Intelligent ore dressing control system based on big data

Abstract

The invention relates to an intelligent beneficiation control system based on big data, which is applied to the technical field of beneficiation, and comprises a data acquisition and transmission unit, a data analysis and decision unit and an execution control and feedback unit, the data acquisition and transmission unit comprises a data acquisition module and a data transmission module, and the data analysis and decision unit comprises a special library modeling module and a data analysis module. According to the intelligent mineral separation control system, experience knowledge of experts in the mineral separation field is fully fused, so that when facing complex and changeable mineral separation working conditions, the system can accurately make decisions according to mineral separation data and other factors like guidance of professional mineral separation teams aside; and the control instruction is generated according to the decision, and the ore dressing equipment is controlled to execute the corresponding operation according to the control instruction, so that the complex ore dressing process can be effectively and accurately controlled, the intelligent level of ore dressing production can be remarkably improved, and the ore dressing efficiency and the product quality are improved.

Description

Technical Field

[0001] The present invention relates to a control system, and in particular to an intelligent mineral processing control system based on big data applied in the field of mineral processing technology. Background Art

[0002] With the rapid development of information technologies such as the Industrial Internet, big data, and cloud computing, the process industry faces the thorny challenge of integrating advanced information technologies with traditional control systems to achieve intelligent control systems. Mineral processing, a typical process industry, often suffers from poor production controllability due to the variable properties of raw ore. In particular, in key processes such as grinding, magnetic separation, and concentration and filter pressing, numerous parameters and factors influence operational and production indicators. The constant changes in production operations and factors often lead to unstable production conditions and low labor efficiency, severely restricting the development of mineral processing companies.

[0003] The invention patent with publication number CN118807969A discloses an intelligent control method and system for mineral processing. The invention achieves the purpose of intelligent control of mineral processing indicators by building an intelligent terminal platform for mineral processing and establishing complete process detection and execution control functions, reducing the dependence of mineral processing indicators on manual operation and manual decision-making, and improving the stability of production processes and indicators.

[0004] The invention patent with publication number CN116681199A discloses a smart mine beneficiation system. The invention uses communication and information technology and artificial intelligence technology to establish and implement the enterprise intelligent manufacturing system architecture, realize accurate perception and precise control of the entire production process, and form a collaborative management and control system based on standardization, leanness, digitization, automation, and intelligence, so as to achieve the enterprise's goal of improving production efficiency.

[0005] Mineral processing experts, drawing on their extensive experience and expertise, possess a profound understanding of the various phenomena and issues encountered during the mineral processing process. Based on factors such as ore characteristics and production conditions, they can accurately determine the appropriate adjustment direction for process parameters, promptly identify potential problems, and propose effective solutions. However, existing mineral processing control systems fail to fully utilize this valuable resource, resulting in limited intelligent control capabilities and difficulty in precisely controlling complex mineral processing processes. Therefore, we propose an intelligent mineral processing control system based on big data. Summary of the Invention

[0006] In view of the above-mentioned prior art, the technical problem to be solved by the present invention is that the mineral processing control system in the prior art fails to fully utilize the valuable resource of the experience and knowledge of experts in the mineral processing field, resulting in its limited intelligent control level and difficulty in coping with the complex and changeable situations in the mineral processing process.

[0007] To solve the above problems, the present invention provides an intelligent ore dressing control system based on big data, which includes a data acquisition and transmission unit, an analysis and decision execution unit, and an execution control and feedback unit; The data acquisition and transmission unit includes a data acquisition module and a data transmission module. The analysis and decision execution unit includes a special database modeling module and a data analysis module. The execution control and feedback unit includes an execution control module; The data acquisition module is used to acquire ore dressing data, which includes but is not limited to: raw ore property data, grinding process data, magnetic separation process data, thickening and pressure filtration process data, and the operating status data of ore dressing equipment; The data transmission module is used to transmit the ore dressing data acquired by the data acquisition module to the data analysis module in real time through a communication method combining wired and wireless; The special database modeling module is used to construct an expert knowledge base model according to the experience knowledge of experts in the ore dressing field and industry standard specifications; The data analysis module is used to analyze the ore dressing data through big data analysis technology, make intelligent decisions according to the analysis results and the expert knowledge base model, and generate control instructions according to the decisions; The execution control module is used to send the control instructions generated by the data analysis module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instructions.

[0008] In the above intelligent ore dressing control system based on big data, the experience knowledge of experts in the ore dressing field is fully integrated, so that when the system faces complex and changeable ore dressing working conditions, it can accurately make decisions according to factors such as ore dressing data, just like having a professional ore dressing team guiding beside, thus being able to effectively and precisely control the complex ore dressing process, and further significantly improving the intelligent level of ore dressing production, as well as improving ore dressing efficiency and product quality.

[0009] As a further improvement of the present application, the data acquisition and transmission unit further includes a data storage module. The data transmission module will also transmit the ore dressing data acquired by the data acquisition module to the data storage module, and the data storage module is used to classify and store the ore dressing data.

[0010] As another improvement of the present application, the intelligent ore dressing control system further includes an index monitoring and analysis unit. The index monitoring and analysis unit includes an index monitoring module, an index setting module, and an analysis and control decision-making module. The index monitoring module is used to monitor the ore dressing indexes in real time, and the index setting module is used to set the index target values.

[0011] As a supplement to another improvement of this application, the index analysis and strategy formulation module is used to compare and analyze the actual index monitored by the index monitoring module with the index target value, determine whether there is a deviation between the actual index and the index target value. When there is a deviation, the cause of the deviation is analyzed through the expert knowledge base model, and an adjustment strategy is formulated according to the result of the deviation cause analysis. Then, a control instruction is generated according to the adjustment strategy. The execution control module is also used to send the control instruction generated by the index analysis and strategy formulation module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instruction.

[0012] As a supplement to another improvement of this application, the execution control and feedback unit further includes an execution feedback module, which is used to monitor the execution situation of the ore dressing equipment for the control instruction and feedback the execution result to the data analysis module and the index analysis and strategy formulation module.

[0013] As another improvement of this application, the intelligent ore dressing control system further includes an integrated coordination unit. The integrated coordination unit includes a priority setting module and a conflict judgment and coordination module. The priority setting module is used to set the priorities of the control instructions generated by the data analysis module and the control instructions generated by the index analysis and strategy formulation module.

[0014] As a supplement to another improvement of this application, before sending the control instructions generated by the data analysis module and the control instructions generated by the index analysis and strategy formulation module to the ore dressing equipment, the execution control module will first send the control instructions to the conflict judgment and coordination module. The conflict judgment and coordination module is used to judge whether there is a conflict between the control instructions generated by the data analysis module and the control instructions generated by the index analysis and strategy formulation module. When the judgment result is no conflict, the conflict judgment and coordination module sends an acknowledgment signal to the execution control module, so that the execution control module directly sends the control instructions to the corresponding ore dressing equipment. When the judgment result is that there is a conflict, the conflict judgment and coordination module sends a guiding signal to the execution control module according to the priority of the control instructions, guiding the execution control module to select the control instruction with a higher priority among the conflicting control instructions and send it to the corresponding ore dressing equipment.

[0015] As a supplement to another improvement of this application, the integrated coordination unit further includes a display, conflict reminder and suggestion module with visualization display function and reminder function. When the judgment result is that there is a conflict, the conflict judgment and coordination module will also control the display, conflict reminder and suggestion module to send a reminder to relevant technical personnel, and control the display, conflict reminder and suggestion module to display relevant information about the control instruction conflict to relevant technical personnel, so that relevant technical personnel record the relevant information and regularly organize meetings of experts in the ore dressing field for discussion and research. Then, the expert knowledge base model is optimized according to the meeting results.

[0016] In summary, the intelligent ore dressing control system in this application fully integrates the experience and knowledge of experts in the ore dressing field. When facing complex and changeable ore dressing working conditions, the system can accurately make decisions based on factors such as ore dressing data, just like having a professional ore dressing team guiding beside. It generates control instructions according to the decisions, and controls the ore dressing equipment to perform corresponding operations according to the control instructions, so as to effectively and precisely control the complex ore dressing process, thereby significantly improving the intelligent level of ore dressing production, as well as the ore dressing efficiency and product quality. Through the setting of the index monitoring and analysis unit, the intelligent ore dressing control system in this application also has the function of monitoring and analyzing ore dressing indexes. When there is a deviation between the actual index and the target value of the index, the deviation cause can be analyzed through the expert knowledge base model, and an adjustment strategy can be formulated according to the result of the deviation cause analysis, so as to further improve the intelligent level of ore dressing production, as well as the ore dressing efficiency and product quality. Through the setting of the comprehensive coordination unit, it can effectively avoid the instruction conflicts generated by the data analysis module and the index analysis and strategy formulation module, ensure that the instructions received by the ore dressing equipment are consistent and reasonable, and at the same time promote the optimization of the expert knowledge base model. This collaborative mechanism not only ensures the stable operation of the system, but also improves the adaptability and intelligence of the system to the complex production environment, enabling the system to continuously optimize and work efficiently during long-term operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is the system structure block diagram of the intelligent ore dressing control system based on big data in the first embodiment of this application; Figure 2 is the system structure block diagram of the data acquisition and transmission unit in the first embodiment of this application; Figure 3 is the system structure block diagram of the data analysis, decision-making and execution unit and the execution control and feedback unit in the first embodiment of this application; Figure 4 is the system structure block diagram of the intelligent ore dressing control system based on big data in the second embodiment of this application; Figure 5 is the system structure block diagram of the index monitoring and analysis unit in the second embodiment of this application; Figure 6 is the system structure block diagram of the execution control and feedback unit in the second embodiment of this application; Figure 7 is the system structure block diagram of the comprehensive coordination unit in the third embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will make a detailed description of the three embodiments of this application with reference to the drawings.

[0019] The first embodiment: Figures 1 - 3Disclosed is an intelligent ore dressing control system based on big data, including a data acquisition and transmission unit, an analysis and decision execution unit, and an execution control and feedback unit; The data acquisition and transmission unit includes a data acquisition module and a data transmission module. The analysis and decision execution unit includes a special database modeling module and a data analysis module. The execution control and feedback unit includes an execution control module; The data acquisition module is used to acquire ore dressing data, which includes but is not limited to: raw ore property data (such as ore grade, particle size distribution, etc.), grinding process data (such as mill load, feed rate, discharge concentration, etc.), magnetic separation process data (such as magnetic field intensity, pulp flow rate, etc.), thickening and pressure filtration process data (such as pulp concentration, cake thickness, etc.), and ore dressing equipment operation status data (such as ore dressing equipment temperature, vibration, etc.); The data transmission module is used to transmit the ore dressing data collected by the data acquisition module to the data analysis module in real time through a communication method combining wired and wireless. For key data and data with high real-time requirements, wired Ethernet transmission is adopted to ensure the stability and low latency of data transmission. For data with a wide distribution range and difficult wiring, wireless transmission technology is adopted; The special database modeling module is used to construct an expert knowledge base model according to the experience knowledge of experts in the ore dressing field and industry standard specifications; The data analysis module is used to analyze the ore dressing data through big data analysis technology, make intelligent decisions according to the analysis results and the expert knowledge base model, and generate control instructions according to the decisions. For example, during the grinding process, according to data such as mill load and feed particle size, combined with expert knowledge, decide whether to adjust operation parameters such as feed rate and mill speed; The execution control module is used to send the control instructions generated by the data analysis module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instructions.

[0020] In the intelligent ore dressing control system of this application, the experience knowledge of experts in the ore dressing field is fully integrated, so that when the system faces complex and changeable ore dressing working conditions, it can accurately make decisions according to factors such as ore dressing data like having a professional ore dressing team guiding beside, generate control instructions according to the decisions, and control the ore dressing equipment to perform corresponding operations according to the control instructions, thereby being able to effectively control the complex ore dressing process precisely, and then significantly improving the intelligent level of ore dressing production, and improving ore dressing efficiency and product quality.

[0021] The data acquisition and transmission unit further includes a data storage module. The data transmission module also transmits the ore dressing data collected by the data acquisition module to the data storage module. The data storage module is used to classify and store the ore dressing data for subsequent data management and analysis.

[0022] The second implementation method: Please refer toFigures 4 - 6 , different from the first embodiment, the intelligent ore dressing control system further includes an index monitoring and analysis unit, which includes an index monitoring module, an index setting module, and an index analysis and strategy formulation module. The index monitoring module is used to monitor ore dressing indexes (such as concentrate grade, tailings grade, recovery rate, grinding fineness, etc.) in real time, and the index setting module is used to set the target values of the indexes.

[0023] The index analysis and strategy formulation module is used to compare and analyze the actual indexes monitored by the index monitoring module with the target values of the indexes, and judge whether there is a deviation between the actual indexes and the target values of the indexes. When there is a deviation, the expert knowledge base model is used to analyze the cause of the deviation, and an adjustment strategy is formulated according to the result of the deviation cause analysis. For example, if it is found through analysis that the low concentrate grade is due to the relatively coarse particle size of the grinding product and the inappropriate magnetic separation magnetic field intensity, then the adjustment strategy may include adjusting the grinding and classification parameters (such as increasing the feed amount of the mill, increasing the rotation speed of the classifier, etc.) and optimizing the magnetic separation process parameters (such as appropriately increasing the magnetic field intensity). Then, a control instruction is generated according to the adjustment strategy, and the execution control module is also used to send the control instruction generated by the index analysis and strategy formulation module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instruction.

[0024] Through the setting of the index monitoring and analysis unit, the intelligent ore dressing control system in this application also has the function of monitoring and analyzing ore dressing indexes. And when there is a deviation between the actual indexes and the target values of the indexes, the expert knowledge base model can be used to analyze the cause of the deviation, and an adjustment strategy is formulated according to the result of the deviation cause analysis, so as to further improve the intelligent level of ore dressing production, and further improve the ore dressing efficiency and product quality.

[0025] The execution control and feedback unit further includes an execution feedback module, which is used to monitor the execution situation of the control instruction by the ore dressing equipment and feedback the execution result to the data analysis module and the index analysis and strategy formulation module for further optimization and adjustment.

[0026] The third embodiment: Please refer to Figure 7, different from the first and second embodiments, the intelligent ore dressing control system further includes a comprehensive coordination unit, which includes a priority setting module and a conflict judgment and coordination module. The priority setting module is used to set the priorities of the control instructions generated by the data analysis module and the control instructions generated by the analysis and standard-making policy module. Before sending the control instructions generated by the data analysis module and the control instructions generated by the analysis and standard-making policy module to the ore dressing equipment, the execution control module will first send the control instructions to the conflict judgment and coordination module. The conflict judgment and coordination module is used to judge whether there is a conflict between the control instructions generated by the data analysis module and the control instructions generated by the analysis and standard-making policy module. When the judgment result is no conflict, the conflict judgment and coordination module sends an acknowledgment signal to the execution control module, enabling the execution control module to directly send the control instructions to the corresponding ore dressing equipment. When the judgment result is that there is a conflict, the conflict judgment and coordination module sends a guidance signal to the execution control module according to the priorities of the control instructions, guiding the execution control module to select the control instruction with a higher priority from the conflicting control instructions and send it to the corresponding ore dressing equipment (the conflicting instruction with a lower priority is not sent to the ore dressing equipment).

[0027] The comprehensive coordination unit further includes a display and conflict reminder module with visualization display and reminder functions. When the judgment result is that there is a conflict, the conflict judgment and coordination module will also control the display and conflict reminder module to send a reminder to relevant technical personnel, and control the display and conflict reminder module to display relevant information about the control instruction conflict to relevant technical personnel, causing relevant technical personnel to record the relevant information and regularly organize meetings for discussion and research by experts in the ore dressing field. Then, the expert knowledge base model is optimized according to the meeting results.

[0028] Through the setting of the comprehensive coordination unit, it is possible to effectively avoid conflicts between the instructions generated by the data analysis module and the analysis and standard-making policy module, ensure that the instructions received by the ore dressing equipment are consistent and reasonable, and at the same time promote the optimization of the expert knowledge base model. This collaborative mechanism not only guarantees the stable operation of the system, but also improves the adaptability and intelligence of the system to complex production environments, enabling the system to continuously optimize and work efficiently during long-term operation.

[0029] Combined with the current actual requirements, the above-mentioned embodiments adopted in this application, the protection scope is not limited thereto. Within the knowledge scope of those skilled in the art, various changes made without departing from the concept of this application still fall within the protection scope of the present invention.

Claims

1. An intelligent ore dressing control system based on big data, characterized in that It includes a data acquisition and transmission unit, a data analysis and decision execution unit, and an execution control and feedback unit; The data acquisition and transmission unit includes a data acquisition module and a data transmission module. The data analysis and decision execution unit includes a specialized database modeling module and a data analysis module. The execution control and feedback unit includes an execution control module; The data acquisition module is used to acquire ore dressing data, and the ore dressing data includes, but is not limited to: raw ore property data, grinding process data, magnetic separation process data, thickening and pressure filtration process data, and the operating status data of ore dressing equipment; The data transmission module is used to transmit the ore dressing data collected by the data acquisition module to the data analysis module in real time through a communication method combining wired and wireless; The specialized database modeling module is used to build an expert knowledge base model according to the experience knowledge of experts in the ore dressing field and industry standard specifications; The data analysis module is used to analyze the ore dressing data through big data analysis technology, make intelligent decisions based on the analysis results and the expert knowledge base model, and generate control instructions according to the decisions; The execution control module is used to send the control instructions generated by the data analysis module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instructions.

2. The intelligent ore dressing control system based on big data according to claim 1, wherein The data acquisition and transmission unit further includes a data storage module. The data transmission module also transmits the ore dressing data collected by the data acquisition module to the data storage module, and the data storage module is used to classify and store the ore dressing data.

3. The intelligent ore dressing control system based on big data according to claim 1, wherein It further includes an index monitoring and analysis unit. The index monitoring and analysis unit includes an index monitoring module, an index setting module, and an index analysis and control strategy module. The index monitoring module is used to monitor the ore dressing indexes in real time, and the index setting module is used to set the target values of the indexes.

4. An intelligent ore dressing control system based on big data according to claim 3, characterized in that, The index analysis and control strategy module is used to compare and analyze the actual indexes monitored by the index monitoring module with the target values of the indexes, judge whether there is a deviation between the actual indexes and the target values of the indexes. When there is a deviation, analyze the cause of the deviation through the expert knowledge base model, formulate an adjustment strategy according to the results of the deviation cause analysis, and then generate control instructions according to the adjustment strategy. The execution control module is also used to send the control instructions generated by the index analysis and control strategy module to the corresponding ore dressing equipment, so that the ore dressing equipment performs corresponding operations according to the control instructions.

5. An intelligent ore dressing control system based on big data according to claim 4, characterized in that, The execution control and feedback unit further includes an execution feedback module, which is used to monitor the execution situation of the control instructions by the ore dressing equipment and feedback the execution results to the data analysis module and the index analysis and control strategy module.

6. An intelligent ore dressing control system based on big data according to claim 4, characterized in that It further includes a comprehensive coordination unit. The comprehensive coordination unit includes a priority setting module and a conflict judgment and coordination module. The priority setting module is used to set the priorities of the control instructions generated by the data analysis module and the control instructions generated by the index analysis and control strategy module.

7. An intelligent ore dressing control system based on big data according to claim 6, characterized in that, Before sending the control instructions generated by the data analysis module and the control instructions generated by the analysis and standard-making policy module to the ore dressing equipment, the execution control module first sends the control instructions to the conflict judgment and coordination module. The conflict judgment and coordination module is used to judge whether there is a conflict between the control instructions generated by the data analysis module and the control instructions generated by the analysis and standard-making policy module. When the judgment result is no conflict, the conflict judgment and coordination module sends an acknowledgment signal to the execution control module, enabling the execution control module to directly send the control instructions to the corresponding ore dressing equipment. When the judgment result is that there is a conflict, the conflict judgment and coordination module sends a guidance signal to the execution control module according to the priority of the control instructions, guiding the execution control module to select the control instruction with a higher priority from the conflicting control instructions and send it to the corresponding ore dressing equipment.

8. An intelligent ore dressing control system based on big data according to claim 7, characterized in that, The comprehensive coordination unit further includes a display and conflict reminder module with visualization display function and reminder function. When the judgment result is that there is a conflict, the conflict judgment and coordination module also controls the display and conflict reminder module to send a reminder to relevant technical personnel, and controls the display and conflict reminder module to display relevant information about the control instruction conflict to relevant technical personnel, causing the relevant technical personnel to record the relevant information, and regularly organizing meetings of experts in the ore dressing field for discussion and research, and then optimizing the expert knowledge base model according to the meeting results.

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