A method and system for detecting ore grade and elements

Abstract

The invention discloses an ore grade and element detection method and system, and relates to the technical field of ore detection. The ore grade and element detection method determines whether the ore sample can be subjected to laser induced breakdown. If the ore sample can be subjected to laser induced breakdown, the ore sample is subjected to laser induced breakdown according to the set laser induced breakdown parameters to obtain the ore sample spectrum data; feature extraction is performed on the obtained ore sample spectrum data to obtain element matching data and element content matching data, and the element type and element content are determined; the content ratio of the element type is determined based on the element content, and the content ratio of the element type is compared with the ore grade corresponding to each content ratio of the element type stored in the database, and the ore grade corresponding to the content ratio of the element type is determined, which solves the problem that most of the existing ore grade and element detection methods are chemical analysis methods, which are time-consuming, costly and harmful to the environment.

Description

Technical Field

[0001] The present invention relates to the technical field of ore detection, and in particular to a method and system for detecting ore grade and elements. Background Art

[0002] In the whole process of mineral resource development, scientific and orderly mining is implemented, and the disturbance of the ecological environment in the mining area and the surrounding area is controlled within a controllable range, so as to realize the ecological environment, scientific mining methods, efficient resource utilization, digital management information and harmonious mining community. Intelligent perception and identification of ore properties are the basis for realizing the intelligent production process of mineral processing in the field of intelligent mining. The core development direction of intelligent mineral processing: ore property identification, intelligent flotation equipment and genetic mineral processing technology. The grade, particle size and crushing characteristics of valuable elements in ore are the three most important basic properties among the various physical and chemical properties of ore. These three basic properties determine the theoretical basis and process measures applicable to the separation of useful components and the rational use or comprehensive use of products. In actual production, the fluctuations of the three directly affect the stability and economic benefits of mineral processing operations, which is of great significance to the efficient and intelligent control of mineral processing production.

[0003] Among them, ore grade refers to the content of useful components or useful minerals in ore per unit volume or unit weight. Ore grade is the main criterion for determining ore and non-ore, and for identifying ore grade. At present, an X-ray generator is usually installed above the belt that transports ore, and a high- and low-energy detector is installed below the belt. The X-ray generator is used to perform X-ray irradiation detection on the lump ore on the transport belt, and the high- and low-energy transmission grayscale images of the ore are collected by the high- and low-energy detectors. Then, the high- and low-energy transmission grayscale images are processed in real time to detect the content information of the target elements in the lump ore, thereby obtaining the ore grade.

[0004] However, most of the existing methods for detecting ore grade and elements are chemical analysis methods, which are time-consuming, costly and harmful to the environment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for detecting ore grade and elements, which solves the problem that most of the existing ore grade and element detection methods are chemical analysis methods, which are time-consuming, costly and harmful to the environment.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an ore grade and element detection method, comprising the following steps: determining whether an ore sample can be subjected to laser induced breakdown, replacing the ore sample if it cannot be subjected to laser induced breakdown, and subjecting the ore sample to laser induced breakdown according to set laser induced breakdown parameters if it can be subjected to laser induced breakdown, wherein the set laser induced breakdown parameters include setting pulse width, setting focus depth and setting laser energy; acquiring ore sample spectral data based on plasma generated after laser induced breakdown of the ore sample; performing feature extraction on the acquired ore sample spectral data to obtain element matching data and element content matching data, wherein the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes integrated area and spectral intensity of the area under the emission peak; determining the element type based on the element matching data, and determining the element content based on the element content matching data; determining the content ratio of the element type based on the element content, comparing the content ratio of the element type with the ore grade corresponding to each content ratio of the element type stored in a database, and determining the ore grade corresponding to the content ratio of the element type.

[0007] Furthermore, the determining of the element type based on the element matching data comprises the following steps: obtaining element reference feature data corresponding to each matching element stored in a database, wherein the element reference feature data comprises an element reference wavelength, an element reference wave width, an element reference wave peak and an element reference waveform shape; comparing and analyzing the element matching data with the element reference feature data corresponding to each element stored in the database to obtain an element matching index; and determining the matching element corresponding to the smallest element matching index as the element type of the element matching data.

[0008] Furthermore, the determining of element content based on element content matching data comprises the following steps: obtaining content matching compensation data, wherein the content matching compensation data comprises an integral area compensation parameter and a spectral intensity compensation parameter; fusing the content matching compensation data with the element content matching data to obtain compensated matching data, wherein the compensated matching data comprises a compensated integral area and a compensated spectral intensity; comparing the compensated matching data with content reference comparison data corresponding to each matching element content stored in a database to obtain an element content matching index, wherein the content reference comparison data comprises an integral area reference comparison parameter and a spectral intensity reference comparison parameter; and determining the matching element content corresponding to the minimum element content matching index as the element content of the element.

[0009] Furthermore, the calculation formula of the element content matching index is as follows:

[0010] ;

[0011] middle, is the number of the content reference comparison data corresponding to each matching element content stored in the database, is the element content matching index, is the integrated area after compensation, is the spectral intensity after compensation, The first The integral area of ​​the reference comparison data corresponding to the content of the matched elements is the reference comparison parameter. The first The spectral intensity reference comparison parameters of the content reference comparison data corresponding to the matching element content, where , , is the integral area compensation parameter, is the spectral intensity compensation parameter, is the integrated area under the emission peak, is the spectral intensity, is a natural constant.

[0012] Furthermore, the process of obtaining content matching compensation data is as follows: after laser induced breakdown, actual working parameters of the intelligent laser induced breakdown spectrometer are obtained, and the actual working parameters include actual pulse width, actual focusing depth and actual laser energy; the actual working parameters are fused and compared with the set laser induced breakdown parameters to obtain a laser induced breakdown deviation index; an ore sample deviation index is obtained, and the ore sample deviation index is used as a basis for determining whether the ore sample can undergo laser induced breakdown; the laser induced breakdown deviation index is fused with the ore sample deviation index to obtain a comprehensive deviation index; the comprehensive deviation index is compared with a comprehensive deviation threshold stored in a database to obtain content matching compensation data.

[0013] Furthermore, the comprehensive deviation index is compared with the comprehensive deviation threshold stored in the database to obtain content matching compensation data, including the following steps: if the comprehensive deviation index is equal to the comprehensive deviation threshold stored in the database, then the matching compensation data stored in the database is obtained, and the matching compensation data stored in the database is defined as the content matching compensation data, and at this time the integral area compensation parameter and the spectral intensity compensation parameter in the content matching compensation data are both 0; if the comprehensive deviation index is not equal to the comprehensive deviation threshold stored in the database, then the difference between the comprehensive deviation index and the comprehensive deviation threshold stored in the database is obtained, and the difference is compared with the matching compensation data corresponding to each difference stored in the database to obtain the matching compensation data corresponding to the difference stored in the database, and the matching compensation data corresponding to the difference stored in the database is defined as the content matching compensation data.

[0014] Furthermore, the calculation formula of the comprehensive deviation index is as follows:

[0015] ;

[0016] In the formula, is the comprehensive deviation index, is the ore sample deviation index, is the laser-induced breakdown deviation index, is the ore sample deviation index weight factor stored in the database, is the laser-induced breakdown deviation index weight factor stored in the database.

[0017] Furthermore, the method of obtaining the ore sample deviation index includes the following steps: obtaining ore sample screening data stored in a database, the ore sample screening data stored in the database including ore sample reference moisture, ore sample reference particle size, ore sample reference roughness and ore sample reference reflectivity; obtaining actual physical data of the ore sample, the actual physical data of the ore sample including actual moisture, ore sample actual particle size, ore sample actual roughness and ore sample actual reflectivity; obtaining the ore sample deviation index based on the actual physical data of the ore sample and the ore sample screening data stored in the database.

[0018] Furthermore, the determination of whether the ore sample can undergo laser induced breakdown comprises the following steps: comparing the ore sample deviation index with the ore sample deviation threshold stored in the database: if the ore sample deviation index is less than or equal to the ore sample deviation threshold stored in the database, determining that the ore sample can undergo laser induced breakdown; if the ore sample deviation index is greater than the ore sample deviation threshold stored in the database, determining that the ore sample cannot undergo laser induced breakdown.

[0019] An ore grade and element detection system, used for the above-mentioned ore grade and element detection method, comprises an ore sample screening module, a spectral data acquisition module, a feature extraction module, an element analysis module and an ore grade determination module, wherein: the ore sample screening module is used to determine whether the ore sample can be subjected to laser induced breakdown, if not, the ore sample is replaced, if it can be subjected to laser induced breakdown, the ore sample is subjected to laser induced breakdown according to set laser induced breakdown parameters, the set laser induced breakdown parameters include set pulse width, set focus depth and set laser energy; the spectral data acquisition module is used to obtain ore grade based on the plasma generated after the ore sample is subjected to laser induced breakdown Sample spectral data; the feature extraction module is used to extract features from the acquired ore sample spectral data to obtain element matching data and element content matching data, the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes the integral area and spectral intensity of the area under the emission peak; the element analysis module is used to determine the element type based on the element matching data, and determine the element content based on the element content matching data; the ore grade determination module is used to determine the content ratio of the element type based on the element content, compare the content ratio of the element type with the ore grade corresponding to each content ratio of the element type stored in the database, and determine the ore grade corresponding to the content ratio of the element type.

[0020] The present invention has the following beneficial effects:

[0021] Compared with traditional chemical analysis methods, this ore grade and element detection method provides rapid sample processing and data analysis, and can complete the detection of a large number of samples in a short time. Through precise laser settings and high-quality spectral data analysis, this method can provide higher detection accuracy and repeatability. Laser-induced breakdown is a non-contact, non-destructive testing method that retains the integrity of the sample and is suitable for precious or limited sample analysis. It solves the problems of traditional chemical analysis methods that are time-consuming, costly and harmful to the environment.

[0022] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The figure is a flow chart of the ore grade and element detection method of the present invention.

[0024] Figure 2 It is a flow chart of the ore grade and element detection system of the present invention. DETAILED DESCRIPTION

[0025] The embodiment of the present application can quickly and accurately determine the type and content of different elements in the ore sample through the ore grade and element detection method and system, and determine the specific grade of the ore by comparing it with the information in the database. This method mainly solves the problem that traditional chemical analysis methods are time-consuming, costly and harmful to the environment, and provides an efficient and non-destructive ore quality assessment technology, which greatly improves the development and utilization efficiency of mineral resources and environmental friendliness.

[0026] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for detecting ore grade and elements, comprising the following steps: determining whether the ore sample can be subjected to laser induced breakdown, replacing the ore sample if the ore sample cannot be subjected to laser induced breakdown, and subjecting the ore sample to laser induced breakdown according to set laser induced breakdown parameters if the ore sample can be subjected to laser induced breakdown, wherein the set laser induced breakdown parameters include setting pulse width, setting focus depth and setting laser energy; acquiring ore sample spectrum data based on plasma generated after the ore sample is subjected to laser induced breakdown; performing feature extraction on the acquired ore sample spectrum data to obtain element matching data and element content matching data, wherein the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes integrated area and spectral intensity of the region under the emission peak; determining the element type based on the element matching data, and determining the element content based on the element content matching data; determining the content proportion of the element type based on the element content, comparing the content proportion of the element type with the ore grade corresponding to each content proportion of the element type stored in the database, and determining the ore grade corresponding to the content proportion of the element type.

[0027] First, evaluate whether the ore sample is suitable for laser induced breakdown (LIBS). This step ensures that only suitable samples are used for analysis, avoiding invalid or erroneous data collection. The ore sample is processed using the set laser parameters (pulse width, focus depth, laser energy). The precise control of these parameters is the key to achieving high-quality spectral data acquisition. The spectral data of the ore sample is obtained through the plasma generated by laser induced breakdown. This step captures the emission spectrum of the elements present in the ore and provides raw data for the next step of analysis. Feature extraction is performed on the spectral data, including wavelength, wave width, wave peak and waveform shape. These features help to identify specific chemical elements.

[0028] The extracted spectral feature data is used to match the features of known elements, determine the type of elements present in the sample, and calculate the integral area and spectral intensity of the area under the emission peak to estimate the element content, which provides a basis for quantitative analysis. The element content ratio is compared with the element content ratio of the corresponding ore grade recorded in the database to determine the ore grade, achieving a quantitative assessment of the ore quality and providing a scientific basis for further mining and processing.

[0029] Compared with traditional chemical analysis methods, it provides fast sample processing and data analysis, and can complete the detection of a large number of samples in a short time. Through precise laser settings and high-quality spectral data analysis, this method can provide higher detection accuracy and repeatability. Laser-induced breakdown is a non-contact, non-destructive testing method that retains the integrity of the sample and is suitable for precious or limited sample analysis.

[0030] The setting of pulse width affects the temperature and density of plasma, thus affecting the quality of spectral signal. Generally, the most suitable pulse width is determined by experiment to obtain the clearest and most distinguishable spectral line. The experiment usually starts from the range recommended by the literature and is optimized by adjusting and observing the clarity and signal-to-noise ratio of the spectral line. The setting of focus depth determines the position of the laser focus on the surface or inside of the sample, affecting the distribution of laser energy and the ablation efficiency of the sample. The setting of focus depth is usually based on the characteristics of the laser and the physical properties of the sample. The focus depth is adjusted experimentally, and the ablation of the sample surface and the consistency of the spectral data are monitored to determine the optimal focus depth. Setting laser energy directly affects the ablation amount of the sample and the quality of the plasma generated. Too low energy may lead to ineffective ablation or too weak signal, while too high energy may lead to excessive ablation of the sample or signal saturation. Usually, several laser energy levels are set in the experiment, and the spectral intensity and signal-to-noise ratio are observed to find the most suitable laser energy setting.

[0031] Specifically, the determining of the element type based on the element matching data includes the following steps: obtaining element reference feature data corresponding to each matching element stored in a database, the element reference feature data including an element reference wavelength, an element reference wave width, an element reference wave peak and an element reference waveform shape; comparing and analyzing the element matching data with the element reference feature data corresponding to each element stored in the database to obtain an element matching index; and determining the matching element corresponding to the smallest element matching index as the element type of the element matching data.

[0032] First, access a database that stores a variety of element reference feature data, including element reference wavelength, wave width, wave peak, and waveform shape. These data are usually derived from scientific research and experiments, and reflect the typical spectral characteristics of each element under specific conditions. The element matching data (experimental data) obtained from the sample is compared with the element reference feature data in the database, and a matching index is calculated using a special algorithm. This index reflects the similarity between the experimental data and the reference data. The matching index is usually calculated as the deviation between the experimental waveform and the reference waveform, which can be quantified using methods such as least squares, correlation coefficients, or other statistical methods.

[0033] In addition to the above methods, the calculation formula of the element matching index can also be as follows:

[0034] ;

[0035] In the formula, is the number of the element reference feature data corresponding to each element stored in the database, To measure wavelength, To measure the wave width, To measure the peak, The first The element reference wavelength of the element reference characteristic data corresponding to each element, The first The element reference wave width of the element reference characteristic data corresponding to the element, The first The element reference peak of the element reference characteristic data corresponding to the element, The waveform shape is consistent with the first The similarity of the element reference waveform shape of the element reference feature data corresponding to the element, is a natural constant.

[0036] In this embodiment, This is the absolute difference term. This part calculates the absolute difference between the experimentally measured wavelength, wave width and wave peak and the reference value of the corresponding element in the database. This difference reflects the numerical closeness of the experimental data to the theoretical or known data. A smaller difference value indicates a higher match. is the waveform shape similarity term, which takes into account the similarity of waveform shapes. Waveform shape is a very important parameter in the analysis, which can help identify overlapping spectra or similar spectral components. The function form is designed to convert the similarity into a logarithmic form, increase the dynamic range of the calculation and improve the sensitivity of small similarity values.

[0037] By using exponential and logarithmic functions, the formula is able to enhance the response to subtle differences, which is particularly important for accurately identifying elements with complex or similar spectral lines. Wavelength is the first and most direct indicator for identifying elements, because the emission spectrum of each element has a unique wavelength characteristic, which is determined by the electronic structure of the element. The wave width provides information about the broadening of the spectral line, which is related to the temperature, pressure, element concentration or instrument resolution of the light source, and is very helpful for distinguishing elements with similar wavelengths but different physical or chemical environments. The peak intensity can reflect the concentration and detection conditions of the element and is an important parameter for quantifying the element content. The waveform shape is a key feature to further refine the element identification, especially when the spectra overlap or multiple elements coexist, the matching of waveform shapes can significantly improve the accuracy and reliability of identification.

[0038] The formula combines four dimensions: wavelength, wave width, wave peak and waveform shape. This multi-feature combination provides comprehensive data comparison and can effectively improve the accuracy and reliability of matching.

[0039] Specifically, the method of determining the element content based on the element content matching data includes the following steps: obtaining content matching compensation data, wherein the content matching compensation data includes an integral area compensation parameter and a spectral intensity compensation parameter; fusing the content matching compensation data with the element content matching data to obtain compensated matching data, wherein the compensated matching data includes a compensated integral area and a compensated spectral intensity; comparing the compensated matching data with content reference comparison data corresponding to each matching element content stored in a database to obtain an element content matching index, wherein the content reference comparison data includes an integral area reference comparison parameter and a spectral intensity reference comparison parameter; and determining the matching element content corresponding to the smallest element content matching index as the element content of the element.

[0040] First, the integral area compensation parameters and spectral intensity compensation parameters are obtained. These compensation parameters are used to adjust the measured data to eliminate deviations caused by experimental conditions (such as instrument differences, sample status, environmental influences, etc.). The obtained compensation parameters are applied to the actually measured integral area and spectral intensity to obtain compensated matching data. This step adjusts the data to more accurately reflect the true content of the element. The compensated matching data is compared with the content reference comparison data of the corresponding element stored in the database. These reference data include the integral area reference comparison parameters and spectral intensity reference comparison parameters of specific elements under standard conditions. The element content matching index is calculated, usually by comparing the difference between the compensated data and the reference data, and the element content with the smallest matching index is selected as the final element content, indicating that this is the reference content closest to the experimental data.

[0041] By compensating for possible errors in the experiment, this method can more accurately determine the element content and provide analytical results that are closer to the actual situation. Comparison with standard reference data in the database can ensure that the results between different experiments are comparable, which is particularly important for scientific research and quality control. The method of selecting the minimum matching index reduces the interference of subjective judgment and ensures the objectivity and repeatability of the results.

[0042] The calculation formula of the element content matching index is as follows:

[0043] ;

[0044] In the formula, is the number of the content reference comparison data corresponding to each matching element content stored in the database, is the element content matching index, is the integrated area after compensation, is the spectral intensity after compensation, The first The integral area of ​​the reference comparison data corresponding to the content of the matched elements is the reference comparison parameter. The first The spectral intensity reference comparison parameters of the content reference comparison data corresponding to the matching element content, where , , is the integral area compensation parameter, is the spectral intensity compensation parameter, is the integrated area under the emission peak, is the spectral intensity, is a natural constant.

[0045] In this embodiment, the compensated integral area and compensated spectral intensity are calculated by adding compensation parameters to the measured data. This compensation helps to correct the influence of factors such as experimental conditions, changes in equipment performance, and different sample states. An exponential function is used to process the square difference between the compensated data and the reference data in the database. This form of processing can amplify smaller differences and enhance sensitivity to subtle changes. The difference term is based on the difference between the compensated integral area and spectral intensity and the reference data, providing a quantitative indicator for evaluating the closeness of the sample to the reference standard.

[0046] Through the application of exponential and squared differences, the formula can sensitively reflect even small differences, which is particularly important for accurately measuring element content, especially when the content is low or the spectral data is complex. Through the use of compensation parameters, data deviations caused by instrument differences, different sample processing or changes in the test environment can be corrected, making the results more reliable and universal. Using reference comparison data in the database can ensure the standardization of results and the accuracy of comparative analysis, which is helpful for quality control in scientific research and industrial applications.

[0047] The integrated area represents the total area under the spectral line in a specific wavelength range, which is usually proportional to the concentration of the element. Therefore, the integrated area is a direct and effective indicator for quantifying the element content. The spectral intensity refers to the intensity of the spectral emission at a specific wavelength. It can provide direct evidence of the existence of the element and reflects the concentration level of the element. High spectral intensity usually means a high concentration of the element. Both parameters Mf and Gf are directly related to the quantitative analysis of the element. Ideally, if the sample processing and instrument conditions are consistent, these two parameters should provide mutually supporting information, that is, the increase in element concentration should be reflected in both the integrated area and the spectral intensity. By adding the compensation parameters (bM, bG) to the measured integrated area (sM) and spectral intensity (sG), the compensated integrated area (Mf) and spectral intensity (Gf) that are adjusted to be closer to the true value can be obtained, which takes into account the difference between the actual experimental situation and the ideal data, and helps to improve the accuracy of data analysis.

[0048] Specifically, the process of obtaining content matching compensation data is as follows: after laser induced breakdown, the actual working parameters of the intelligent laser induced breakdown spectrometer are obtained, and the actual working parameters include actual pulse width, actual focusing depth and actual laser energy; the actual working parameters are fused and compared with the set laser induced breakdown parameters to obtain a laser induced breakdown deviation index; the ore sample deviation index is obtained, and the ore sample deviation index is used as a basis for determining whether the ore sample can undergo laser induced breakdown; the laser induced breakdown deviation index is fused with the ore sample deviation index to obtain a comprehensive deviation index; the comprehensive deviation index is compared with a comprehensive deviation threshold stored in a database to obtain content matching compensation data.

[0049] Measure the actual parameters of the intelligent laser induced breakdown spectrometer in operation, such as pulse width, focus depth and laser energy, which directly affect the laser breakdown process and the quality of the generated spectral data. Compare the actual working parameters with the ideal parameters set previously, and calculate the laser induced breakdown deviation index, which reflects the deviation between the actual operating state of the equipment and the expected settings. Evaluate the adaptability of the characteristics of the ore sample (such as hardness, density, etc.) to laser induced breakdown to form an ore sample deviation index. Combine the laser induced breakdown deviation index and the ore sample deviation index to obtain a comprehensive deviation index, which comprehensively considers the dual effects of the equipment and the sample. Compare the comprehensive deviation index with the preset deviation threshold in the database. If the deviation is within an acceptable range, use the corresponding compensation data to adjust the spectral data analysis results to ensure accurate measurement of the element content.

[0050] By considering the actual conditions of the equipment and samples and making corresponding deviation compensation, the accuracy of element content determination can be significantly improved. This method makes the spectral analysis process more adaptable and can be adjusted according to different equipment operation conditions and sample characteristics, and is suitable for a variety of different test environments and sample types. By comparing and adjusting the actual measurement data with the standard deviation threshold, the data analysis is standardized, making the results more comparable and reliable.

[0051] The calculation formula of laser-induced breakdown deviation index is as follows:

[0052] ;

[0053] In the formula, is the laser-induced breakdown deviation index, is the actual pulse width, is the actual depth of focus, is the actual laser energy, To set the pulse width, To set the focus depth, To set the laser energy.

[0054] The formula takes into account three key laser operating parameters: pulse width (Mk), focal depth (Ms), and laser energy (Mn), which directly affect the laser-induced breakdown process and its effects. For each parameter, the relative deviation between its actual value and the set value is calculated. This relative deviation indicates the degree of deviation of the parameter in actual use, and the relative calculation reflects the accuracy of the parameter setting. The relative deviations of all parameters are summed and added to one, and then the natural logarithm is taken. Adding one is to avoid the situation where the value in the logarithmic operation is zero, which can ensure that effective logarithmic calculations can be performed even in the absence of deviation. By calculating the deviation index, it is possible to clearly quantify whether the performance of the laser equipment in actual operation meets the preset standards and its possible deviation. After identifying the operating parameters with large deviations, targeted adjustments or maintenance can be made to ensure that the equipment operates in the best state, thereby improving the accuracy and repeatability of the experiment. The logarithmic form is often used in statistical analysis to amplify small changes and can compress a relatively large range of values ​​into a more manageable range. This is particularly useful when dealing with parameter deviations, and can more sensitively reflect small deviation changes.

[0055] The pulse width determines the length of time that the laser energy is input to the sample. Short pulse widths can provide high peak power, which helps to quickly heat the material and generate plasma, but may lead to rapid evaporation of the material and explosive material removal, affecting the stability of the plasma. The depth of focus affects the concentration of laser energy on the surface or inside the material. Focusing deeper can increase the energy absorption inside the material, which is conducive to deeper material analysis, but too deep a focus may lead to the loss of surface information. Laser energy is the main factor determining the generation and duration of plasma. High energy can enhance the spectral signal of the plasma and improve the signal-to-noise ratio of the signal, but too high energy may cause excessive ablation of the sample and affect the accuracy of the analysis results. These three parameters work together in the laser-induced breakdown process and influence each other to optimize the acquisition of spectral signals. For example, a shorter pulse width requires a higher laser energy to ensure sufficient spectral signal intensity; at the same time, the adjustment of the depth of focus may need to be adapted according to the changes in pulse width and laser energy to ensure that the beam acts effectively on the sample.

[0056] The method of comparing the comprehensive deviation index with the comprehensive deviation threshold stored in the database to obtain content matching compensation data includes the following steps: if the comprehensive deviation index is equal to the comprehensive deviation threshold stored in the database, then obtaining the matching compensation data stored in the database, and defining the matching compensation data stored in the database as content matching compensation data, at which time the integral area compensation parameter and the spectral intensity compensation parameter in the content matching compensation data are both 0; if the comprehensive deviation index is not equal to the comprehensive deviation threshold stored in the database, then obtaining the difference between the comprehensive deviation index and the comprehensive deviation threshold stored in the database, comparing the difference with the matching compensation data corresponding to each difference stored in the database, obtaining the matching compensation data corresponding to the difference stored in the database, and defining the matching compensation data corresponding to the difference stored in the database as content matching compensation data.

[0057] When the comprehensive deviation index is exactly equal to the threshold value preset in the database, it means that the deviation between the laser equipment and the sample is exactly as expected, and there is no need for additional adjustment. At this time, no compensation needs to be applied, so the compensation parameter is set to 0. When the comprehensive deviation index is inconsistent with the threshold, it indicates that the actual operating conditions deviate from the ideal state, and the compensation parameters need to be adjusted according to the specific size of the deviation to correct any analytical errors caused by the deviation.

[0058] According to the difference between the comprehensive deviation index and the threshold, the database is queried to find the corresponding matching compensation data, which are obtained based on historical experiments and calibrations and are used to adjust key parameters in spectral analysis (such as integrated area and spectral intensity) to ensure the accuracy of the final results.

[0059] By adjusting the content to match the compensation data to compensate for the deviation in the experiment, the element content in the sample can be measured more accurately, especially under undesirable experimental conditions. All compensation adjustments are based on data and algorithms stored in the database in advance. These data and algorithms are derived from a large number of experimental statistics and analysis, which increases the scientificity and accuracy of decision-making. By finely controlling the compensation parameters, deviations of different sizes can be accurately adjusted to ensure that the accuracy of the analysis will not be affected by slight changes in operating conditions. Relying on the thresholds and compensation data stored in the database, the entire compensation process can be automated, reducing human operation errors and improving processing efficiency.

[0060] The calculation formula of the comprehensive deviation index is as follows:

[0061]

[0062] In the formula, is the comprehensive deviation index, is the ore sample deviation index, is the laser-induced breakdown deviation index, is the ore sample deviation index weight factor stored in the database, is the laser-induced breakdown deviation index weight factor stored in the database.

[0063] In this embodiment, the ore sample deviation index reflects the adaptability of the physical and chemical properties of the ore sample to the laser-induced breakdown process. For example, the humidity of the ore affects the penetration of the laser and the quality of the spectral data. The laser-induced breakdown deviation index, which evaluates the deviation between the performance of the laser equipment in actual operation and the preset parameters, such as pulse width, focal depth and laser energy. The comprehensive deviation index is calculated by weighted summation, in which each deviation index is multiplied by its corresponding weight factor and then added, which can comprehensively consider the deviations from both the sample and the equipment.

[0064] By incorporating sample and equipment biases, the formula provides a comprehensive assessment that more fully reflects the impact of experimental conditions on the results.

[0065] Weight factors stored in the database and , determined by analyzing historical data and experimental results. This process involves statistical analysis, such as regression analysis or variance analysis, to evaluate the extent to which different deviation factors (such as the characteristics of the ore sample and the operating parameters of the laser equipment) affect the final result. Through these analyses, it can be determined which factors have a greater impact on the results and the corresponding weights are assigned accordingly. This is done to ensure that the weight factors can accurately reflect the importance of each factor in the comprehensive deviation index, making the results more accurate and reliable.

[0066] Specifically, the method of obtaining the ore sample deviation index includes the following steps: obtaining the ore sample screening data stored in the database, the ore sample screening data stored in the database including the ore sample reference moisture, the ore sample reference particle size, the ore sample reference roughness and the ore sample reference reflectivity; obtaining the actual physical data of the ore sample, the actual physical data of the ore sample including the ore sample actual moisture, the ore sample actual particle size, the ore sample actual roughness and the ore sample actual reflectivity; obtaining the ore sample deviation index based on the actual physical data of the ore sample and the ore sample screening data stored in the database.

[0067] Reference moisture, particle size, roughness and reflectivity of ore samples are extracted from the database. These reference data are based on a large number of experimental and test results and represent the characteristics of ore samples under ideal or typical conditions. The actual physical properties of the current ore sample are measured, including moisture, particle size, roughness and reflectivity. These measurements reflect the specific state of the sample at the time of the experiment. According to the difference between the actual physical data of the ore sample and the reference data in the database, the deviation index is calculated. This deviation index can quantify the degree of deviation between the sample state and the ideal state. The precise evaluation and adjustment of the physical properties of the ore sample can be more accurately performed for laser-induced breakdown spectroscopy analysis, because these physical properties directly affect the interaction effect between the laser and the material. Ore samples often have large variability under natural conditions. By evaluating the specific physical properties of each sample, the experimental method or parameters can be adjusted to adapt to these variations, thereby obtaining more stable and reliable experimental results. Using the standard reference data stored in the database provides a standardized comparison basis for the experiment, which helps to achieve comparability between tests conducted at different times and locations. By taking multiple physical parameters into account, the suitability of an ore sample for a specific experimental setup can be fully assessed, allowing appropriate adjustments to be made or a more suitable sample to be selected prior to the experiment.

[0068] The calculation formula of the ore sample deviation index is as follows:

[0069] ;

[0070] In the formula, is the ore sample deviation index, is the actual humidity of the ore sample, is the actual particle size of the ore sample, is the actual roughness of the ore sample, is the actual reflectivity of the ore sample, is the reference humidity of the ore sample, is the reference particle size of the ore sample, is the reference roughness of the ore sample, is the reference reflectance of the ore sample.

[0071] In this embodiment, for each physical parameter (humidity, particle size, roughness, reflectivity), the relative deviation between its actual measured value and the reference value is calculated. This ratio calculation provides a standardized deviation measure that can ignore the influence of units and magnitudes and directly reflect the degree of deviation. The deviation ratios of all parameters are summed, and one is added at the end, and then the natural logarithm is taken. Adding one is to ensure that the logarithmic function is still computable in the absence of any deviation (i.e., when the sum of all ratios is zero) to avoid mathematical errors. By calculating the ratio of the relative deviation of each parameter, physical properties of different types and scales can be standardized, so that the deviation assessment is not affected by the specific physical quantity unit, and the fairness and consistency of the comparison are enhanced. By accurately measuring the deviation between the sample characteristics and the reference value, the experimental settings or pretreatment steps can be adjusted to ensure that the experimental conditions better match the actual state of the sample, thereby improving the accuracy and reliability of the analytical data.

[0072] Humidity directly affects the physical and chemical behavior of ore samples under laser irradiation. High humidity may cause the laser energy to be partially absorbed by water, reducing the energy acting on the mineral itself, thereby affecting the generation and stability of plasma. Particle size affects the absorption and scattering characteristics of the sample surface to the laser energy. Larger particle size may lead to uneven distribution of laser absorption and thermal effects, while smaller particle size helps to obtain more uniform and representative spectral signals. Roughness affects the interaction between the laser beam and the sample surface. The rough surface can increase the laser scattering and absorption area, sometimes increasing the intensity of the spectral signal, but may also cause signal inconsistency. Reflectivity determines how much laser energy is reflected by the sample surface instead of being absorbed. High reflectivity usually means less energy is used to generate plasma, which may affect the quality and detectability of the spectrum.

[0073] These parameters are interrelated and together determine the effect of the interaction between the laser and the sample. For example, high humidity may increase the reflectivity of the sample, while changes in particle size and roughness will affect the scattering and absorption of the laser on the sample surface. In LIBS analysis, the ideal sample should have moderate humidity, uniform particle size, appropriate roughness and low reflectivity to maximize the absorption of laser energy and the generation of plasma. By considering multiple independent physical properties, the formula provides a comprehensive evaluation of sample characteristics, which helps to fully understand the sample state and ensure the comprehensiveness and in-depth analysis results.

[0074] Specifically, the determination of whether the ore sample can undergo laser induced breakdown includes the following steps: comparing the ore sample deviation index with the ore sample deviation threshold stored in the database: if the ore sample deviation index is less than or equal to the ore sample deviation threshold stored in the database, determining that the ore sample can undergo laser induced breakdown; if the ore sample deviation index is greater than the ore sample deviation threshold stored in the database, determining that the ore sample cannot undergo laser induced breakdown.

[0075] In this embodiment, the ore sample deviation index is calculated based on the deviation between the actual physical data of the sample (such as humidity, particle size, roughness and reflectivity) and the reference data. This index quantifies the degree of deviation between the sample state and the ideal or typical state. The ore sample deviation threshold stored in the database is set based on a large amount of experimental data, which represents the maximum allowable deviation of the sample for laser-induced breakdown. By comparing the actual deviation index with this threshold, it can be determined whether the sample is within the acceptable deviation range. If the deviation index is less than or equal to the threshold, it is considered that the physical state of the sample is suitable for LIBS analysis because its deviation is within the controllable range and does not affect the quality of the analysis results. If the deviation index exceeds the threshold, it is considered that the physical state of the sample may not be suitable for LIBS analysis because excessive deviation may cause inaccurate or non-repeatable analysis results.

[0076] Avoiding the analysis of inappropriate samples can save valuable time and resources, improve experimental efficiency, and through strict sample screening, ensure that the data obtained is more stable and reliable, thereby enhancing the generalizability and repeatability of experimental results.

[0077] A system for detecting ore grade and elements, such as Figure 2As shown, a method for detecting ore grade and elements as described above includes an ore sample screening module, a spectral data acquisition module, a feature extraction module, an element analysis module and an ore grade determination module, wherein: the ore sample screening module is used to determine whether the ore sample can be subjected to laser induced breakdown, if not, the ore sample is replaced, if it can be subjected to laser induced breakdown, the ore sample is subjected to laser induced breakdown according to set laser induced breakdown parameters, the set laser induced breakdown parameters include set pulse width, set focus depth and set laser energy; the spectral data acquisition module is used to acquire spectral data of the ore sample based on the plasma generated after the ore sample is subjected to laser induced breakdown ; The feature extraction module is used to extract features from the acquired ore sample spectral data to obtain element matching data and element content matching data, wherein the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes the integral area and spectral intensity of the area under the emission peak; the element analysis module is used to determine the element type based on the element matching data, and to determine the element content based on the element content matching data; the ore grade determination module is used to determine the content ratio of the element type based on the element content, and compare the content ratio of the element type with the ore grade corresponding to each content ratio of the element type stored in the database to determine the ore grade corresponding to the content ratio of the element type.

[0078] An electronic device comprises: a processor and a memory, wherein computer program instructions are stored in the memory, and when the computer program instructions are executed by the processor, the processor executes the above-mentioned ore grade and element detection method.

[0079] A computer-readable storage medium is used to store a program, and when the program is executed by a processor, the ore grade and element detection method as described above is implemented.

[0080] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0084] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0085] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for detecting ore grade and elements, characterized in that: The following steps are involved: Determine whether the ore sample can be subjected to laser induced breakdown, if not, replace the ore sample, if it can be subjected to laser induced breakdown, perform laser induced breakdown on the ore sample according to set laser induced breakdown parameters, wherein the set laser induced breakdown parameters include setting pulse width, setting focus depth and setting laser energy; Obtaining ore sample spectrum data based on plasma generated after laser-induced breakdown of the ore sample; Extracting features from the acquired ore sample spectrum data to obtain element matching data and element content matching data, wherein the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes the integrated area and spectral intensity of the region under the emission peak; Determine the element type based on the element matching data, and determine the element content based on the element content matching data; Determining the element content based on the element content matching data comprises the following steps: Acquiring content matching compensation data, wherein the content matching compensation data includes an integrated area compensation parameter and a spectral intensity compensation parameter; The content matching compensation data is merged with the element content matching data to obtain compensated matching data, wherein the compensated matching data includes a compensated integral area and a compensated spectral intensity; Compare the compensated matching data with the content reference comparison data corresponding to the content of each matching element stored in the database to obtain the element content matching index, wherein the content reference comparison data includes an integral area reference comparison parameter and a spectral intensity reference comparison parameter; The matching element content corresponding to the minimum element content matching index is determined as the element content of the element; The calculation formula of the element content matching index is as follows: ； In the formula, is the number of the content reference comparison data corresponding to each matching element content stored in the database, is the element content matching index, is the integrated area after compensation, is the spectral intensity after compensation, The first The integral area of ​​the reference comparison data corresponding to the content of the matched elements is the reference comparison parameter. The first The spectral intensity reference comparison parameters of the content reference comparison data corresponding to the matching element content, where , , is the integral area compensation parameter, is the spectral intensity compensation parameter, is the integrated area under the emission peak, is the spectral intensity, is a natural constant; The content ratio of the element type is determined based on the element content, and the content ratio of the element type is compared with the ore grade corresponding to each content ratio of the element type stored in the database to determine the ore grade corresponding to the content ratio of the element type.

2. The method for detecting ore grade and elements according to claim 1, characterized in that: Determining the element type based on the element matching data comprises the following steps: Acquire element reference characteristic data corresponding to each matching element stored in a database, wherein the element reference characteristic data includes an element reference wavelength, an element reference wave width, an element reference wave peak, and an element reference waveform shape; Compare and analyze the element matching data with the element reference characteristic data corresponding to each element stored in the database to obtain the element matching index; The matching element corresponding to the smallest element matching index is determined as the element type of the element matching data.

3. The method for detecting ore grade and elements according to claim 1, characterized in that: The process of obtaining content matching compensation data is as follows: After the laser induced breakdown, actual working parameters of the intelligent laser induced breakdown spectrometer are obtained, wherein the actual working parameters include actual pulse width, actual focus depth and actual laser energy; The actual working parameters are compared with the set laser-induced breakdown parameters to obtain the laser-induced breakdown deviation index; Obtaining a deviation index of the ore sample, wherein the deviation index of the ore sample is used as a basis for determining whether the ore sample can be subjected to laser induced breakdown; The laser-induced breakdown deviation index is combined with the ore sample deviation index to obtain a comprehensive deviation index; The comprehensive deviation index is compared with the comprehensive deviation threshold stored in the database to obtain content matching compensation data.

4. A method for detecting ore grade and elements according to claim 3, characterized in that: The method of comparing the comprehensive deviation index with the comprehensive deviation threshold stored in the database to obtain content matching compensation data comprises the following steps: If the comprehensive deviation index is equal to the comprehensive deviation threshold stored in the database, the matching compensation data stored in the database is obtained, and the matching compensation data stored in the database is defined as content matching compensation data. At this time, the integral area compensation parameter and the spectral intensity compensation parameter in the content matching compensation data are both 0; If the comprehensive deviation index is not equal to the comprehensive deviation threshold stored in the database, the difference between the comprehensive deviation index and the comprehensive deviation threshold stored in the database is obtained, the difference is compared with the matching compensation data corresponding to each difference stored in the database, and the matching compensation data corresponding to the difference stored in the database corresponding to the difference is obtained, and the matching compensation data corresponding to the difference stored in the database is defined as content matching compensation data.

5. The method for detecting ore grade and elements according to claim 3, characterized in that: The calculation formula of the comprehensive deviation index is as follows: ； In the formula, is the comprehensive deviation index, is the ore sample deviation index, is the laser-induced breakdown deviation index, is the ore sample deviation index weight factor stored in the database, is the laser-induced breakdown deviation index weight factor stored in the database.

6. The method for detecting ore grade and elements according to claim 3, characterized in that: The method of obtaining the ore sample deviation index comprises the following steps: Acquire ore sample screening data stored in a database, wherein the ore sample screening data stored in the database includes ore sample reference moisture, ore sample reference particle size, ore sample reference roughness and ore sample reference reflectivity; Acquiring actual physical data of the ore sample, wherein the actual physical data of the ore sample includes actual moisture of the ore sample, actual particle size of the ore sample, actual roughness of the ore sample and actual reflectivity of the ore sample; The ore sample deviation index is obtained based on the actual physical data of the ore sample and the ore sample screening data stored in the database.

7. A method for detecting ore grade and elements according to claim 6, characterized in that: The method of determining whether the ore sample can be subjected to laser induced breakdown comprises the following steps: Compare the ore sample deviation index with the ore sample deviation threshold stored in the database: If the ore sample deviation index is less than or equal to the ore sample deviation threshold stored in the database, it is determined that the ore sample can be subjected to laser induced breakdown; If the ore sample deviation index is greater than the ore sample deviation threshold stored in the database, it is determined that the ore sample cannot be subjected to laser induced breakdown.

8. An ore grade and element detection system, used in an ore grade and element detection method according to any one of claims 1 to 7, characterized in that: It includes ore sample screening module, spectral data acquisition module, feature extraction module, element analysis module and ore grade determination module, among which: The ore sample screening module is used to determine whether the ore sample can be subjected to laser induced breakdown. If it cannot be subjected to laser induced breakdown, the ore sample is replaced. If it can be subjected to laser induced breakdown, the ore sample is subjected to laser induced breakdown according to set laser induced breakdown parameters. The set laser induced breakdown parameters include setting pulse width, setting focus depth and setting laser energy. The spectrum data acquisition module is used to acquire spectrum data of the ore sample based on the plasma generated after the ore sample is subjected to laser-induced breakdown; The feature extraction module is used to extract features from the acquired ore sample spectrum data to obtain element matching data and element content matching data, wherein the element matching data includes measurement wavelength, measurement wave width, measurement wave peak and waveform shape, and the element content matching data includes the integrated area and spectral intensity of the region under the emission peak; The element analysis module is used to determine the element type based on the element matching data and determine the element content based on the element content matching data; Determining the element content based on the element content matching data comprises the following steps: Acquiring content matching compensation data, wherein the content matching compensation data includes an integrated area compensation parameter and a spectral intensity compensation parameter; The content matching compensation data is merged with the element content matching data to obtain compensated matching data, wherein the compensated matching data includes a compensated integral area and a compensated spectral intensity; Compare the compensated matching data with the content reference comparison data corresponding to the content of each matching element stored in the database to obtain the element content matching index, wherein the content reference comparison data includes an integral area reference comparison parameter and a spectral intensity reference comparison parameter; The matching element content corresponding to the minimum element content matching index is determined as the element content of the element; The calculation formula of the element content matching index is as follows: ； In the formula, is the number of the content reference comparison data corresponding to each matching element content stored in the database, is the element content matching index, is the integrated area after compensation, is the spectral intensity after compensation, The first The integral area of ​​the reference comparison data corresponding to the content of the matched elements is the reference comparison parameter. The first The spectral intensity reference comparison parameters of the content reference comparison data corresponding to the matching element content, where , , is the integral area compensation parameter, is the spectral intensity compensation parameter, is the integrated area under the emission peak, is the spectral intensity, is a natural constant; The ore grade determination module is used to determine the content ratio of the element type based on the element content, compare the content ratio of the element type with the ore grades corresponding to each content ratio of the element type stored in the database, and determine the ore grade corresponding to the content ratio of the element type.

Images