Inlet furnace material detection method and device, electronic equipment and storage medium

Abstract

The invention provides a furnace charge detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an emission spectrum of a standard sample; according to the emission spectrum of the standard sample and the element types and components of the standard sample, a plurality of calibration models are established, and each calibration model corresponds to one element; evaluating the plurality of calibration models to obtain an optimal calibration model corresponding to each element; and according to the optimal calibration model corresponding to each element, constructing a uniformity evaluation model to evaluate the uniformity of the furnace charge. According to the method, a plurality of standard samples with the same element types and different components are arranged, emission spectrums of the standard samples are processed to construct a plurality of calibration models, then the calibration models are evaluated to determine an optimal model suitable for a current charging material, and finally, a uniformity evaluation model is constructed according to the optimal model, so that the uniformity of the charging material is evaluated. In this way, it can be ensured that uniformity evaluation can be accurately carried out on the charging material containing any element type.

Description

Technical Field

[0001] The present invention relates to the technical field of material detection, and in particular to a method and device for detecting incoming furnace materials, electronic equipment, and a storage medium. Background Art

[0002] In the metallurgical industry, the metal production process usually consists of multiple links, and each step should be monitored and controlled to ensure that the metal products meet the quality requirements. Among them, the mixing process of the incoming charge is at the front end of the process production process, which affects the quality consistency of the final product. Therefore, how to monitor the mixing process of the incoming charge and determine the mixing endpoint is crucial to the entire production process.

[0003] The quality of material mixing directly determines the quality of the product, so it is very important to mix materials efficiently. Since the movement of powders during the mixing process is very complex, researchers currently cannot fully understand the actual movement laws of particles when mixing powder materials. How to correctly evaluate the mixing effect of materials has always been a hot topic and difficulty in research.

[0004] The evaluation of the mixing effect of powder materials requires a scientific method to quantitatively analyze the mixing effect and accurately determine the mixing uniformity. At present, the metallurgical industry usually uses offline sampling and determination, and uses chemical, near-infrared spectroscopy, X-ray fluorescence spectroscopy and other analytical methods to determine the composition of the sample to evaluate the content uniformity of the mixture. Traditional methods are time-consuming and labor-intensive, interfere with the mixing process, and even destroy the mixing balance, resulting in errors. In addition, such methods are prone to sample damage and increase the loss of raw materials.

[0005] At present, the methods for evaluating mixing effects mainly include: chemical analysis method, tracer method and instrumental analysis method. Among them, instrumental analysis method is increasingly used. Instrumental analysis method mainly includes digital image analysis method, near-infrared spectroscopy, X-ray spectroscopy, etc. These methods have their own advantages and disadvantages.

[0006] Nowadays, more and more people are beginning to use laser induced breakdown spectroscopy (LIBS) technology to detect material composition. This technology is widely used due to its characteristics of rapidity, minimal damage, remote sensing, and simultaneous detection of multiple elements. However, the detection effect of LIBS technology is more dependent on the construction of the model and its applicability is poor, which leads to inaccurate detection of the uniformity of the incoming charge. Summary of the invention

[0007] In view of the above defects of the prior art, the present invention provides a method and device for detecting incoming charge, an electronic device, and a storage medium to solve the technical problem of inaccurate uniformity detection of incoming charge.

[0008] To achieve the above-mentioned purpose and other related purposes, the present invention provides a method for detecting incoming charge, comprising: obtaining an emission spectrum of a standard sample, wherein the standard sample and the incoming charge to be detected have the same element type but different elemental composition; establishing multiple calibration models based on the emission spectrum of the standard sample, and the element type and composition of the standard sample, each calibration model corresponding to an element; evaluating the multiple calibration models to obtain an optimal calibration model corresponding to each element; and constructing a uniformity evaluation model based on the optimal calibration model corresponding to each element to evaluate the uniformity of the incoming charge.

[0009] In one embodiment of the present invention, multiple calibration models are established based on the emission spectrum of the standard sample, and the element type and composition of the standard sample, including: extracting the first characteristic spectrum line of the standard sample based on the emission spectrum of the standard sample; selecting the spectrum lines corresponding to all elements in the standard sample from the first characteristic spectrum line to obtain the second characteristic spectrum line corresponding to the standard sample; screening out the second characteristic spectrum lines existing in all standard samples to obtain the third characteristic spectrum line; classifying the third characteristic spectrum lines according to the element type to obtain one or more third characteristic spectrum lines corresponding to each element; and establishing multiple calibration models based on the one or more third characteristic spectrum lines corresponding to each element and the element composition of the standard sample.

[0010] In one embodiment of the present invention, extracting the first characteristic spectral line of the standard sample according to the emission spectrum of the standard sample includes: preprocessing the emission spectrum of the standard sample to obtain a preprocessed emission spectrum; extracting the first characteristic spectral line of the standard sample according to the preprocessed emission spectrum.

[0011] In one embodiment of the present invention, the emission spectrum of the standard sample is preprocessed to obtain a preprocessed emission spectrum, including: performing spectral averaging, background subtraction, intensity normalization and spectral decomposition processing on the emission spectrum of the standard sample to obtain a preprocessed emission spectrum.

[0012] In one embodiment of the present invention, in the step of establishing a plurality of the calibration models, the calibration method adopted is a spectral line intensity calibration method, a single spectral line internal standard reference method, or a multi-spectral line internal standard reference method.

[0013] In one embodiment of the present invention, in the step of establishing a plurality of calibration models, the calibration model used is a linear model, a quadratic function type, or a logarithmic function type.

[0014] In one embodiment of the present invention, multiple calibration models are evaluated to obtain the optimal calibration model corresponding to each element, including: using one or more indicators of mean square error, root mean square error, mean absolute error and determination coefficient to evaluate multiple calibration models to obtain the optimal calibration model corresponding to each element.

[0015] To achieve the above-mentioned purpose and other related purposes, the present invention also provides a device for detecting incoming charge based on laser induced breakdown spectroscopy technology, comprising: a data acquisition unit, used to acquire the emission spectrum of a standard sample, wherein the standard sample has the same element type as the incoming charge to be detected but different elemental composition; a first modeling unit, used to establish multiple calibration models according to the emission spectrum of the standard sample and the element type and composition of the standard sample, each calibration model corresponding to an element; an evaluation unit, used to evaluate the multiple calibration models to obtain the optimal calibration model corresponding to each element; and a second modeling unit, used to construct a uniformity evaluation model according to the optimal calibration model corresponding to each element to evaluate the uniformity of the incoming charge.

[0016] To achieve the above-mentioned purpose and other related purposes, the present invention also provides an electronic device, including a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to implement a method provided in any one of the above embodiments.

[0017] To achieve the above-mentioned object and other related objects, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to enable a computer to execute the method provided in any one of the above-mentioned embodiments.

[0018] Beneficial effects of the present invention: The present invention proposes a method and device for detecting incoming charge, an electronic device, and a storage medium. The method sets a plurality of standard samples with the same element type and different compositions, processes the emission spectra of the standard samples to construct a plurality of calibration models, and then evaluates these calibration models to determine the optimal model suitable for the current incoming charge. Finally, a uniformity evaluation model is constructed based on the optimal model, thereby ensuring that the uniformity of incoming charge containing any element type can be accurately evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A flow chart of a method for detecting incoming charge provided by an embodiment of the present invention;

[0021] Figure 2 A detailed flow chart of step S200 provided in one embodiment of the present invention;

[0022] Figure 3 A detailed flow chart of step S210 provided for one embodiment of the present invention;

[0023] Figure 4 Another flow chart of a method for detecting incoming charge provided by an embodiment of the present invention;

[0024] Figure 5 A schematic diagram of a furnace charge detection device provided by an embodiment of the present invention;

[0025] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0026] Explanation of the reference numerals: 101, data acquisition unit; 102, first modeling unit; 103, evaluation unit; 104, second modeling unit; 201, processor; 202, memory. DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present invention through specific specific embodiments, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. It should be noted that the following embodiments and the features in the embodiments can be combined with each other without conflict. In addition to the specific methods, equipment, and materials used in the embodiments, according to the technical personnel in this technical field's grasp of the prior art and the records of the present invention, any methods, equipment, and materials of the prior art that are similar or equivalent to the methods, equipment, and materials described in the embodiments of the present invention can also be used to implement the present invention.

[0028] It should be understood that the terms used in the embodiments of the present invention are for describing specific embodiments rather than for limiting the scope of protection of the present invention. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those generally understood by those skilled in the art.

[0029] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In some of the embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0030] The flowchart and block diagram in the accompanying drawings illustrate the system architecture, functions and operations that may be implemented according to the methods and computer program products of various embodiments disclosed in the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of the boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0031] See also Figure 1 , Figure 1 A method for detecting incoming materials provided in one embodiment of the present invention includes steps S100 to S400.

[0032] Step S100, obtaining the emission spectrum of the standard sample, wherein the standard sample and the charge to be detected have the same element type but different element composition. In this step, based on the laser induced breakdown spectroscopy technology (LIBS for short), a pulsed laser is used to excite plasma on the surface of the standard sample, and the emission spectrum of the standard sample is obtained through the spectral wavelength and intensity information of the plasma emission. At the same time, the element type and composition of the standard sample itself are known, so the emission spectrum of the standard sample with known element type and composition can be obtained through this step.

[0033] When configuring the standard sample, the elemental composition can be divided into multiple gradients, and the composition of the elements in the charge must be included. For example, if the copper content in the charge is 40%, then the copper content in the standard sample can be 30%, 35%, 40%, 45%, or 50%.

[0034] Step S200: Establish multiple calibration models according to the emission spectrum of the standard sample, and the element type and composition of the standard sample, each calibration model corresponds to one element. The element type and composition of the standard sample are known, and its emission spectrum is also known, so the calibration model can be constructed, and when constructing the calibration model, a calibration model is constructed for each element.

[0035] See also Figure 2 In a specific embodiment of the present invention, step S200 includes steps S210 to S250.

[0036] Step S210, extract the first characteristic spectrum line of the standard sample according to the emission spectrum of the standard sample. Characteristic spectrum line refers to a series of specific dark lines or bright lines presented on the spectrometer by the light after passing through the material due to the different absorption, emission or scattering degree of the material to light of different wavelengths in spectroscopy, which are displayed as troughs and peaks in the spectrum curve. These dark lines or bright lines are called atomic characteristic spectrum lines, and their generation principle is mainly related to the internal structure of the atom, that is, related to the type of element. In this step, all the first characteristic spectrum lines in each standard sample are obtained. Some of these first characteristic spectrum lines are related to the element, and some are noise caused by fluctuations in the detection environment, detection errors, etc.

[0037] See also Figure 3 In a specific embodiment of the present invention, step S210 includes: S211, preprocessing the emission spectrum of the standard sample to obtain the preprocessed emission spectrum; S212, extracting the first characteristic spectrum line of the standard sample according to the preprocessed emission spectrum. In this embodiment, the preprocessing can be, for example, spectrum averaging, background subtraction, intensity normalization, spectrum decomposition and other operations, and the purpose of these preprocessing is to be able to extract the first characteristic spectrum line more conveniently and quickly.

[0038] Step S220, select the spectral lines corresponding to all elements in the standard sample from the first characteristic spectral lines, and obtain the second characteristic spectral lines corresponding to the standard sample. Since the types of elements in the standard sample are known, the wavelengths corresponding to these elements can be obtained based on the existing recognized spectral line parameter database. The spectral line parameter database refers to a database that stores a large amount of atomic or molecular spectral line parameters. These parameters include key information such as wavelength, energy level, transition probability, etc. The wavelength corresponding to the element is obtained by querying the database. Since the types of elements in the standard sample are determined, the first characteristic spectral lines can be screened based on this to obtain the second characteristic spectral lines corresponding to these elements in the standard sample. The second characteristic spectral line can be recorded as (λ ij ,I ij ), where the subscript i represents the serial number of the standard sample. Assuming there are N standard samples, then i = 1, 2, ..., N. The subscript j represents the jth second characteristic spectrum line in the standard sample. For different standard samples, the maximum value of j may be different; λ ij and I ij That is, the wavelength and intensity of the jth second characteristic spectral line of the i-th standard sample.

[0039] Step S230, filter out the second characteristic spectral line that exists in all standard samples to obtain the third characteristic spectral line. For some scenes with low components, or when the characteristic spectral lines of elements are not obvious, the calibration model constructed based on these characteristic spectral lines will naturally not work well. Therefore, in this step, the second characteristic spectral line that exists in all standard samples is firstly filtered out. ij ,I ij) as an example, the third characteristic spectrum obtained after screening can be recorded as (λ' ij ,I' ij ), after screening, the number of the third characteristic spectral lines in each standard sample is the same, that is, the maximum value of the subscript j is the same.

[0040] Step S240: Classify the third characteristic spectral lines by element type to obtain one or more third characteristic spectral lines corresponding to each element. This step is equivalent to classifying the third characteristic spectral lines (λ' ij ,I' ij ) are grouped, each group of the third characteristic spectral lines corresponds to an element type, and the grouped characteristic spectral lines can be recorded as Where C is the element type.

[0041] Step S250: Establish multiple calibration models based on one or more third characteristic spectral lines corresponding to each element and the element composition of the standard sample. Assume that the element composition of the standard sample is W i c Here, i is the standard sample number, and C is the element type. Specifically, here is the characteristic spectrum after grouping. And ingredient information i c To build a calibration model.

[0042] In a specific embodiment of the present invention, in the step of establishing multiple calibration models, the calibration method adopted is the spectral line intensity calibration method or the single spectral line internal standard reference method or the multi-spectral line internal standard reference method. The spectral line intensity calibration method is a quantitative analysis method commonly used in spectral analysis, which determines the concentration of the element by measuring the spectral line intensity of the analyzed element in the sample spectrum. The single spectral line internal standard reference method and the multi-spectral line internal standard reference method both belong to the internal standard reference method. The internal standard method selects an internal standard element that is close to the characteristics of the analyzed element, and uses the spectral line intensity ratio of the analyzed element and the internal standard element to draw a standard curve with the concentration of the element to be measured. The difference is that the single spectral line internal standard reference method is equivalent to establishing a calibration model for each spectral line, while the multi-spectral line internal standard reference method establishes a calibration model according to multiple spectral lines corresponding to the element.

[0043] In a specific embodiment of the present invention, in the step of establishing multiple calibration models, the calibration model used is a linear model or a quadratic function type or a logarithmic function type. The linear model assumes that there is a linear relationship between the spectral signal and the sample concentration. This model is simple and intuitive, and is suitable for situations where the relationship between the signal and the concentration is approximately linear. The linear model works well when processing simple or less noisy data, but may not be accurate enough when facing complex samples or nonlinear relationships. The quadratic function calibration model takes into account the nonlinear relationship between the spectral signal and the sample concentration. This model is suitable for situations where the relationship between the signal and the concentration presents a parabolic change; the quadratic function model can provide a more complex relationship description than the linear model, so it is more suitable when processing data with obvious nonlinear characteristics. The logarithmic function calibration model uses a logarithmic function to describe the relationship between the spectral signal and the sample concentration. This model is suitable for situations where the rate of increase of the signal gradually slows down as the concentration increases, which is common in certain chemical and biological analyses. The logarithmic function model can handle nonlinear relationships where the amplitude of the signal decreases as the concentration increases.

[0044] When establishing a calibration model, for the same spectral line of the same element, different methods can be used to establish a calibration model respectively, and the optimal calibration model can be selected through evaluation later.

[0045] Step S300, evaluate multiple calibration models to obtain the optimal calibration model corresponding to each element. After the evaluation, the calibration model that meets the conditions can be added to the calibration model database, and the corresponding characteristic spectrum or characteristic spectrum combination can be added to the characteristic spectrum database; for those that do not meet the evaluation requirements, the calibration model and the corresponding characteristic spectrum or characteristic spectrum combination are abandoned.

[0046] In a specific embodiment of the present invention, multiple calibration models are evaluated to obtain the optimal calibration model corresponding to each element, including: using one or more indicators of mean square error, root mean square error, mean absolute error and determination coefficient to evaluate multiple calibration models to obtain the optimal calibration model corresponding to each element.

[0047] In this embodiment, some common evaluation indicators are listed, such as mean square error, root mean square error, mean absolute error and determination coefficient. In addition, other evaluation indicators can be introduced. In addition, when performing the evaluation, an appropriate number of evaluation indicators can be selected to ensure that the best calibration model is finally selected.

[0048] Step S400: construct a uniformity evaluation model based on the optimal calibration model corresponding to each element to evaluate the uniformity of the incoming charge. With the optimal calibration model, the composition of each element in the incoming charge can be calculated based on these models. By analyzing the difference in element composition at different positions of the incoming charge, the uniformity can be obtained. These calculation processes together with the optimal calibration model can be packaged into a uniformity evaluation model.

[0049] It should be noted that the steps of the above methods are divided only for the purpose of clear description. When implementing, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they contain the same logical relationship, they are all within the protection scope of this patent; adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of the algorithm and process are all within the protection scope of this patent. Figure 4 The figure shows another flow chart of the charge detection method. Although the steps are different from those described in the above embodiment, the overall logic is the same. It should be noted that: Figure 4 The analysis lines in are the characteristic spectral lines mentioned above.

[0050] See also Figure 5 , Figure 5 A device for detecting incoming materials based on laser induced breakdown spectroscopy technology provided in one embodiment of the present invention comprises a data acquisition unit 101, a first modeling unit 102, an evaluation unit 103 and a second modeling unit 104. The data acquisition unit 101 is used to acquire the emission spectrum of a standard sample, the standard sample and the incoming materials to be detected have the same element type but different element composition; the first modeling unit 102 is used to establish multiple calibration models according to the emission spectrum of the standard sample, and the element type and composition of the standard sample, each calibration model corresponding to one element; the evaluation unit 103 is used to evaluate the multiple calibration models to obtain the optimal calibration model corresponding to each element; the second modeling unit 104 is used to construct a uniformity evaluation model according to the optimal calibration model corresponding to each element, so as to evaluate the uniformity of the incoming materials.

[0051] It should be noted that the charge detection device of the present embodiment is a device corresponding to the charge detection method described above, and the functional modules in the charge detection device correspond to the corresponding steps in the charge detection method. The charge detection device of the present embodiment can be implemented in coordination with the charge detection method, that is, in the absence of conflict, the relevant technical details mentioned in the charge detection method described above can also be applied to the charge detection device of the present embodiment.

[0052] See also Figure 6 , Figure 6An electronic device provided for one embodiment of the present invention includes a processor 201, a memory 202 and a communication bus; the communication bus is used to connect the processor 201 and the memory 202; the processor 201 is used to execute the computer program stored in the memory 202 to implement the above-mentioned charge detection method.

[0053] The above-mentioned electronic device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0054] The electronic device mentioned above can be any electronic product that can perform human-computer interaction with a user, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive network television (IPTV), a smart wearable device, etc.

[0055] The electronic device may also include a network device and / or a user device, wherein the network device includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud consisting of a large number of hosts or network servers based on cloud computing.

[0056] The network where the above electronic devices are located includes but is not limited to the Internet, wide area network, metropolitan area network, local area network, virtual private network (VPN), etc.

[0057] The above-mentioned processor can be, for example, a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components; the above-mentioned memory may include random access memory (RAM), and may also include non-volatile memory (Non-volatile Memory), such as at least one disk storage.

[0058] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is used to enable a computer to execute the above-mentioned charge detection method.

[0059] In general, the charge detection method of the present invention reduces the error caused by human screening, is easy to implement, fast and convenient, and has strong versatility compared to conventional detection methods. For characteristic spectral lines that do not meet the threshold of the calibration model, the reason may be the spectral line identification error in the previous step, or it may be caused by factors such as self-absorption and severe interference.

[0060] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for detecting incoming charge, characterized in that: include: Acquire an emission spectrum of a standard sample, wherein the standard sample has the same element type as the charge to be detected but has a different elemental composition; Establishing a plurality of calibration models according to the emission spectrum of the standard sample and the element type and composition of the standard sample, each calibration model corresponding to one element; Evaluate the plurality of calibration models to obtain an optimal calibration model corresponding to each element; According to the optimal calibration model corresponding to each element, a uniformity evaluation model is constructed to evaluate the uniformity of the charge.

2. The method for detecting incoming charge according to claim 1, characterized in that: According to the emission spectrum of the standard sample, and the element type and composition of the standard sample, multiple calibration models are established, including: Extracting a first characteristic spectrum line of the standard sample according to the emission spectrum of the standard sample; Selecting the spectral lines corresponding to all elements in the standard sample from the first characteristic spectral lines to obtain the second characteristic spectral lines corresponding to the standard sample; The second characteristic spectral line existing in all standard samples is screened out to obtain the third characteristic spectral line; Classifying the third characteristic spectral lines according to element types to obtain one or more third characteristic spectral lines corresponding to each element; A plurality of calibration models are established according to one or more third characteristic spectral lines corresponding to each element and the elemental composition of the standard sample.

3. The method for detecting incoming charge according to claim 2, characterized in that: Extracting a first characteristic spectrum line of the standard sample according to the emission spectrum of the standard sample comprises: Preprocessing the emission spectrum of the standard sample to obtain a preprocessed emission spectrum; According to the preprocessed emission spectrum, a first characteristic spectrum line of the standard sample is extracted.

4. The method for detecting incoming charge according to claim 3, characterized in that: Preprocessing the emission spectrum of the standard sample to obtain a preprocessed emission spectrum includes: The emission spectrum of the standard sample is subjected to spectrum averaging, background subtraction, intensity normalization and spectrum decomposition processing to obtain a pre-processed emission spectrum.

5. The method for detecting incoming charge according to claim 2, characterized in that: In the step of establishing a plurality of the calibration models, the calibration method adopted is a spectral line intensity calibration method, a single spectral line internal standard reference method, or a multi-spectral line internal standard reference method.

6. The method for detecting incoming charge according to claim 2, characterized in that: In the step of establishing a plurality of calibration models, the calibration model adopted is a linear model, a quadratic function type, or a logarithmic function type.

7. The method for detecting incoming charge according to claim 1, characterized in that: Evaluate the multiple calibration models to obtain the optimal calibration model corresponding to each element, including: The plurality of calibration models are evaluated using one or more indicators of mean square error, root mean square error, mean absolute error and determination coefficient to obtain an optimal calibration model corresponding to each element.

8. A device for detecting incoming charge based on laser induced breakdown spectroscopy technology, characterized in that: include: A data acquisition unit, used to acquire an emission spectrum of a standard sample, wherein the standard sample has the same element type as the charge to be detected but has a different elemental composition; A first modeling unit is used to establish a plurality of calibration models according to the emission spectrum of the standard sample and the element type and composition of the standard sample, each calibration model corresponding to one element; An evaluation unit, used to evaluate the multiple calibration models to obtain the optimal calibration model corresponding to each element; The second modeling unit is used to construct a uniformity evaluation model according to the optimal calibration model corresponding to each element to evaluate the uniformity of the charge.

9. An electronic device, characterized in that: The system comprises a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is used to make a computer execute the method according to any one of claims 1 to 7.

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