A mineral analysis system based on online detection and intelligent feedback

Abstract

The present invention relates to the technical field of mineral analysis, and specifically discloses a mineral analysis system based on online detection and intelligent feedback. The system is provided with an element composition detection module, a synchronous spectral inversion module, a chemical substance retrieval and grading module, and a dual-track intelligent feedback module, to obtain a mineral element composition content table and a laser induced breakdown index to calculate the spectral characteristic value of a mineral sample and perform intelligent inversion of the mineral chemical structure, obtain the chemical substance content value of the mineral sample and the mineral chemical substance deviation rate, perform qualified marking and mineral grade marking on the current mineral sample, feed back and store the mineral analysis result in a mineral analysis data center, comprehensively analyze the grade and the mineral chemical substance deviation rate for laser adjustment, reduce mineral analysis errors and problem risks, and achieve high-sensitivity, high-reference mineral detection and intelligent feedback analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of mineral analysis, and in particular to a mineral analysis system based on online detection and intelligent feedback. Background Art

[0002] Mineral analysis can be used to monitor the content and combination of various mineral elements in the process flow to ensure that the quality of the product meets the standards, detect impurities or abnormal mineral content as early as possible, and take timely measures to adjust the production process to ensure stable product quality. At the same time, by analyzing the content and fluctuations of various mineral elements, process bottlenecks and room for improvement can be identified to improve overall production efficiency, which is conducive to enterprises to optimize the production process flow, improve production efficiency and reduce production costs. From the perspective of resource utilization, mineral analysis can accurately control the input amount and ratio of raw materials according to the analysis results, avoid excessive consumption of resources and waste of materials, rationally utilize mineral element resources, save production costs, improve resource utilization efficiency, detect the content of pollutants and harmful substances in the production process, and improve the technical level of mineral production and processing.

[0003] Nowadays, there are still some shortcomings, which are specifically reflected in the following aspects: traditional mineral analysis relies on the sampling results of mineral samples and needs to go through a complex pretreatment process. On the one hand, mineral samples will cause mineral wear during the pretreatment process of slicing, grinding, and dissolving, resulting in an increase in the sample processing cost in the detection and analysis of minerals. The time dimension of mineral analysis will also be extended with the increase in the accuracy of pretreatment operations, which is not conducive to improving the real-time online feedback efficiency of mineral analysis; on the other hand, this method cannot maintain the integrity of mineral samples, and the deviation of pretreatment operations will cause certain human errors in the original mineral spectral characteristics. The traditional acquisition of mineral chemical structure is usually based on direct measurement, which is separated from the determination and analysis of mineral elemental composition and needs to be carried out separately. Two parts of analysis and testing are required, which requires additional steps and operations, increasing the complexity and tediousness of the mineral analysis process, and the time cost is high, resulting in a lack of comprehensiveness in the method of obtaining mineral analysis results. At the same time, the acquired mineral chemical structure and mineral elemental composition are obtained separately, so it is impossible to fully understand the relationship between the internal structure of the mineral and the elemental composition. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a mineral analysis system based on online detection and intelligent feedback, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a mineral analysis system based on online detection and intelligent feedback, including an elemental composition detection module, a synchronous spectral inversion module, a chemical substance retrieval and grading module and a dual-track intelligent feedback module, wherein the elemental composition detection module is used to obtain a mineral elemental composition content table and a laser-induced breakdown index; the synchronous spectral inversion module is used to calculate the spectral characteristic values ​​of the mineral sample based on the mineral elemental composition content table and the laser-induced breakdown index, perform intelligent inversion of the mineral chemical structure based on the spectral characteristic values ​​of the mineral sample, and obtain the chemical substance content value of the mineral sample; the chemical substance retrieval and grading module is used to obtain the mineral chemical substance deviation rate based on the chemical substance content value of the mineral sample, and perform qualified marking on the current mineral sample based on the mineral chemical substance deviation rate, obtain the qualified marking result, and perform mineral grade marking on the mineral sample based on the qualified marking result; the dual-track intelligent feedback module is used to perform mineral spectral characteristic values ​​and chemical substance types, chemical substance content values, and mineral chemical substance deviation rate feedback on the qualified mineral samples in the mineral sample qualified marking according to the grade and store them in the mineral analysis data center, and comprehensively analyze the grade and mineral chemical substance deviation rate for laser adjustment.

[0006] As a further solution, a mineral element composition content table is obtained. The specific analysis process includes: performing ultrashort pulse laser induced breakdown on the mineral sample to excite the surface plasma of the mineral sample, performing element composition detection based on the surface plasma of the mineral sample, and obtaining plasma element composition detection result parameters, wherein the plasma element composition detection result parameters include element composition type and element composition content; sorting the element composition types based on the element composition content and calculating the proportion of each element composition content, and establishing a mineral element composition content table.

[0007] As a further solution, the laser induced breakdown index is obtained, and the specific analysis process is as follows: obtaining the environmental purity parameters in the ultrashort pulse laser induced breakdown process, the environmental purity parameters include the luminous flux of visible light received per unit area, the content of active microorganisms, the environmental gas flow rate, and the noise frequency; obtaining the breakdown environment purity grade based on the environmental purity grade assessment model and the environmental purity parameters; obtaining the laser induced breakdown environment addition value set in the database based on the breakdown environment purity grade; obtaining the laser induced breakdown parameters in the ultrashort pulse laser induced breakdown process, the laser induced breakdown parameters include the laser machine air cooling efficiency, pulse energy, pulse width, and ablation diameter; obtaining the laser induced breakdown index based on the laser induced parameters and the laser induced breakdown environment addition value set in the database.

[0008] As a further approach, the calculation formula for the laser-induced breakdown index is:

[0009]

[0010] Where J is the laser-induced breakdown index, f is the air cooling efficiency of the laser machine, m is the pulse energy, d is the pulse width, z is the ablation diameter, is the laser induced breakdown environment addition value set in the database, and e is a natural constant.

[0011] As a further solution, the spectral characteristic values ​​of the mineral sample are calculated based on the mineral element composition content table and the laser induced breakdown index. The specific analysis process is: obtain the element composition types in the mineral element composition content table whose element composition content accounts for more than 1%; obtain the spectral image of the plasma, and the spectral image of the plasma reflects the spectral characteristics of the mineral sample; obtain the spectral characteristic parameters of the material sample whose element composition content accounts for more than 1% based on the spectral image of the plasma, and the spectral characteristic parameters of the material sample include the number of spectral peaks, the uniformity of spectral site distribution and the absorbance of spectral absorption peak; obtain the spectral characteristic values ​​based on the spectral characteristic parameters of the material sample and the laser induced breakdown index.

[0012] As a further solution, the calculation formula of the spectral characteristic value is:

[0013]

[0014] Where TZ is the spectral characteristic value, G is the number of spectral peaks, Y is the uniformity of spectral site distribution, X is the absorptivity of the spectral absorption peak, J is the laser-induced breakdown index, and e is a natural constant.

[0015] As a further solution, intelligent inversion of the mineral chemical structure is performed based on the spectral characteristic values ​​of the mineral samples to obtain the chemical substance content values ​​of the mineral samples. The specific analysis process is: obtaining the spectral characteristic values ​​of the mineral samples; matching the chemical structure combination in the mineral analysis data center based on the spectral characteristic values ​​of the mineral samples, and retrieving the chemical structure combination to obtain the types of chemical substances contained in the mineral samples; obtaining the chemical substance content values ​​of the mineral samples based on the mineral chemical substance measurement model and the number of chemical substance types and spectral characteristic values ​​contained in the mineral samples.

[0016] As a further solution, the mineral chemical substance deviation rate is obtained based on the chemical substance content value of the mineral sample, and the current mineral sample is marked as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. The specific analysis process is: obtaining the chemical substance content value of the mineral sample; obtaining the mineral chemical substance target value set in the database based on the chemical substance content value of the mineral sample; obtaining the mineral chemical substance deviation rate based on the chemical substance content value of the mineral sample, the mineral chemical substance target value set in the database and the mineral chemical substance content deviation model; marking the current mineral sample as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. The mineral chemical substance deviation rate is the basis for judging whether the current mineral sample is qualified and the grade classification.

[0017] As a further solution, mineral samples are marked with mineral grades based on the qualified marking results. The specific analysis process is: obtaining the mineral chemical substance deviation rate of the mineral samples whose qualified marking results are qualified; obtaining the set mineral chemical substance deviation rate interval endpoints in the database; grading based on the mineral chemical substance deviation rate of the mineral samples whose qualified marking results are qualified and the set mineral chemical substance deviation rate interval endpoints in the database; marking the mineral samples with mineral grades.

[0018] As a further solution, the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark are fed back according to the grade and stored in the mineral analysis data center, and the grade and mineral chemical substance deviation rates are comprehensively analyzed for laser adjustment. The specific analysis process is: obtaining the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark; obtaining the corresponding data storage points in the mineral analysis data center based on the grade of the qualified mineral sample mark in the qualification mark; feeding back the mineral spectral characteristic values, chemical substance types, and chemical substance content values ​​of the qualified mineral samples based on the data storage points and storing them in the mineral analysis data center; extracting the grade and mineral chemical substance deviation rate of qualified mineral samples in the mineral analysis data center; calculating the laser ablation diameter optimization value based on the grade of the qualified mineral sample, the mineral chemical substance deviation rate and the laser induced breakdown optimization model, and performing laser adjustment, wherein the laser adjustment refers to increasing the ablation diameter in the laser induced breakdown parameters according to the laser ablation diameter optimization value.

[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0020] (1) The analytical process of obtaining mineral element composition and content based on ultrashort pulse laser induced breakdown spectroscopy technology not only has the characteristics of high sensitivity, high reference and full element analysis, but also does not limit the sample morphology during the entire measurement process, nor does it require complex pretreatment such as slicing, grinding, and dissolving of the sample. Therefore, this method can minimize the damage to the sample by the outside world during the measurement process, maintain the integrity of the object, and retain the spectral characteristics of the original substance. It has strong scene applicability and can effectively meet the urgent needs of mining production enterprises for online real-time detection of raw materials and mineral component analysis in various links of the mineral processing and processing process.

[0021] (2) The present invention uses the spectral characteristic values ​​of mineral samples to perform intelligent inversion of the chemical structure of minerals to obtain the chemical substances contained in the mineral samples, which breaks through the traditional detection consumption for determining chemical substances and is conducive to quickly and accurately obtaining information on the chemical substances contained in the mineral samples. By performing intelligent inversion analysis on the spectral data of mineral samples, the corresponding relationship between the elemental composition and the chemical substances in the samples as well as the content, structure and other information of the chemical substances can be obtained. The chemical substance analysis results of the mineral samples can help to accurately determine the type of ore deposit and the mineralization law, thereby improving the efficiency and success rate of the analysis. In addition, it can also help the developers of mineral resources to better understand the chemical composition and chemical properties of the ore, guide the mineral processing and smelting processes in the mining process, and thus improve the mining and utilization efficiency of mineral resources and reduce mining costs.

[0022] (3) The mineral spectral characteristic values, chemical substance types and chemical substance content values ​​of qualified mineral samples in the mineral sample qualification mark are fed back according to the grade and stored in the corresponding data storage point of the mineral analysis data center. An objective and convenient data storage method is established. The qualified mineral samples in the mineral sample qualification mark are stored according to the grade. On the one hand, with the help of classified storage, real-time intelligent feedback of mineral analysis results can be achieved while performing data induction and rapid retrieval. On the other hand, storage according to grade can divide the data space, save the data computing power of the mineral analysis data center, and improve data storage efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0024] Figure 1 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] See also Figure 1 The embodiment of the present invention provides a technical solution: a mineral analysis system based on online detection and intelligent feedback, including an element composition detection module, a synchronous spectrum inversion module, a chemical substance retrieval and classification module and a dual-track intelligent feedback module.

[0027] The element composition detection module is used to obtain the mineral element composition content table and laser induced breakdown index.

[0028] Specifically, a mineral element composition content table is obtained, and the specific analysis process includes: performing ultrashort pulse laser induced breakdown on the mineral sample to excite the surface plasma of the mineral sample, performing element composition detection based on the surface plasma of the mineral sample, and obtaining plasma element composition detection result parameters, wherein the plasma element composition detection result parameters include element composition type and element composition content; sorting the element composition types based on the element composition content and calculating the proportion of each element composition content, and establishing a mineral element composition content table.

[0029] It should be noted that the use of ultrashort pulse laser technology for elemental composition detection can achieve high-sensitivity detection of trace elements in mineral samples under the premise of zero loss of mineral samples. The non-contact and non-destructive detection method will not destroy the structure of the mineral sample and retains the integrity of the sample. At the same time, the detection of elemental composition under this method is essentially for the detection of elemental composition by ultrashort pulse laser induced breakdown to excite the plasma on the surface of the sample, which can realize the simultaneous detection of multiple elements, reduce the time cost of intelligent feedback of mineral analysis on the basis of shortening the detection time, improve the detection speed, improve the analysis efficiency, have higher accuracy, and make the detection results more reliable. The elemental composition types are sorted based on the elemental composition content and the proportion of each elemental composition content is calculated to form a mineral elemental composition content table. On the one hand, it is conducive to the later extraction of plasma spectral images to obtain the spectral characteristic parameters of material samples with elemental composition types with elemental composition content accounting for more than 1%. On the other hand, the sorting of elemental composition types based on the elemental composition content conforms to the logical structure of intelligent inversion of the mineral chemical structure. Through the sorting of the elemental composition content and the proportion calculation, the content distribution of each element in the sample is clearly presented, which can reflect the corresponding relationship between the elemental composition content and the chemical composition in the sample.

[0030] It should be noted that the analysis process of obtaining mineral element composition and content based on ultrashort pulse laser induced breakdown spectroscopy technology not only has the characteristics of high sensitivity, high reference and full element analysis, but also does not limit the sample shape during the entire measurement process, and does not require complex pretreatment such as slicing, grinding, and dissolving of the sample. Therefore, this method can minimize the external damage to the sample during the measurement process, maintain the integrity of the object, and retain the spectral characteristics of the original substance. It has strong scene applicability and can effectively meet the urgent needs of mining production companies for online real-time detection of raw materials and mineral component analysis in various links of the mineral processing and processing process.

[0031] Specifically, the laser induced breakdown index is obtained, and the specific analysis process is as follows: obtaining the environmental purity parameters in the ultrashort pulse laser induced breakdown process, the environmental purity parameters include the luminous flux of visible light received per unit area, the content of active microorganisms, the environmental gas flow rate, and the noise frequency; obtaining the breakdown environment purity grade based on the environmental purity grade assessment model and the environmental purity parameters; obtaining the laser induced breakdown environment addition value set in the database based on the breakdown environment purity grade; obtaining the laser induced breakdown parameters in the ultrashort pulse laser induced breakdown process, the laser induced breakdown parameters include the laser machine air cooling efficiency, pulse energy, pulse width, and ablation diameter; obtaining the laser induced breakdown index based on the laser induced parameters and the laser induced breakdown environment addition value set in the database.

[0032] It should be noted that the calculation formula of the environmental purity rating model is as follows;

[0033]

[0034] In the formula, D is the purity level of the breakdown environment, T is the luminous flux of visible light received per unit area, W is the content of active microorganisms, Q is the flow rate of environmental gas, Z is the noise frequency, and e is a natural constant.

[0035] It should be noted that the purity of the breakdown environment is an evaluation index for the impact of the environmental quality in the ultrashort pulse laser-induced breakdown process on the plasma generated by laser-induced breakdown. The luminous flux of visible light received per unit area refers to the light energy flow rate from the visible light band received per unit area. The luminous flux of visible light can excite free electrons in the plasma, increase their energy level, and improve the movement performance of electrons, which is helpful to form high-temperature, high-energy, and high-quality plasma under the action of laser. Excessive luminous flux may cause excessive excitation of the plasma, local high temperature, etc., which will have a destructive effect on the plasma and its surrounding environment, affecting its stability and performance. The active microbial content refers to the number or density of active microorganisms present in a unit volume of air, expressed as an indicator of the number of active organisms. The active microorganisms The content reflects the richness and biodiversity of microorganisms in the environment, which in turn affects the oxygen and moisture content of the surrounding air, changes the propagation characteristics of the light beam, and thus affects the focusing and energy transmission effects of the laser. The environmental gas flow rate is used to indicate the rate at which the gas in the environment passes through a unit area per unit time, usually expressed in units such as cubic meters per second or cubic meters per hour. The gas flow rate affects the diffusion and propagation of gases in the atmosphere, thereby affecting the propagation, defocusing and focusing of the laser beam. The environmental purity has an impact on the interaction between the laser and the plasma. The noise frequency is the frequency of the sound wave in the environment, which is used to indicate the distribution of each frequency component in the noise signal. Noise of a specific frequency will interfere with or interfere with the purity of the working environment of the laser breakdown, affecting the output power, frequency and coherence of the laser.

[0036] It should be noted that there is a certain positive correlation between the luminous flux of visible light and the content of active microorganisms. The growth and metabolism of active microorganisms usually require photosynthesis. When the luminous flux is high, it can provide more light energy required for photosynthesis, thereby promoting the reproduction and growth of active microorganisms. At the same time, it can also promote the decomposition of oxygen and water in the air, produce more active oxidizing substances, and the oxidation reaction in the environment releases heat, causing the gas to flow or diffuse, thereby affecting the flow rate of environmental gases. High luminous flux will increase the photocurrent of the photoreceptor, and the noise frequency will interfere with the signal of the photoreceptor. Excessively high noise frequency may cause erroneous readings or interference of the photoreceptor, thereby affecting the accurate detection of luminous flux.

[0037] Specifically, the calculation formula of the laser-induced breakdown index is:

[0038]

[0039] Where J is the laser-induced breakdown index, f is the air cooling efficiency of the laser machine, m is the pulse energy, d is the pulse width, z is the ablation diameter, is the laser induced breakdown environment addition value set in the database, and e is a natural constant.

[0040] It should be noted that the laser induced breakdown index is used to evaluate the laser quality of the plasma generated by laser induced breakdown in the ultrashort pulse laser induced breakdown operation. It indicates the characteristics of the mineral sample when responding to laser energy under specific conditions, and thus serves as an important indicator affecting the effect of plasma breakdown. The set laser induced breakdown environment addition value is extracted from the database. A mapping set of historically measured laser induced breakdown environment addition values ​​is established based on historical data to obtain the current laser induced breakdown environment addition value. The laser machine air cooling efficiency is used to indicate the efficiency of the laser using an air cooling system for cooling. It is usually expressed by the ratio between the electrical power absorbed by the laser and the actual laser power generated. Good air cooling efficiency can maintain the stability and performance of the laser and ensure the stability and consistency of the laser output power, thereby affecting the effect of plasma breakdown. Pulse energy refers to the energy carried by the laser when each pulse is emitted. The pulse energy directly determines the laser The energy transfer and local ablation degree of the target mineral sample affect the interaction intensity between the laser and the target mineral sample. The pulse width refers to the duration of the pulse laser. The pulse width affects the duration of the laser and is an important factor affecting the energy transfer rate and duration of the laser, which in turn affects the time evolution and stability of the plasma breakdown process. The ablation diameter refers to the diameter length of the ablation area caused by the laser on the target surface, which directly affects the generation and evolution process of the plasma, thereby affecting the effect of the plasma breakdown. Good air cooling efficiency can maintain the high-efficiency operation of the laser and ensure continuous output of high energy. The pulse energy and pulse width jointly determine the intensity and duration of the laser pulse. Higher pulse energy and longer pulse width will cause a larger range of ablation, which usually leads to a larger ablation diameter. The laser causes a greater degree of ablation in the target mineral sample, forming a better effect of affecting the breakdown plasma.

[0041] The synchronous spectral inversion module is used to calculate the spectral characteristic values ​​of mineral samples based on the mineral element composition content table and the laser induced breakdown index, perform intelligent inversion of the mineral chemical structure based on the spectral characteristic values ​​of the mineral samples, and obtain the chemical substance content value of the mineral samples.

[0042] Specifically, the spectral characteristic values ​​of the mineral samples are calculated based on the mineral element composition content table and the laser induced breakdown index, and the specific analysis process is: obtaining the types of element components in the mineral element composition content table whose element composition content accounts for more than 1%; obtaining a spectral image of the plasma, the spectral image of the plasma reflects the spectral characteristics of the mineral sample; obtaining spectral characteristic parameters of the material sample whose element composition content accounts for more than 1% based on the spectral image of the plasma, the spectral characteristic parameters of the material sample include the number of spectral peaks, the uniformity of spectral site distribution and the absorbance of spectral absorption peak; obtaining spectral characteristic values ​​based on the spectral characteristic parameters of the material sample and the laser induced breakdown index.

[0043] It should be noted that the spectral characteristics of mineral samples are extracted by using the elemental components in the mineral element content table that account for more than 1%, which reasonably reduces the spectral feature interference error caused by too little elemental content, conforms to the analysis logic of the correspondence between elemental composition and the chemical substance content of mineral samples, and avoids the waste of data computing power. This comprehensive analysis method organically combines and efficiently analyzes mineral element content information and spectral feature information, which can more comprehensively reveal the chemical composition and spectral characteristics of mineral samples. By obtaining the spectral image of plasma to reflect the spectral characteristics of mineral samples, the spectral characteristics of mineral samples can be more intuitively understood, and an effective basis can be provided for the subsequent acquisition and calculation of spectral feature parameters, thereby realizing the direct display and quantitative analysis of the spectral characteristics of samples.

[0044] Furthermore, the calculation formula of the spectral characteristic value is:

[0045]

[0046] Where TZ is the spectral characteristic value, G is the number of spectral peaks, Y is the uniformity of spectral site distribution, X is the absorptivity of the spectral absorption peak, J is the laser-induced breakdown index, and e is a natural constant.

[0047] It should be noted that the spectral characteristic value is a quantitative indicator of spectral characteristics based on plasma spectral images, and is an important criterion for intelligent inversion of mineral chemical structure. The number of spectral peaks refers to the number of peaks appearing on the spectral curve, which reflects the types and contents of different elements or compounds in the sample. An increase in the number of spectral peaks usually indicates that there are more types of chemical compounds in the sample. The uniformity of spectral site distribution refers to whether the distribution of different peaks on the spectrum is uniform. If the uniformity of spectral site distribution is high, it means that the spectral peak distribution is relatively average, and the chemical compounds in the mineral sample are distributed more evenly. On the contrary, if the uniformity of spectral site distribution is low, it means that there is obvious compositional inhomogeneity in the sample. The spectral absorption peak absorbance refers to the absorbance of each peak on the spectral curve, which reflects the degree of absorption of the sample to light of a specific wavelength. The size of the absorbance can be used to locate the mineral. The relative content of different components in the material sample, as well as the absorption characteristics of each component, the number of spectral peaks and the uniformity of spectral site distribution will together affect the type and distribution uniformity of the chemical composition of the sample. An increase in the number of peaks will lead to an increase in the unevenness of the site distribution. The spectral absorption peak absorptivity is closely related to the number of spectral peaks. The absorption peak intensity of different elements or compounds on the spectrum is related to their content. Therefore, the number of peaks will also affect the size of the absorption peak absorptivity. Parameters such as the number of spectral peaks, the uniformity of spectral site distribution and the spectral absorption peak absorptivity can comprehensively reflect the spectral characteristics of the mineral sample, thereby helping to determine the material composition and structural characteristics of the mineral sample. The laser-induced breakdown index can reflect the characteristics of the mineral sample in response to laser energy under specific conditions, and then serve as an important indicator affecting the breakdown plasma effect, further assisting in the interpretation and quantification of the spectral characteristic values.

[0048] Specifically, intelligent inversion of the mineral chemical structure is performed based on the spectral characteristic values ​​of the mineral sample to obtain the chemical substance content value of the mineral sample. The specific analysis process is: obtaining the spectral characteristic values ​​of the mineral sample; matching the chemical structure combination in the mineral analysis data center based on the spectral characteristic values ​​of the mineral sample, and retrieving the chemical structure combination to obtain the types of chemical substances contained in the mineral sample; obtaining the chemical substance content value of the mineral sample based on the mineral chemical substance measurement model and the number of chemical substance types and spectral characteristic values ​​contained in the mineral sample.

[0049] It should be noted that the calculation formula of the mineral chemical substance measurement model is as follows:

[0050]

[0051] Where NH is the chemical substance content value, TZ is the spectral characteristic value, n is the number of chemical substances contained in the mineral sample, and e is a natural constant.

[0052] In a specific embodiment, the chemical substance content value is used to represent the comprehensive parameters of the content and distribution characteristics of multiple chemical substances in a mineral sample. Using the spectral characteristic values ​​of the mineral sample for chemical structure inversion is an intelligent method. Specific chemical substance content values ​​are generated through data matching and analysis, and intelligent inference of the chemical composition of the mineral sample is achieved, thereby improving the accuracy and precision of the analysis and avoiding human subjective interference. At the same time, the mineral analysis data in the data center is matched and inverted, and the chemical structure combination is matched based on the spectral characteristic values ​​to retrieve the types of chemical substances contained in the mineral sample. This process is more efficient and faster, can save time and labor costs, improve the comprehensiveness and depth of the analysis, and achieve intelligent feedback.

[0053] It should be noted that intelligent inversion of the chemical structure of minerals based on the spectral characteristic values ​​of mineral samples to obtain the chemical substances contained in the mineral samples breaks through the traditional detection consumption for determining chemical substances, and is conducive to quickly and accurately obtaining information on the chemical substances contained in the mineral samples. By performing intelligent inversion analysis on the spectral data of mineral samples, the correspondence between the elemental composition and the chemical substances in the samples, as well as the content and structure of the chemical substances, can be obtained. The chemical substance analysis results of mineral samples can help to accurately determine the type of ore deposit and mineralization laws, thereby improving the efficiency and success rate of exploration. In addition, it can also help developers of mineral resources to better understand the chemical composition and chemical properties of ores, guide mineral processing and smelting processes in the mining process, and thereby improve the mining and utilization efficiency of mineral resources and reduce mining costs.

[0054] The chemical substance retrieval and grading module is used to obtain the mineral chemical substance deviation rate based on the chemical substance content value of the mineral sample, and to mark the current mineral sample as qualified based on the mineral chemical substance deviation rate, obtain the qualified marking result, and mark the mineral grade of the mineral sample based on the qualified marking result.

[0055] Specifically, the mineral chemical substance deviation rate is obtained based on the chemical substance content value of the mineral sample, and the current mineral sample is marked as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. The specific analysis process is: obtaining the chemical substance content value of the mineral sample; obtaining the mineral chemical substance reference value set in the database based on the chemical substance content value of the mineral sample; obtaining the mineral chemical substance deviation rate based on the chemical substance content value of the mineral sample, the mineral chemical substance reference value set in the database and the mineral chemical substance content deviation model; marking the current mineral sample as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. The mineral chemical substance deviation rate is the basis for judging whether the current mineral sample is qualified and the grade.

[0056] It should be noted that the calculation formula of the mineral chemical substance content deviation model is as follows:

[0057]

[0058] In the formula, is the mineral chemical substance deviation rate, B is the mineral chemical substance standard value set in the database, NH is the chemical substance content value, and e is the natural constant.

[0059] It should be noted that the set mineral chemical substance value is extracted from the database, and a mapping set of historically measured mineral chemical substance values ​​is established based on historical data to obtain the current mineral chemical substance value. The current mineral sample is marked as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. If the mineral chemical substance deviation rate is greater than or equal to 50%, the qualified marking result of the current mineral sample is unqualified; if the mineral chemical substance deviation rate is less than 50%, the qualified marking result of the current mineral sample is qualified, thereby ensuring that the produced mineral samples meet the corresponding chemical substance standards. By quantifying the chemical substance content deviation rate, the quality of the mineral sample can be more accurately evaluated, thereby marking it as qualified. This helps to perform laser-induced breakdown and inversion again for mineral samples with excessively large mineral chemical substance deviation rates during the analysis process, thereby reducing the risk of mineral analysis errors and quality problems during the analysis process.

[0060] Specifically, the mineral samples are marked with mineral grades based on the qualified marking results, and the specific analysis process is: obtaining the mineral chemical substance deviation rate of the mineral samples whose qualified marking results are qualified; obtaining the set mineral chemical substance deviation rate interval endpoints in the database; grading based on the mineral chemical substance deviation rate of the mineral samples whose qualified marking results are qualified and the set mineral chemical substance deviation rate interval endpoints in the database; marking the mineral samples with mineral grades.

[0061] In a specific embodiment, by marking the grade of mineral samples based on the mineral chemical substance deviation rate with qualified marking results and the set mineral chemical substance deviation rate interval endpoints in the database, it is possible to achieve fine grading of the quality of mineral samples, and realize real-time intelligent feedback of mineral analysis results while performing data induction and rapid retrieval by means of classified storage. The set mineral chemical substance deviation rate interval endpoints are extracted from the database, and the current mineral chemical substance deviation rate interval endpoints are obtained by establishing a mapping set of historically measured mineral chemical substance deviation rate interval endpoints based on historical data. The unified and objective interval standard more objectively and accurately determines the grade standard of mineral samples, makes the intelligent feedback process of the analysis results more data-supported, makes data induction and retrieval faster and more efficient, and helps to optimize and manage the mineral analysis process and improve the efficiency of detection and analysis work.

[0062] The dual-track intelligent feedback module is used to provide feedback on the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark according to the grade level and store them in the mineral analysis data center, and comprehensively analyze the grade level and mineral chemical substance deviation rate to perform laser adjustment.

[0063] Specifically, the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark are fed back according to the grade and stored in the mineral analysis data center, and the grade and mineral chemical substance deviation rates are comprehensively analyzed for laser adjustment. The specific analysis process is: obtaining the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark; obtaining the corresponding data storage points in the mineral analysis data center based on the grade of the qualified mineral sample mark in the qualification mark; feeding back the mineral spectral characteristic values, chemical substance types, and chemical substance content values ​​of the qualified mineral samples based on the data storage points and storing them in the mineral analysis data center; extracting the grade and mineral chemical substance deviation rate of qualified mineral samples in the mineral analysis data center; calculating the laser ablation diameter optimization value based on the grade of the qualified mineral sample, the mineral chemical substance deviation rate and the laser induced breakdown optimization model, and performing laser adjustment, wherein the laser adjustment refers to increasing the ablation diameter in the laser induced breakdown parameters according to the laser ablation diameter optimization value.

[0064] It should be noted that the calculation formula of the laser-induced breakdown optimization model is as follows:

[0065]

[0066] In the formula, Optimized value for laser ablation diameter, is the mineral chemical deviation rate, is the grade of the mineral sample, and e is a natural constant.

[0067] It should be noted that the laser ablation diameter optimization value refers to the laser ablation diameter optimization based on the mineral chemical substance deviation rate and the grade of the mineral sample obtained from the mineral sample plasma formed by the current ultrashort pulse laser induced breakdown, which indicates the degree of increase in the ablation diameter during the original ultrashort pulse laser induced breakdown process, improves the accuracy and stability of the laser induced breakdown analysis, reduces the mineral chemical substance deviation rate, and obtains more reliable mineral analysis results. According to the optimization value calculated by the laser induced breakdown optimization model, the laser parameters are automatically adjusted to achieve precise control of the laser ablation diameter, reduce human operation errors, and improve the consistency and repeatability of the analysis. Here, only qualified mineral samples in the mineral analysis data center are extracted in order to avoid further misleading of the laser ablation diameter optimization caused by the analysis errors of unqualified mineral samples, improve the analysis efficiency and accuracy, save optimization time and the adjustment cost of laser induced breakdown. Through laser adjustment and optimization, more refined analysis and detection of mineral samples can be achieved, and the accuracy and reliability of the analysis results can be improved.

[0068] In a specific embodiment, the mineral spectral characteristic values, chemical substance types, and chemical substance content values ​​of qualified mineral samples in the mineral sample qualification mark are fed back according to the grade level and stored in the corresponding data storage point of the mineral analysis data center, and an objective and convenient data storage method is established. The qualified mineral samples in the mineral sample qualification mark are stored according to the grade level. On the one hand, with the help of classified storage, real-time intelligent feedback of mineral analysis results can be achieved while performing data induction and rapid retrieval. On the other hand, storage according to the grade level can divide the data space, save the data computing power of the mineral analysis data center, and improve data storage efficiency.

[0069] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A mineral analysis system based on online detection and intelligent feedback, characterized in that: It includes element composition detection module, synchronous spectrum inversion module, chemical substance retrieval and classification module and dual-track intelligent feedback module, among which: The element composition detection module is used to obtain the mineral element composition content table and the laser induced breakdown index; The specific analysis process of obtaining the mineral element content table includes: Performing ultrashort pulse laser induced breakdown on the mineral sample to excite the surface plasma of the mineral sample, performing elemental composition detection based on the surface plasma of the mineral sample, and obtaining plasma elemental composition detection result parameters, wherein the plasma elemental composition detection result parameters include elemental composition type and elemental composition content; Sort the elemental components based on their content and calculate the proportion of each elemental component to establish a mineral elemental content table; Obtain the laser induced breakdown index. The specific analysis process is as follows: Obtaining environmental purity parameters during ultrashort pulse laser induced breakdown, wherein the environmental purity parameters include the luminous flux of visible light received per unit area, the content of active microorganisms, the flow rate of environmental gas, and the noise frequency; Obtaining a breakdown environmental purity grade based on an environmental purity grade assessment model and environmental purity parameters; Acquire a laser-induced breakdown environment addition value set in a database based on the breakdown environment purity level; Obtaining laser induced breakdown parameters during the ultrashort pulse laser induced breakdown process, wherein the laser induced breakdown parameters include air cooling efficiency of the laser machine, pulse energy, pulse width, and ablation diameter; Obtaining a laser induced breakdown index based on the laser induced parameters and the laser induced breakdown environment addition value set in the database; The calculation formula of the laser induced breakdown index is: Where J is the laser-induced breakdown index, f is the air cooling efficiency of the laser machine, m is the pulse energy, d is the pulse width, z is the ablation diameter, is the laser-induced breakdown environment addition value set in the database, and e is a natural constant; The synchronous spectral inversion module is used to calculate the spectral characteristic values ​​of the mineral sample based on the mineral element composition content table and the laser induced breakdown index, perform intelligent inversion of the mineral chemical structure based on the spectral characteristic values ​​of the mineral sample, and obtain the chemical substance content value of the mineral sample; The spectral characteristic values ​​of the mineral samples are calculated based on the mineral element content table and the laser-induced breakdown index. The specific analysis process is as follows: Obtain the types of elemental components that account for more than 1% of the elemental content in the mineral elemental content table; Acquiring a spectral image of the plasma, wherein the spectral image of the plasma reflects the spectral characteristics of the mineral sample; Acquire spectral characteristic parameters of a material sample of an elemental component type whose elemental component content accounts for more than 1% based on the spectral image of the plasma, wherein the spectral characteristic parameters of the material sample include the number of spectral peaks, the uniformity of spectral site distribution, and the spectral absorption peak absorptivity; The calculation formula of the spectral characteristic value is: Where, TZ is the spectral characteristic value, G is the number of spectral peaks, Y is the uniformity of spectral site distribution, X is the absorptivity of the spectral absorption peak, J is the laser-induced breakdown index, and e is a natural constant; The intelligent inversion of the mineral chemical structure is performed based on the spectral characteristic values ​​of the mineral sample to obtain the chemical substance content value of the mineral sample. The specific analysis process is as follows: Obtain spectral characteristic values ​​of mineral samples; Based on the spectral characteristic values ​​of the mineral sample, a chemical structure combination is matched in the mineral analysis data center, and the chemical structure combination is retrieved to obtain the types of chemical substances contained in the mineral sample; Obtaining the chemical substance content value of the mineral sample based on the mineral chemical substance measurement model and the number of chemical substance types and spectral characteristic values ​​contained in the mineral sample; The calculation formula of the mineral chemical substance calculation model is as follows: In the formula, NH is the chemical substance content value, TZ is the spectral characteristic value, n is the number of chemical substances contained in the mineral sample, and e is the natural constant; The chemical substance retrieval and grading module is used to obtain the mineral chemical substance deviation rate based on the chemical substance content value of the mineral sample, and to perform a qualified mark on the current mineral sample based on the mineral chemical substance deviation rate, obtain a qualified mark result, and perform a mineral grade mark on the mineral sample based on the qualified mark result; The dual-track intelligent feedback module is used to provide feedback on the mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark according to the grade level and store them in the mineral analysis data center, and comprehensively analyze the grade level and mineral chemical substance deviation rate to perform laser adjustment.

2. The mineral analysis system based on online detection and intelligent feedback according to claim 1, characterized in that: The mineral chemical substance deviation rate is obtained based on the chemical substance content value of the mineral sample, and the current mineral sample is qualified marked based on the mineral chemical substance deviation rate to obtain a qualified marking result. The specific analysis process is: Obtain the chemical content values ​​of mineral samples; Acquire the value of the mineral chemical substance mark set in the database based on the chemical substance content value of the mineral sample; Based on the chemical substance content value of the mineral sample, the mineral chemical substance standard value set in the database and the mineral chemical substance content deviation model, the mineral chemical substance deviation rate is obtained; The current mineral sample is marked as qualified based on the mineral chemical substance deviation rate to obtain a qualified marking result. The mineral chemical substance deviation rate is the basis for judging whether the current mineral sample is qualified and the grade classification.

3. The mineral analysis system based on online detection and intelligent feedback according to claim 2, characterized in that: The mineral grade of the mineral sample is marked based on the qualified marking result, and the specific analysis process is as follows: Obtaining the mineral chemical substance deviation rate of the mineral sample with a qualified marking result; Obtaining the endpoints of the set mineral chemical substance deviation rate interval in the database; Grade the mineral samples based on the mineral chemical substance deviation rate of the mineral samples with qualified qualification marks and the mineral chemical substance deviation rate interval endpoints set in the database; Mineral samples are labeled with mineral grade.

4. The mineral analysis system based on online detection and intelligent feedback according to claim 1, characterized in that: The mineral samples qualified in the mineral sample qualified mark are fed back with mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates according to the grade level and stored in the mineral analysis data center. The grade level and mineral chemical substance deviation rate are comprehensively analyzed for laser adjustment. The specific analysis process is as follows: Obtaining mineral spectral characteristic values, chemical substance types, chemical substance content values, and mineral chemical substance deviation rates of qualified mineral samples in the mineral sample qualification mark; Acquire the corresponding data storage point in the mineral analysis data center based on the grade of the qualified mineral sample mark in the qualified mark; Feedback and store the mineral spectrum characteristic values, chemical substance types, and chemical substance content values ​​of the qualified mineral samples in the mineral analysis data center based on the data storage point; Extract the grade level and mineral chemical deviation rate of qualified mineral samples in the mineral analysis data center; Based on the grade of the qualified mineral sample, the mineral chemical substance deviation rate and the laser induced breakdown optimization model, the laser ablation diameter optimization value is calculated, and laser adjustment is performed. The laser adjustment refers to increasing the ablation diameter in the laser induced breakdown parameters according to the laser ablation diameter optimization value.

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