standardized model needs to be trained and optimized, including providing a larger number of samples to improve the prediction accuracy of the model.

[0094] In step S6, the predicted concentration obtained by the standardized model is compared with the actual concentration of the material and the mean square error (MSE), root mean square error (RMSE) or R square (R 2 ) indicators to evaluate the accuracy of the model.

[0095] In a specific embodiment, the actual concentration and predicted concentration of Cu, Zn and Pb elements in the secret brass sample are shown in Table 3:

[0096] Table 3 Actual and predicted concentrations of Cu, Zn and Pb elements in brass samples

[0097]

[0098] For each element (Cu, Zn, Pb), MSE, RMSE and R 2 , the calculation results are shown in Table 4:

[0099] Table 4 MSE, RMSE and R 2 index

[0100]

[0101]

[0102] in, The MSE and RMSE of Pb are approximately 0. This is because for the Pb element, even if there is a small difference between the predicted value and the actual value, its MSE value is very small.

[0103] Table 4 shows the performance evaluation indicators of the three elements Cu, Zn and Pb in actual concentration prediction, indicating that the concentration values ​​predicted by the model in this method are relatively accurate and reliable.

[0104] Exemplary Systems

[0105] like Figure 2 As shown, a detection and analysis system for mixed materials based on LIBS technology includes:

[0106] A sample processing module, used for pre-processing samples;

[0107] Sample water sample detection module, used to detect and adjust the water content of the sample;

[0108] LISB detection module, used to perform LIBS detection and collect spectral data;

[0109] A spectral data preprocessing module, used for preprocessing the collected spectral data;

[0110] The data analysis and standardization module is used to extract characteristic spectra, establish standardization models, and output detection results.

[0111] In a specific embodiment, the LISB detection module includes an optical platform for placing samples, an aluminum target close to the optical platform, a first laser pulse emitter and a second laser pulse emitter relatively arranged above the optical platform, a delayed pulse generator connecting the first laser pulse emitter and the second laser pulse emitter, a spectrometer for collecting and processing spectral data, and a digital computer electrically connected to the spectrometer.

[0112] The above is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and the technical scope must be determined according to the scope of the claims.

Claims

1. A method for detecting and analyzing mixed materials based on LIBS technology, characterized in that: The following steps are involved: S1. Pre-treat and group the mixed materials with known element concentrations, and control the water content of each group of mixed materials to be different; S2, perform LIBS detection on each group of mixed materials in S1, collect spectral data and preprocess; S3, establishing a standardization model to standardize the spectral data; S4, pre-treating the mixed material to be tested and detecting the water content of the mixed material to be tested; S5, perform LIBS detection on the mixed material in S4, collect spectral data and pre-process; S6. Input the spectral data in S5 into the standardized model in S3 to perform component analysis on the mixed material to be tested.

2. A method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: In step S1, pre-processing the mixed materials with known element concentrations includes collecting materials with known concentrations, crushing and screening the materials, mixing the materials evenly, and dividing them into several groups; detecting and adjusting the water content of each group of mixed materials, controlling the water content of each group of mixed materials to be different, and recording the element concentration and water content of each group of mixtures.

3. A method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: The preprocessing of the spectral data includes one or more of the following methods: filtering out noise, subtracting background, correcting spectral baseline, and principal component analysis method.

4. A method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: The LIBS detection method is a double-pulse reheating orthogonal DP-LIBS detection method.

5. The method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: The LIBS detection method is a target enhanced DP-LIBS method.

6. A method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: In step S3, the partial least squares (PLS) method is used to establish a standardized model.

7. A method for detecting and analyzing mixed materials based on LIBS technology according to claim 1, characterized in that: Step S6 also includes evaluating the standardized model by the mean square error, root mean square error or R square indicator.

8. A detection and analysis system for mixed materials based on LIBS technology, used to implement the method described in any one of claims 1 to 7, characterized in that: Includes the following modules: A sample processing module, used for pre-processing samples; Sample water sample detection module, used to detect and adjust the water content of the sample; LISB detection module, used to perform LIBS detection and collect spectral data; A spectral data preprocessing module, used for preprocessing the collected spectral data; The data analysis and standardization module is used to extract characteristic spectra, establish standardization models, and output detection results.

9. A detection and analysis system for mixed materials based on LIBS technology according to claim 8, characterized in that: The LISB detection module includes an optical platform for placing samples, an aluminum target closely attached to the optical platform, a first laser pulse emitter and a second laser pulse emitter relatively arranged above the optical platform, a delayed pulse generator connecting the first laser pulse emitter and the second laser pulse emitter, a spectrometer for collecting and processing spectral data, and a digital computer electrically connected to the spectrometer.

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