FL-LIBS calibration-free method, device and equipment based on non-gated acquisition and medium

Abstract

The invention relates to the technical field of atomic spectrum detection, in particular to an FL-LIBS calibration-free method, device and equipment based on non-gated acquisition and a medium. The method comprises the following steps: acquiring a correction spectrum and determining a target reference element; obtaining a plurality of candidate vectors and determining candidate simulation spectrums; iteratively updating each candidate vector; determining a target simulation spectrum, and determining an optimal vector; determining a target electron temperature and a target particle number density; determining the particle number density of other elements in the to-be-detected sample according to the target electron temperature; and carrying out normalization calculation on the target particle number density and the particle number density of other elements to obtain the concentration composition of the sample to be detected. According to the method, a plurality of unknown parameter groups, namely the candidate vectors, are generated, the optimal vector which is the best matched with the unknown parameter groups is searched by means of the optimization algorithm, under the condition that a high-speed gated detector is separated, a method for obtaining the electron temperature needed by the time integral spectrum is provided, and meanwhile, calibration-free quantitative analysis of FL-LIBS can be rapidly and accurately achieved.

Description

Technical Field

[0001] The present application relates to the technical field of atomic spectrum detection, and in particular, to a calibration-free method, device, equipment and medium for FL-LIBS based on non-gated acquisition. Background Art

[0002] Laser-induced breakdown spectroscopy (LIBS), for short, has become a promising atomic spectrum detection technology with the advantages of fast, in-situ, non-contact, and online diagnosis. Traditional LIBS systems usually use solid-state lasers with a low pulse output frequency as the plasma excitation source. Such lasers cannot maintain a stable pulse energy during long-term operation. The unstable pulse energy will cause fluctuations in the LIBS spectrum, resulting in a decrease in analysis accuracy. Fiber lasers can maintain a more stable pulse energy during long-term operation, and the cost of some models is less than one-tenth of that of solid-state lasers, making fiber laser-induced breakdown spectroscopy (FL-LIBS), for short, a new direction for the improvement of LIBS technology.

[0003] Although FL-LIBS has many advantages, its high repetition frequency (≥20kHz) makes it difficult to achieve synchronization between acquisition and pulses. Although gated detectors equipped with high-speed shutters can achieve timing synchronization with pulses, their high price and strict working temperature requirements make them only applicable to laboratory scenarios. In addition, the single-pulse energy of fiber lasers is low, and the signal-to-noise ratio of the spectrum of a single plasma (the spectrum after the accumulation of a few plasmas) is very poor. Therefore, non-gated detectors are usually used to collect FL-LIBS spectra under an exposure time much longer than the plasma generation period. However, the FL-LIBS spectra obtained under this acquisition strategy contain the entire evolution process of the plasma, and the quantitative analysis results obtained using the Calibration-Free LIBS method are difficult to be satisfactory. Therefore, most studies on FL-LIBS still use the standard sample calibration method. In short, there is currently no calibration-free model for FL-LIBS based on non-gated acquisition. Summary of the Invention

[0004] The present application provides a calibration-free method, device, equipment and medium for FL-LIBS based on non-gated acquisition to solve one or more technical problems existing in the prior art, and at least provide a beneficial choice or create conditions.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or will be learned in part through the practice of the present application.

[0006] According to one aspect of the embodiments of the present application, a non-gated acquisition-based FL-LIBS calibration-free method is provided, and the method includes:

[0007] Obtain a corrected spectrum, and determine a target reference element according to the corrected spectrum, where the corrected spectrum is obtained from the FL-LIBS spectrum collected by the non-gated acquisition system for the sample to be measured;

[0008] Obtain a number of candidate vectors containing electron temperature and reference element particle number density information, and determine candidate simulation spectra corresponding to each of the candidate vectors. The candidate vectors correspond to the target reference element, and the values of the candidate vectors are randomly generated within a preset range;

[0009] Iteratively update each of the candidate vectors according to a preset optimization algorithm. In each iteration round, the fitness of each of the candidate vectors is evaluated in a parallel evaluation manner. The parallel evaluation manner is to compare the similarity between each of the candidate simulation spectra and the corrected spectrum;

[0010] Determine a target simulation spectrum with the highest similarity to the corrected spectrum according to the fitness of each of the candidate vectors in the final iteration round, and determine the candidate simulation vector corresponding to the target simulation spectrum as the optimal vector;

[0011] Determine the target electron temperature and the target particle number density of the target reference element according to the optimal vector;

[0012] Determine the particle number density of other elements in the sample to be measured except the target reference element according to the target electron temperature;

[0013] Perform normalization calculation on the target particle number density and the particle number density of each of the other elements to obtain the concentration composition of the sample to be measured.

[0014] In an embodiment of the present application, based on the foregoing solution, before obtaining the corrected spectrum, the method further includes:

[0015] Obtain the FL-LIBS spectrum collected by the non-gated acquisition system for the sample to be measured;

[0016] Perform preprocessing of background removal, noise removal, and peak searching on the FL-LIBS spectrum to obtain a preprocessed measurement spectrum.

[0017] In an embodiment of the present application, based on the foregoing solution, the corrected spectrum is obtained through the following steps:

[0018] Determine a target spectral line with the maximum intensity among the respective spectral lines of the measured spectrum;

[0019] Determine the corrected spectrum according to the spectral line parameters of the target spectral line and a preset correction coefficient.

[0020] In an embodiment of the present application, based on the foregoing solution, the determining the target reference element according to the corrected spectrum includes:

[0021] Select an element that satisfies a preset condition among the respective elements of the corrected spectrum as the target reference element;

[0022] Wherein, the preset condition is to have the largest number and exceed a preset signal-to-noise ratio threshold of observed spectral lines.

[0023] In an embodiment of the present application, based on the foregoing solution, the candidate simulated spectrum corresponding to a single candidate vector is obtained through the following steps:

[0024] Determine a first spectral line intensity parameter according to a preset first calculation formula, target parameters, and the candidate vector;

[0025] Perform time integration on the first spectral line intensity parameter to obtain the candidate simulated spectrum.

[0026] In an embodiment of the present application, based on the foregoing solution, the preset range is obtained through the following steps:

[0027] Determine a second spectral line intensity parameter according to the first calculation formula, the target parameters, and a preset electron temperature;

[0028] Determine a third spectral line intensity parameter according to a preset second calculation formula, the target parameters, and the preset electron temperature;

[0029] Determine a theoretical self-absorption coefficient curve related to the particle number density and the preset electron temperature according to the ratio of the second spectral line intensity parameter and the third spectral line intensity parameter;

[0030] Determine the value range of the particle number density according to the theoretical self-absorption coefficient curve, and use the value range as the preset range.

[0031] According to one aspect of the embodiments of the present application, there is provided a non-gated acquisition-based FL-LIBS calibration-free device, and the device includes:

[0032] A first acquisition unit, configured to acquire a corrected spectrum and determine a target reference element according to the corrected spectrum, where the corrected spectrum is obtained from the FL-LIBS spectrum acquired by a non-gated acquisition system for a sample to be measured;

[0033] A second acquisition unit, configured to acquire a plurality of candidate vectors including electronic temperature and reference element particle number density information, and determine candidate simulation spectra corresponding to each of the candidate vectors, where the candidate vectors correspond to the target reference element, and the values of the candidate vectors are randomly generated within a preset range;

[0034] An iteration unit, configured to iteratively update each of the candidate vectors according to a preset optimization algorithm, and evaluate the fitness of each of the candidate vectors in a parallel evaluation manner in each iteration round, where the parallel evaluation manner is to compare the similarity between each of the candidate simulation spectra and the corrected spectrum;

[0035] A first determination unit, configured to determine a target simulation spectrum with the highest similarity to the corrected spectrum according to the fitness of each of the candidate vectors in the final iteration round, and determine the candidate simulation vector corresponding to the target simulation spectrum as the optimal vector;

[0036] A second determination unit, configured to determine a target electronic temperature and a target particle number density of the target reference element according to the optimal vector;

[0037] A third determination unit, configured to determine the particle number density of other elements in the sample to be measured except the target reference element according to the target electronic temperature;

[0038] A concentration calculation unit, configured to perform normalization calculation on the target particle number density and the particle number density of each of the other elements to obtain the concentration composition of the sample to be measured.

[0039] According to one aspect of the embodiments of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and the computer program includes executable instructions, and when the executable instructions are executed by a processor, the method described in the above embodiments is implemented.

[0040] According to one aspect of the embodiments of the present application, there is provided an electronic device, including: one or more processors; a memory, configured to store executable instructions of the processor, and when the executable instructions are executed by the one or more processors, the one or more processors implement the method described in the above embodiments.

[0041] Advantages of the present application: From the corrected spectrum obtained from the FL-LIBS spectrum collected by the non-gated acquisition system for the sample to be measured, it is possible to visually observe the target reference elements with a relatively large number of spectral lines and a high signal-to-noise ratio. Thus, subsequent concentration calibration based on the target reference elements makes the calibration result more accurate. Further, by obtaining a number of candidate vectors, that is, by introducing randomly generated unknowns, each of the candidate vectors is iteratively updated through a preset optimization algorithm. In each iteration round, the fitness of each candidate vector is evaluated in a parallel evaluation manner. The parallel evaluation manner is to compare the similarity of each candidate simulation spectrum with the corrected spectrum respectively, so as to determine the target simulation spectrum with the highest similarity to the corrected spectrum, and then obtain the optimal vector.

[0042] The optimal vector obtained can be used to determine the target electron temperature, that is, the electron temperature of the plasma induced by the laser for the sample to be measured can be obtained, without the need to use a gated detector with high cost in the prior art to determine the electron temperature. Further, based on the determined target electron temperature and the target particle number density of the target reference element, the particle number density of other elements in the sample to be measured can be obtained, and then the concentration of each element can be obtained, so as to complete the calibration of the sample to be measured.

[0043] The present application generates a number of unknown parameter groups, that is, candidate vectors, and uses an optimization algorithm to find the most matching optimal vector, thereby obtaining the electron temperature evolving with time. Without using a high-speed gated detector, a method for obtaining the time-resolved electron temperature required for the time-integrated spectrum is provided, and at the same time, the calibration-free quantitative analysis of FL-LIBS can be quickly and accurately realized.

[0044] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0046] Figure 1 is a flowchart of a calibration-free method for FL-LIBS based on non-gated acquisition according to an embodiment of the present application;

[0047] Figure 2 is a specific logic flowchart of a calibration-free method for FL-LIBS based on non-gated acquisition proposed by an embodiment of the present application;

[0048] Figure 3 This is the specific step diagram of the optimization algorithm proposed in the embodiments of the present application;

[0049] Figure 4 This is the block diagram of the FL-LIBS calibration-free device based on non-gated acquisition shown in the embodiments of the present application;

[0050] Figure 5 This is the structural diagram of the electronic device shown in the present application. Detailed implementation manners

[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0052] In addition, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will recognize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be employed. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0053] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller node devices.

[0054] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all the content and operations / steps, nor do they necessarily have to be executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0055] It should be noted that: "a plurality of" as mentioned herein refers to two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0056] The following is a detailed description of the background technology of the embodiments of the present application:

[0057] Laser-induced breakdown spectroscopy (LIBS) is an atomic spectrum detection technology that combines the advantages of in-situ, fast, and contactless, and can perform full-element qualitative or quantitative analysis on most samples. In the past decade, fiber lasers have gradually replaced traditional solid or gas lasers and are widely used in industrial processing and intelligent manufacturing. Combining the advantages of both, fiber laser-induced breakdown spectroscopy (FL-LIBS) has the following advantages: first, it can work stably for a long time; second, the ultra-high output frequency of fiber lasers can greatly improve the collection efficiency compared with solid pulse lasers; third, the lower maintenance cost is conducive to the commercialization of LIBS detection equipment. Therefore, promoting the research on FL-LIBS calibration methods can not only improve the maturity of the technology, but also expand the application scenarios of LIBS, providing new solutions for rapid detection and online detection.

[0058] The FL-LIBS spectrum contains the spectral line information of each element to be tested, and the peak intensity can reflect the particle number density of each element. How to specifically infer the concentration composition of the sample to be tested from the peak intensity of the spectrum involves the study of calibration methods / calibration models.

[0059] Existing technical solutions for FL-LIBS quantitative analysis include:

[0060] ① Standard sample calibration is currently the most common quantitative analysis method for FL-LIBS. A variety of improved methods have been derived around hardware system improvements, spectral preprocessing and machine learning, which are suitable for non-gated acquisition strategies.

[0061] ② Very few researchers use free calibration method to quantitatively analyze FL-LIBS. However, the detection of spectrum depends on the gated acquisition strategy, which requires expensive gated detectors with high-speed shutters and cannot be separated from trigger synchronization devices such as photoelectric modulators.

[0062] ③ Few researchers use free calibration methods to quantitatively analyze FL-LIBS based on non-gated acquisition, because its quantitative analysis accuracy is very poor, and the forced calculated data are only recorded as experimental results.

[0063] The defects of the existing solutions are:

[0064] ① The standard sample calibration method cannot be applied in scenarios where there are no standard samples.

[0065] ②The calibration-free method is free from the limitation of samples and has research potential. However, currently, there is only a free calibration method based on the Boltzmann plane. The use of the free calibration method involves an important assumption: the particles in the plasma conform to the Boltzmann distribution, that is, they follow the local thermal equilibrium theory (LTE). In practice, only the plasma close to the transient state (<1 μs) can be approximately regarded as conforming to the LTE theory. Therefore, in order to collect the plasma spectrum within an extremely short observation window, an ICCD detector equipped with a high-speed shutter is usually used. Such devices are generally expensive. When used in FL-LIBS, it not only loses the advantage of low cost but also makes the system more complex because the detector needs to synchronize with a pulse output frequency above dozens of kHz.

[0066] ③Non-gated detectors, such as CCD and COMS, do not have a high-speed shutter, and their exposure time determines the minimum acquisition time, which is generally longer than the evolution time of the fiber laser-induced plasma. When using such detectors to collect the spectrum of the fiber laser-induced plasma, there must be a problem that the collected plasma temperature changes with time. Therefore, the FL-LIBS collected by the non-gated detector deviates from the LTE theory, making it difficult for the existing free calibration method to accurately calculate the plasma temperature and particle number density.

[0067] In traditional LIBS using a solid-state laser, there is a newly proposed calibration-free method for the non-gated acquisition strategy: the time-integrated free calibration method. Although this calibration model improves the accuracy of quantitative analysis in LIBS, it is only applicable to traditional LIBS and does not completely eliminate the need for gated devices.

[0068] ④The single-pulse energy of the fiber laser is low (<1 mJ). In order to obtain a high signal-to-noise ratio spectrum, multiple plasmas need to be accumulated. For the gated acquisition strategy, multiple plasmas can be accumulated by switching the shutter multiple times within one exposure time. For the non-gated acquisition strategy, the exposure time can be set much longer than the plasma generation period. This acquisition method of the non-gated detector is called continuous acquisition, and it is impossible to set a delay to avoid the continuous spectral background caused by bremsstrahlung at the initial stage of each plasma expansion. Therefore, the FL-LIBS collected by the non-gated acquisition contains an unavoidable bremsstrahlung background.

[0069] The implementation details of the technical solution of the embodiments of the present application are elaborated in detail below:

[0070] According to one aspect of the present application, a calibration-free method for FL-LIBS based on non-gated acquisition is provided. Figure 1 FIG. is a flowchart of the calibration-free method for FL-LIBS based on non-gated acquisition shown in the embodiments of the present application. The calibration-free method for FL-LIBS based on non-gated acquisition includes at least steps S1 to S5, which are introduced in detail as follows:

[0071] In step S1, a corrected spectrum is obtained, and a target reference element is determined according to the corrected spectrum. The corrected spectrum is obtained from the FL-LIBS spectrum collected by a non-gated acquisition system for a sample to be measured.

[0072] Specifically, the non-gated acquisition system includes an ultraviolet fused silica lens group, a C-T spectrometer, a CMOS detector (non-gated detector), and a data terminal. Here, the sample to be measured is taken as an example of TC4 titanium alloy. The working principle of the non-gated acquisition system is as follows: The ultraviolet fused silica lens group couples the light emitted by the laser-induced plasma into the optical fiber probe of the spectrometer. The coupling optical fiber transmits the optical signal to the CMOS detector for exposure, and then the data is transmitted to the terminal device (computer, embedded system, etc.).

[0073] Among them, the corrected spectrum is obtained through the following steps:

[0074] Before obtaining the corrected spectrum, the method further includes:

[0075] Obtain the FL-LIBS spectrum collected by the non-gated acquisition system for the sample to be measured;

[0076] Perform preprocessing of background removal, noise removal, and peak searching on the FL-LIBS spectrum to obtain a preprocessed measurement spectrum.

[0077] Determine the target spectral line with the maximum intensity among the spectral lines of the measurement spectrum;

[0078] Determine the corrected spectrum according to the spectral line parameters of the target spectral line and a preset correction coefficient.

[0079] Specifically, the corrected spectrum is the spectrum obtained by correcting the measurement spectrum collected and preprocessed by the non-gated acquisition system. From the corrected spectrum, the spectral lines and signal-to-noise ratios of each element can be intuitively seen.

[0080] The measurement spectrum is obtained by performing preprocessing operations such as noise removal, background removal, spectral line peak searching, intensity calibration, and intensity normalization on the obtained FL-LIBS spectrum. Finally, the corrected spectrum is obtained by combining the target spectral line in the measurement spectrum and a preset correction coefficient.

[0081] In step S2, a number of candidate vectors containing information on electron temperature and reference element particle number density are obtained, and the candidate simulation spectra corresponding to each candidate vector are determined. The candidate vectors correspond to the target reference element, and the values of the candidate vectors are randomly generated within a preset range.

[0082] Specifically, the core of the method proposed in the embodiments of the present application is that candidate vectors (i.e., electron temperature and particle number density) are randomly generated, and the similarity between the candidate simulated spectra and the corrected spectrum under different combinations of electron temperature and particle number density is judged, and the candidate vector corresponding to the candidate simulated spectrum that can make the similarity reach the highest is found as the final result (i.e., the optimal vector described in the present application).

[0083] Furthermore, since the non-gated acquisition system described in the present application is implemented by a non-gated detector, considering that the exposure time of the non-gated detector is greater than the evolution time of the plasma, the electron temperature changes with time during the exposure time. Therefore, let the initial temperature be T 0 , the power be a, and the electron temperature curve is represented by Equation (1). Let the parameter F 1 represent the particle number density of the target reference element. Among them, T 0 , a, and the temperature t form a single candidate vector.

[0084] T(t)=T 0 t a (1)

[0085] Determining the corrected spectrum according to the spectral parameters of the target spectral line and a preset correction coefficient can be specifically: determining the correction coefficient F through Equation (2) 2 . I obs (λ m ) is the reading of the strongest spectral line in the measured spectrum (which can be directly seen from the measured spectrum), and L(λ m ,T 10000K ) is the blackbody radiation intensity at the wavelength where the spectral line is located at 10000 K (Kelvin, a unit of temperature). Among them, t is the time, which is determined by the evolution life of the plasma. Considering that the single-pulse energy of the fiber laser is less than 1 mJ, the value of t is taken as 10 -6 .

[0086]

[0087] In an embodiment of the present application, determining the target reference element according to the corrected spectrum includes:

[0088] Selecting the elements that meet the preset conditions from each element of the corrected spectrum as the target reference element;

[0089] Among them, the preset condition is to have the largest number of observed spectral lines and exceed the preset signal-to-noise ratio threshold.

[0090] Because the more spectral lines there are, the more representative the overall spectrum is. If the matrix of the sample to be measured is known, then the matrix element is selected. Among them, the preset quantity threshold can be set according to actual needs, and the preset signal-to-noise ratio threshold can be set according to actual needs.

[0091] In step S3, each of the candidate vectors is iteratively updated according to a preset optimization algorithm, and the fitness of each of the candidate vectors is evaluated in a parallel evaluation manner in each iteration round. The parallel evaluation manner is to compare the similarity between each of the candidate simulated spectra and the corrected spectrum.

[0092] In an embodiment of the present application, the candidate simulated spectrum corresponding to a single candidate vector is obtained through the following steps:

[0093] Determine a first spectral line intensity parameter according to a preset first calculation formula, target parameters, and the candidate vector;

[0094] Perform time integration on the first spectral line intensity parameter to obtain the candidate simulated spectrum.

[0095] Specifically, the preset first calculation formula is Formula (3) in the embodiment of the present application. Through Formula (1), Formula (3), Formula (4), and Formula (8) in the embodiment of the present application, where Formula (4) expresses the spectral line theoretical intensity ι ignoring the self-absorption effect, which is reflected in Formula (3), so as to obtain the candidate simulated spectrum. The candidate vectors used above include electron temperature and particle number density, and the target parameters include the following parameters:

[0096] h is Planck's constant, k B is Boltzmann's constant, π is pi, c is the speed of light, m e is the electron mass, all of which are known numbers; λ is the central wavelength of the spectral line, A ki is the spontaneous emission coefficient, E k is the energy of the upper transition level, g k is the upper level degeneracy, the subscripts k and i represent the upper and lower transition levels of the spectral line λ, E ion,s is the first ionization energy of element s, U s (T) is the partition function of element s at electron temperature T, and the superscripts l and ll represent atomic lines and ionic lines. The above parameters are obtained by querying a preset database, such as obtained from the preset database, i.e., the NIST database.

[0097] In an embodiment of the present application, the preset range is obtained through the following steps:

[0098] The preset range is obtained through the following steps:

[0099] Determine a second spectral line intensity parameter according to the first calculation formula, the target parameters, and a preset electron temperature;

[0100] Determine a third spectral line intensity parameter according to a preset second calculation formula, the target parameters, and the preset electron temperature;

[0101] Determine a theoretical self-absorption coefficient curve related to the population density and the preset electron temperature according to the ratio of the second spectral line intensity parameter to the third spectral line intensity parameter;

[0102] Determine the value range of the population density according to the theoretical self-absorption coefficient curve, and use the value range as the preset range.

[0103] The second spectral line intensity parameter here is the theoretical intensity ι of the spectral line * , which is also calculated by Equation (3). However, different from the first spectral line intensity parameter, the temperature T used is different. In the first spectral line intensity parameter, the temperature T is the electron temperature in the candidate vector, while the temperature T in the second spectral line intensity parameter is the preset electron temperature, and the preset electron temperature can be set to 10000 K (Kelvin). That is to say, the theoretical self-absorption coefficient can be calculated through the preset electron temperature and the target parameter, without using the electron temperature in the candidate vector. That is to say, the obtained theoretical self-absorption coefficient curve is the relationship between the theoretical self-absorption coefficient and the population density (not specifically referring to the target reference element, but only saying that the target reference element is applicable to this function change curve).

[0104] The preset second calculation formula is the following formula (4), and the target parameter is the parameter used in formula (4). In fact, the target parameter used in formula (3) is the same as the target parameter used in formula (4). Simulate the population density F in the entire real number domain 1 There are difficulties, so evaluate F through the theoretical self-absorption coefficient 1 The approximate range: According to the spontaneous emission theory, Boltzmann distribution, Saha ionization equation, and blackbody radiation reference self-absorption correction method, the theoretical intensity ι of any spectral line * is expressed by Equation (3), and the parameter in Equation (3) is the first target parameter. The spectral line theoretical intensity ι ignoring the self-absorption effect is expressed by Equation (4). The parameter in Equation (4) is the second target parameter. The ionization degree χ is expressed by Equation (5); the factor R is expressed by Equation (6). The electron temperature T is assumed to be 10000 K in this step; N e is the electron density, which can be deduced by the Saha–Boltzmann method at a known temperature. Thus, the self-absorption coefficient curve SAC, expressed by Equation (7), is a function of F 1 , and F 1 is the only dependent variable of the self-absorption coefficient curve. The reasonable range of F 1 falls within the interval where 0.1 < SAC < 0.9 (i.e., the preset range).

[0105]

[0106] I sim = ∫ι * (t)dt(8)

[0107] I cor = F 2 I obs (9)

[0108] In step S4, according to the fitness of each of the candidate vectors at the final iteration round, determine the target simulated spectrum with the highest similarity to the corrected spectrum, and determine the candidate simulation vector corresponding to the target simulated spectrum as the optimal vector.

[0109] In an embodiment of the present application, the determining the target simulated spectrum with the highest similarity to the corrected spectrum includes:

[0110] According to a preset similarity comparison formula, determine the target simulated spectrum with the closest similarity to the corrected spectrum among each of the candidate simulated spectra.

[0111] Specifically, substitute equation (1) into the temperature in equation (3), and calculate the candidate simulated spectra corresponding to each candidate vector of the target reference element using equation (8). Calculate the corrected spectrum (i.e., the corrected spectrum described in the present application) using equation (9), where I obs represents the actually measured spectrum (i.e., the measured spectrum described in the present application). Obviously, the candidate vector [T sim , a, F 0 composed of the three unknown variables in the simulated spectrum I 1 is the data to be simulated. Evaluate these randomly generated data using the similarity between the candidate simulated spectrum and the corrected spectrum. And the work of generating, evaluating, iterating, and optimizing is handed over to the optimization algorithm (i.e., the preset optimization algorithm), and genetic algorithm or particle swarm optimization can be selected, as shown in the flowcharts of Figure 2 and Figure 3 .

[0112] Figure 2 is the specific logic flowchart of the FL-LIBS calibration-free method based on non-gated acquisition proposed in the embodiment of the present application, Figure 3 is the specific step diagram of the optimization algorithm. In Figure 2 , in the step of "determining the optimal vector through the optimization algorithm", the step logic can be specifically as shown in Figure 5 , that is to say, the specific steps of the optimization algorithm can be referred to the steps shown in Figure 3 , and the optimal vector can be finally determined through the respective steps of Figure 3 .

[0113] To improve the calculation speed, each iteration is handed over to PyTorch to calculate the fitness of all candidate vectors (corresponding to the preset similarity evaluation formula) in parallel. Finally, the target electron temperature and the F of the target reference element are obtained from the global optimal vector. 1 。

[0114] The preset similarity evaluation formula can be specifically:

[0115]

[0116] Among them, fitness is used to characterize the similarity between the candidate simulated spectrum and the corrected spectrum. The smaller the value of fitness, the higher the similarity between the two. u represents the number of spectral lines.

[0117] In step S5, the target electron temperature and the target particle number density of the target reference element are determined according to the optimal vector.

[0118] Specifically, after obtaining the optimal vector, the target electron temperature and the target particle number density of the target reference element in the optimal vector are naturally obtained.

[0119] In step S6, the particle number density of other elements in the sample to be measured except the target reference element is determined according to the target electron temperature.

[0120] Specifically, using the obtained target electron temperature, the F of other elements is calculated in turn 1 : Since substituting the target electron temperature into formula (8) leaves only F 1 one unknown. Therefore, the process of solving for the F that makes the candidate simulated spectrum of other elements closest to the corrected spectrum 1 is the problem of solving the minimum point of a unary function. That is to say, in the generated function variation curve, the abscissa is F 1 , the ordinate is fitness, then finding a point of F 1 in this function variation curve that can make the above fitness value the smallest can determine the particle number density of the current element, that is, the value of F 1 at this time represents the particle number density of the current element.

[0121] Because different elements to be measured have different spectral lines, the values of the spectral line intensities calculated by formula (8) and formula (9) are also different. Therefore, the value of fitness is different for different elements. In step S7, the target particle number density and the particle number densities of each of the other elements are normalized to obtain the concentration composition of the sample to be measured.

[0122] Finally, using the F of all elements obtained 1Calculate the concentration composition of the sample to be measured: F of all elements 1 The result of the normalization calculation is the concentration of each element in the sample to be measured.

[0123] The key point of this method lies in the innovative point that the unknown quantity is generated by simulation (that is, first assume a candidate vector, and then inversely deduce the optimal vector through the subsequent target simulated spectrum to obtain the target electron temperature. Finally, calculate the particle number density and concentration of other elements through the target electron temperature and particle number density, without obtaining the electron temperature through an ICCD detector as in the existing scheme). It should be noted that the expression of any candidate simulated spectrum in this application is represented by I sim to represent, I cor is the expression of the corrected spectrum of this application.

[0124] In summary, the embodiment of this application realizes the non-gated acquisition-based FL-LIBS calibration-free quantitative analysis. By obtaining a plurality of candidate vectors, that is, by introducing randomly generated unknown quantities, and iteratively updating each of the candidate vectors through a preset optimization algorithm. In each iteration round, the fitness of each of the candidate vectors is evaluated in a parallel evaluation manner. The parallel evaluation manner is to compare the similarity of each of the candidate simulated spectra with the corrected spectrum respectively, so as to determine the target simulated spectrum with the highest similarity to the corrected spectrum, and then obtain the optimal vector.

[0125] The target electron temperature can be determined through the obtained optimal vector, that is, the electron temperature of the plasma induced by the laser for the sample to be measured can be obtained, without the need for the prior art to determine the electron temperature through a costly gated detector. Further, through the determined target electron temperature, the particle number density of each element in the sample to be measured can be obtained, and then the concentration of each element can be obtained, so as to complete the calibration of the sample to be measured.

[0126] This application generates a number of unknown parameter groups, that is, candidate vectors, and uses an optimization algorithm to find the most matching candidate vector, thereby obtaining the electron temperature evolving with time. Without a high-speed gated detector, it provides a method for obtaining the time-resolved electron temperature required for time-integrated spectra, and at the same time can quickly and accurately realize the calibration-free quantitative analysis of FL-LIBS. This application can realize the application of this set of high-efficiency, low-maintenance-cost, and long-running LIBS system, achieving the purpose of cost reduction and efficiency increase, and providing a new improvement scheme for on-line monitoring of industrial processing.

[0127] According to one aspect of the embodiments of this application, a non-gated acquisition-based FL-LIBS calibration-free device 300 is proposed. Figure 4Schematic diagram of the FL-LIBS calibration-free device 300 based on non-gated acquisition proposed in the embodiments of this application. The system 300 includes: a first acquisition unit 301, a second acquisition unit 302, an iteration unit 303, a first determination unit 304, a second determination unit 305, a third determination unit 306, and a concentration calculation unit 307.

[0128] The first acquisition unit 301 is configured to acquire a corrected spectrum and determine a target reference element according to the corrected spectrum. The corrected spectrum is obtained from the FL-LIBS spectrum acquired by the non-gated acquisition system for the sample to be measured.

[0129] The second acquisition unit 302 is configured to acquire a plurality of candidate vectors containing electron temperature and reference element particle number density information, and determine candidate simulation spectra corresponding to each of the candidate vectors. The candidate vectors correspond to the target reference element, and the values of the candidate vectors are randomly generated within a preset range.

[0130] The iteration unit 303 is configured to iteratively update each of the candidate vectors according to a preset optimization algorithm. In each iteration round, the fitness of each of the candidate vectors is evaluated in a parallel evaluation manner. The parallel evaluation manner is to compare the similarity between each of the candidate simulation spectra and the corrected spectrum.

[0131] The first determination unit 304 is configured to determine a target simulation spectrum with the highest similarity to the corrected spectrum according to the fitness of each of the candidate vectors in the final iteration round, and determine the candidate simulation vector corresponding to the target simulation spectrum as the optimal vector.

[0132] The second determination unit 305 is configured to determine a target electron temperature and a target particle number density of the target reference element according to the optimal vector.

[0133] The third determination unit 306 is configured to determine the particle number density of other elements in the sample to be measured except the target reference element according to the target electron temperature.

[0134] The concentration calculation unit 307 is configured to perform a normalization calculation on the target particle number density and the particle number densities of each of the other elements to obtain the concentration composition of the sample to be measured.

[0135] As another aspect, the present application also provides a computer-readable storage medium, on which a program product is stored that can implement the method provided above in this specification. In some possible implementation manners, each aspect of the present application can also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary implementation manners of the present application described in the "Embodiment Method" section above in this specification.

[0136] The program product for implementing the above method according to the implementation manner of the present application can be a portable compact disc read-only memory (CD-ROM) and includes program code, and can run on a terminal device, such as a personal computer. However, the program product of the present application is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device.

[0137] The program product can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0138] The computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the readable program code. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable signal medium can also be any readable medium other than the readable storage medium, and this readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0139] The program code contained on the readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0140] The program code for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0141] Reference will now be made to Figure 5 describe the electronic device 400 according to this embodiment of the present application. Figure 5 The electronic device 400 shown is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0142] As Figure 5 shown, the electronic device 400 is presented in the form of a general-purpose computing device. The components of the electronic device 400 may include, but are not limited to: at least one of the above-mentioned processing units 410, at least one of the above-mentioned storage units 420, and a bus 430 connecting different system components (including the storage unit 420 and the processing unit 410).

[0143] Among them, the storage unit stores program code, and the program code can be executed by the processing unit 410, so that the processing unit 410 executes the steps according to various exemplary embodiments of the present application described in the "Embodiment Method" section of this specification.

[0144] The storage unit 420 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 421 and / or a cache storage unit 422, and may further include a read-only storage unit (ROM) 423.

[0145] The storage unit 420 may further include a program / utility 424 having a set (at least one) of program modules 425. Such program modules 425 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. The implementation of a network environment may be included in each or some combination of these examples.

[0146] The bus 430 can represent one or more of several types of bus structures, including a memory bus or a memory control node, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of the various bus structures.

[0147] The electronic device 400 can also communicate with one or more external devices 1200 (such as a keyboard, a pointing device, a Bluetooth device, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 400, and / or communicate with any device that enables the electronic device 400 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication can be carried out through the input / output (I / O) interface 450. Moreover, the electronic device 400 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 460. As shown in the figure, the network adapter 460 communicates with other modules of the electronic device 400 through the bus 430. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0148] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by the way of software in combination with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product, and the software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0149] In addition, the above drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, rather than for limiting purposes. It is easy to understand that the processes shown in the above drawings do not indicate or limit the time sequence of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously in, for example, multiple modules.

[0150] It should be understood that the present application is not limited to the exact structures that have been described and shown in the drawings above, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A FL-LIBS calibration-free method based on non-gated acquisition, characterized in that: The method comprises: Acquire a corrected spectrum, and determine a target reference element according to the corrected spectrum, wherein the corrected spectrum is obtained according to an FL-LIBS spectrum collected by a non-gated acquisition system for a sample to be tested; Acquire a plurality of candidate vectors containing information on electron temperature and reference element particle number density, and determine a candidate simulation spectrum corresponding to each of the candidate vectors, wherein the candidate vectors correspond to the target reference element, and the values ​​of the candidate vectors are randomly generated within a preset range; Iteratively updating each candidate vector according to a preset optimization algorithm, evaluating the fitness of each candidate vector in a parallel evaluation manner in each iteration round, wherein the parallel evaluation manner is to compare the similarity of each candidate simulated spectrum with the corrected spectrum respectively; Determine the target simulated spectrum with the highest similarity to the corrected spectrum according to the fitness of each candidate vector in the final iteration round, and determine the candidate simulated vector corresponding to the target simulated spectrum as the optimal vector; determining a target electron temperature and a target particle number density of the target reference element according to the optimal vector; Determine the particle number density of other elements in the sample to be tested except the target reference element according to the target electron temperature; The target particle number density and the particle number density of each of the other elements are normalized and calculated to obtain the concentration composition of the sample to be tested.

2. The FL-LIBS calibration-free method based on non-gated acquisition according to claim 1, characterized in that: Before obtaining the corrected spectrum, the method further comprises: Acquiring a FL-LIBS spectrum collected by the non-gated acquisition system for the sample to be tested; The FL-LIBS spectrum is preprocessed by background removal, noise removal, and peak search to obtain a preprocessed measurement spectrum.

3. The FL-LIBS calibration-free method based on non-gated acquisition according to claim 2, characterized in that: The modified spectrum is obtained by the following steps: Determining a target spectral line with the largest intensity among the spectral lines of the measured spectrum; The corrected spectrum is determined according to the spectral line parameters of the target spectral line and a preset correction coefficient.

4. The FL-LIBS calibration-free method based on non-gated acquisition according to claim 3, characterized in that: The step of determining a target reference element according to the corrected spectrum comprises: Selecting an element that meets a preset condition from among the elements of the corrected spectrum as the target reference element; The preset condition is to have the largest number of observed spectral lines exceeding a preset signal-to-noise ratio threshold.

5. The FL-LIBS calibration-free method based on non-gated acquisition according to claim 4, characterized in that: The candidate simulated spectrum corresponding to a single candidate vector is obtained by the following steps: Determine a first spectral line intensity parameter according to a preset first calculation formula, a target parameter and the candidate vector; The first spectral line intensity parameter is time-integrated to obtain the candidate simulated spectrum.

6. The FL-LIBS calibration-free method based on non-gated acquisition according to claim 5, characterized in that: The preset range is obtained by the following steps: Determine a second spectral line intensity parameter according to the first calculation formula, the target parameter and a preset electron temperature; Determine a third spectral line intensity parameter according to a preset second calculation formula, the target parameter and the preset electron temperature; Determining a theoretical self-absorption coefficient curve related to the particle number density and the preset electron temperature according to a ratio of the second spectral line intensity parameter to the third spectral line intensity parameter; The value range of the particle number density is determined according to the theoretical self-absorption coefficient curve, and the value range is used as the preset range.

7. A FL-LIBS calibration-free device based on non-gated acquisition, characterized in that: The device comprises: A first acquisition unit is used to acquire a corrected spectrum and determine a target reference element according to the corrected spectrum, wherein the corrected spectrum is obtained according to an FL-LIBS spectrum acquired by a non-gated acquisition system for a sample to be tested; A second acquisition unit is used to acquire a plurality of candidate vectors containing information on electron temperature and reference element particle number density, and determine a candidate simulation spectrum corresponding to each of the candidate vectors, wherein the candidate vectors correspond to the target reference element, and the values ​​of the candidate vectors are randomly generated within a preset range; An iteration unit, used for iteratively updating each candidate vector according to a preset optimization algorithm, wherein each iteration round evaluates the fitness of each candidate vector in a parallel evaluation manner, wherein the parallel evaluation manner is to compare the similarity of each candidate simulated spectrum with the corrected spectrum respectively; A first determination unit is used to determine the target simulated spectrum with the highest similarity to the corrected spectrum according to the fitness of each candidate vector in the final iteration round, and determine the candidate simulated vector corresponding to the target simulated spectrum as the optimal vector; a second determination unit, configured to determine a target electron temperature and a target particle number density of the target reference element according to the optimal vector; A third determination unit, configured to determine the particle number density of other elements in the sample to be tested except the target reference element according to the target electron temperature; The concentration calculation unit is used to perform normalized calculation on the target particle number density and the particle number density of each of the other elements to obtain the concentration composition of the sample to be tested.

8. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the FL-LIBS calibration-free method based on non-gated acquisition according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the FL-LIBS calibration-free method based on non-gated acquisition according to any one of claims 1 to 6 is implemented.

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