Coal mine area management system and method based on digital twinning

Abstract

The invention relates to the technical field of coal mine area management, in particular to a coal mine area management system and method based on digital twinning, and the system comprises an information collection module which collects parameter information of a coal mine area; the digital twinborn model building module is used for mapping the coal mine area real object into a virtual space and building a digital twinborn model; the dynamic tracking and predicting module is used for monitoring the information change condition of each parameter of the coal mine area, synchronously mapping the information change condition to the virtual space, updating the digital twinborn model of the coal mine area and performing data prediction; the fault early warning module is used for judging whether the prediction information is in a normal value range or not, if so, performing fault early warning, positioning a fault area, and performing fault diagnosis and early warning; and the man-machine interaction module is used for displaying the dynamic tracking and prediction result of the coal mine area in real time and performing instruction feedback on parameter operation of the coal mine area. The technical problems that coal mine area management in the prior art highly depends on manual inspection, efficiency is low, cost is high, and intelligent early warning capacity is lacked are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine area management, and in particular to a coal mine area management system and method based on digital twins. Background Art

[0002] Coal mining is a high-risk industry. Coal mining area management is a complex and important task, involving multiple aspects such as safe production, environmental protection, resource utilization, and personnel management. Open-pit coal mining faces a variety of safety risks in the production process, including unstable geological environment, safety management of staff, equipment failure, and environmental monitoring. These problems often lead to frequent safety accidents due to untimely information collection, inaccurate data analysis, and delayed response measures. Especially in economically underdeveloped areas, there is no online information collection and monitoring system for production enterprise risk points, which is highly dependent on manual inspections and monitoring. Most manual inspections rely on experience and intuition and lack scientific basis. After manual safety hazards are discovered, they need to be reported layer by layer. The labor cost is high and the efficiency is low. It is easy to miss inspections and delays, and there is a lack of intelligent early warning capabilities, and potential risks cannot be discovered in advance. In addition, since the traditional coal mining area management method relies heavily on manual records, it is difficult to fully grasp the real-time status of the mining area. Summary of the invention

[0003] The purpose of the present invention is to provide a coal mine area management system and method based on digital twins, so as to solve the technical problems in the prior art that coal mine area management is highly dependent on manual inspections, has high efficiency and low cost, and lacks intelligent early warning capabilities.

[0004] The present invention is achieved through the following technical solutions:

[0005] In a first aspect, the present invention provides a coal mine area management system based on digital twin, comprising:

[0006] Information collection module: collects information on various parameters of the coal mining area and uploads the collected information to the digital twin model construction module;

[0007] Digital twin model construction module: digitally process the parameter information of the coal mining area through digital twin technology, map the real objects in the coal mining area into the virtual space, and build a digital twin model of the coal mining area;

[0008] Dynamic tracking and prediction module: Use the monitoring system to monitor the changes in various parameter information in the coal mining area in real time, and synchronously map the real-time parameter information to the virtual space, update the digital twin model of the coal mining area, and predict the gas data of each area in the coal mining area at the same time, and send the predicted data to the fault warning module;

[0009] Fault warning module: Receives the prediction data sent by the dynamic tracking and prediction module, determines whether the prediction data is within the normal value range, and issues a fault warning if it exceeds the normal value range. At the same time, it combines the synchronous mapping performance of the digital twin technology with the fault diagnosis technology to locate the fault area on the digital twin model, and conducts fault diagnosis and warning.

[0010] Human-computer interaction module: provides a human-computer interaction port, displays the dynamic tracking and fault warning results of the coal mine area in real time, and provides command feedback on the operation of various parameters in the coal mine area in a human-computer operation mode.

[0011] Furthermore, sensors are installed on various equipment and monitoring points in the coal mining area. The information collection module receives parameter information uploaded by the sensors. At the same time, the historical operation data of the coal mining area, alarm information, personnel and vehicle information in the mining area, and the normal value range of each parameter are uploaded to the information collection module through the human-computer interaction module to complete the collection of various parameter information in the coal mining area.

[0012] Furthermore, it also includes a perception monitoring module, which uses the Internet of Things technology to perform real-time perception and monitoring of production equipment and buildings in the coal mining area, and the perception monitoring module transmits the perception monitoring results to the information collection module in real time.

[0013] Furthermore, in the dynamic tracking and prediction module, machine learning and artificial intelligence technologies are used to learn and build a prediction model from historical data, and the prediction model is used to predict the data of each area in the coal mining area.

[0014] Furthermore, the prediction model can perform gas outburst prediction, and the gas outburst prediction steps are as follows:

[0015] S1, import the original data of coal and gas outburst, and use Kmeans-SMOTE algorithm to generate a data balance data set;

[0016] S2, cluster the data;

[0017] S3, oversampling using SMOTE;

[0018] S4, calculate the position of the pathfinder using the PFA algorithm;

[0019] S5, update the pathfinder position;

[0020] S6, determine whether the iteration requirements are met, if so, perform model training and build an improved Kmeans-SMOTE-RF prediction model, if not, return to S3;

[0021] S7. Optimize the parameters of the prediction model to obtain the optimal model and output the prediction results.

[0022] Furthermore, the S5 further includes:

[0023] S51. Pull the out-of-bounds population back to the border;

[0024] S52, determine whether it exceeds the boundary, if so, return to S51, if not, update the position of the pathfinder.

[0025] Furthermore, it also includes a fault alarm module, which monitors the deviation between the twin and the physical entity in real time, issues a fault alarm when the deviation is greater than a normal range, and notifies the operator through the human-computer interaction module.

[0026] Furthermore, a data-driven model is established, which is driven by statistical analysis methods and deep learning algorithms to mine the characteristics of historical data, predict future data changes based on current data, and integrate data prediction results and measured data to optimize the digital twin model.

[0027] Furthermore, the digital twin model is presented in real time on the human-computer interaction port through visualization technology.

[0028] In a second aspect, a coal mine area management method based on digital twin is provided, the method comprising:

[0029] S1. Collect various parameter information of coal mining area;

[0030] S2. Use digital twin technology to digitize the parameter information of the coal mining area, map the real objects in the coal mining area into the virtual space, and build a digital twin model of the coal mining area;

[0031] S3. Use the monitoring system to monitor the changes in various parameter information in the coal mining area in real time, and synchronously map the real-time parameter information to the virtual space, update the digital twin model of the coal mining area, and predict the data of each area in the coal mining area;

[0032] S4. Determine whether the predicted data information is within the normal value range. If it exceeds the normal value range, a fault warning is issued. At the same time, the synchronous mapping performance of the digital twin technology is combined with the fault diagnosis technology to locate the fault area, perform fault diagnosis and warning;

[0033] S5. Provide a human-computer interaction port to display the dynamic tracking and prediction results of the coal mining area in real time, and provide command feedback on the operation of various parameters in the coal mining area in a human-computer operation mode.

[0034] The technical solution of the present invention has at least the following advantages and beneficial effects:

[0035] (1) The present invention uses digital twin technology to achieve comprehensive monitoring and management of coal mining areas, with a high degree of automation and comprehensive monitoring and management coverage, eliminating manual inspections that rely on experience and intuition and lack scientific basis, thereby reducing labor costs;

[0036] (2) Through the human-computer interaction port, the dynamic tracking and prediction results of the coal mine area are displayed in real time, and the operation of various parameters in the coal mine area is commanded and fed back in a human-computer operation mode, with rapid and efficient feedback;

[0037] (3) Intelligent warning is provided through the fault warning module to reduce the probability of danger and failure, and protect the life safety of staff and the property safety of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 An overall schematic diagram of a coal mine area management system based on digital twin provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, 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 part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0041] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0042] Example 1

[0043] In this embodiment, if Figure 1 As shown in the figure, a coal mine area management system based on digital twin is established, which includes an information collection module, a digital twin model construction module, a dynamic tracking and prediction module, a fault warning module, a human-computer interaction module and a fault alarm module.

[0044] Specifically, the information collection module also includes: sensors are arranged on various equipment and monitoring points in the coal mining area, the information collection module receives parameter information uploaded by the sensors, and at the same time uploads the historical operation data of the coal mining area, alarm information, personnel and vehicle information in the mining area, and the normal value range of each parameter to the information collection module through the human-computer interaction module, completes the collection of various parameter information in the coal mining area, and builds a perception monitoring module. The perception monitoring module uses the Internet of Things technology to perform real-time perception and monitoring of production equipment and buildings in the coal mining area, and transmits the perception monitoring results to the information collection module in real time. The information collection module uploads the collected information to the digital twin model construction module.

[0045] Specifically, in this embodiment, the digital twin model construction module digitizes the parameter information of the coal mining area through digital twin technology, maps the real objects in the coal mining area into the virtual space, builds a digital twin model of the coal mining area, and simultaneously integrates historical data with current data for training and analysis to obtain the data change rules and realize the learning twin of the digital twin model.

[0046] Specifically, in this embodiment, the dynamic tracking and prediction module also includes building a prediction model, and predicting the data of each area of ​​the coal mining area through the prediction model, wherein the prediction model is constructed using artificial intelligence technology and machine learning algorithms, and a sufficient amount of historical data is input using a data acquisition module and a human-computer interaction port. The prediction model learns and improves the historical data to increase the reliability of the prediction, and the prediction of various parameters of the coal mining area is completed using the prediction model. The prediction model can predict gas outbursts, and the gas outburst prediction steps are as follows:

[0047] 1. Import the original data of coal and gas outburst, and use the Kmeans-SMOTE algorithm to generate a data balance data set;

[0048] 2. Cluster the data;

[0049] 3. Use SMOTE for oversampling;

[0050] 4. Use the PFA algorithm to calculate the position of the pathfinder;

[0051] 5. Pull the out-of-bounds population back to the border;

[0052] 6. Determine whether it exceeds the boundary. If so, return to S51. If not, update the position of the pathfinder.

[0053] 7. Determine whether the iteration requirements are met. If so, perform model training and build an improved Kmeans-SMOTE-RF prediction model. Otherwise, return to S3.

[0054] 8. Optimize the parameters of the prediction model to obtain the optimal model;

[0055] 9. Output the prediction results.

[0056] Specifically, in this embodiment, a fault alarm module is also included. The fault alarm module monitors the deviation between the twin and the physical entity in real time. When the deviation is greater than the normal range, a fault alarm is issued and the operator is notified through the human-computer interaction module.

[0057] Specifically, in this embodiment, the fault warning module is used to receive the prediction information sent by the dynamic tracking and prediction module, and determine whether the prediction information is within the normal value range. If it exceeds the normal value range, a fault warning is issued. At the same time, the synchronous mapping performance of the digital twin technology is combined with the fault diagnosis technology to locate the fault area and perform fault diagnosis and warning.

[0058] Specifically, in this embodiment, the human-computer interaction module includes a visual LED display screen, which displays in real time the dynamic change image of the coal mining area, the current and predicted parameter information of each monitoring point, alarm prompts and early warning prompts. Operators can obtain fault location information through the visual LED display screen, go to the site for investigation and verification, and handle the fault. For some equipment that can be directly operated online, the human-computer interaction port can also be used to directly provide command feedback on the operation of related parameters, saving operation time, improving efficiency, reducing manpower and saving costs.

[0059] Example 2

[0060] In this embodiment, a coal mine area management method based on digital twin is provided, and the method specifically comprises the following steps:

[0061] 1. Collect various parameter information of coal mine area through information collection module. First, set sensors on various equipment and monitoring points in coal mine area, including exhaust vents, drilling machines, loaders, engineering transport vehicles, stripping equipment, large conveyors, etc.; underground mining equipment includes belt conveyors, scraper conveyors, hydraulic supports, single pillars, anchor drilling rigs, semi-coal rock tunneling machines, full rock tunneling machines, full hydraulic drilling rigs, coal mining machines, etc. Sensors include smoke sensors, sound and light sensors, temperature sensors, speed sensors and infrared sensors. Among them, infrared sensors are mainly used to sense the flow and position changes of personnel in the working area of ​​coal mines, and upload the parameter information collected by the sensor to the signal acquisition module. At the same time, the historical operation data of the coal mine area, alarm information, personnel and vehicle information in the mining area, and the normal value range of each parameter are uploaded to the information collection module through the human-computer interaction module to complete the collection of various parameter information in the coal mine area.

[0062] 2. Through digital twin technology, various parameter information of the coal mining area is digitized, the real objects in the coal mining area are mapped into the virtual space, and a digital twin model of the coal mining area is built.

[0063] Specifically, in this embodiment, the historical data uploaded in step 1 is fused and analyzed with the currently detected data to obtain the law of data change and realize the learning twin function of the digital twin model.

[0064] 3. Use the monitoring system to monitor the changes in various parameter information in the coal mining area in real time, and synchronously map the real-time parameter information to the virtual space, update the digital twin model of the coal mining area, and predict the data of each area in the coal mining area at the same time, and send the predicted data to the fault warning module.

[0065] Specifically, in this embodiment, a data-driven model is established through data-driven technology, and the data-driven model is combined with the digital twin model. The characteristics of historical data are mined using statistical analysis methods and deep learning algorithms. The current data is compared and analyzed with the historical data. The results of data prediction and the current data measured values ​​are integrated to update and optimize the digital twin model of the coal mining area, so that the digital twin model can be built more accurately and the prediction results can be more reliable.

[0066] 4. The fault warning module receives the prediction information sent by the dynamic tracking and prediction module, and determines whether the prediction information is within the normal value range. If it exceeds the normal value range, a fault warning is issued. At the same time, the synchronous mapping performance of the digital twin technology is combined with the fault diagnosis technology to locate the fault area and perform fault diagnosis and warning.

[0067] Specifically, in this embodiment, a fault alarm module is used to monitor the deviation between the twin and the physical entity in real time. When the deviation is greater than the normal range, a fault alarm is issued, and the operator is notified through the human-computer interaction module. The operator uses the human-computer interaction port to troubleshoot and handle the fault.

[0068] Specifically, in this embodiment, the prediction information includes the temperature and test of each monitoring point, dust concentration prediction value, oxygen concentration prediction value, gas concentration prediction value, water level and each equipment operation data prediction value, etc.

[0069] 5. Use the human-computer interaction port to display the dynamic image of the coal mining area and the predicted information of the equipment in each area in real time. When it is detected that there is an abnormality in the area or equipment information or an abnormality is about to occur, it will be marked on the dynamic image of the coal mining area to show that there is an abnormality at the location, reminding the staff to go to check and verify.

[0070] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0071] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A coal mine area management system based on digital twin, characterized in that: include: Information collection module: collects information on various parameters of the coal mining area and uploads the collected information to the digital twin model construction module; Digital twin model construction module: digitally process the parameter information of the coal mining area through digital twin technology, map the real objects in the coal mining area into the virtual space, and build a digital twin model of the coal mining area; Dynamic tracking and prediction module: Use the monitoring system to monitor the changes in various parameter information in the coal mining area in real time, and synchronously map the real-time parameter information to the virtual space, update the digital twin model of the coal mining area, and predict the gas data of each area in the coal mining area at the same time, and send the predicted data to the fault warning module; Fault warning module: Receives the prediction data sent by the dynamic tracking and prediction module, determines whether the prediction data is within the normal value range, and issues a fault warning if it exceeds the normal value range. At the same time, it combines the synchronous mapping performance of the digital twin technology with the fault diagnosis technology to locate the fault area on the digital twin model, and conducts fault diagnosis and warning. Human-computer interaction module: provides a human-computer interaction port, displays the dynamic tracking and fault warning results of the coal mine area in real time, and provides command feedback on the operation of various parameters in the coal mine area in a human-computer operation mode.

2. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: Sensors are installed on various equipment and monitoring points in the coal mining area. The information collection module receives the parameter information uploaded by the sensors. At the same time, the historical operation data of the coal mining area, alarm information, personnel and vehicle information in the mining area, and the normal value range of each parameter are uploaded to the information collection module through the human-computer interaction module to complete the collection of various parameter information in the coal mining area.

3. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: It also includes a perception monitoring module, which uses the Internet of Things technology to perceive and monitor the production equipment and buildings in the coal mining area in real time, and the perception monitoring module transmits the perception monitoring results to the information collection module in real time.

4. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: In the dynamic tracking and prediction module, machine learning and artificial intelligence technologies are used to learn and build a prediction model from historical data, and the prediction model is used to predict the data of various regions in the coal mining area.

5. A coal mine area management system based on digital twins as claimed in claim 4, characterized in that: The prediction model can perform gas outburst prediction, and the gas outburst prediction steps are as follows: S1, import the original data of coal and gas outburst, and use Kmeans-SMOTE algorithm to generate a data balance data set; S2, cluster the data; S3, oversampling using SMOTE; S4, calculate the position of the pathfinder using the PFA algorithm; S5, update the pathfinder position; S6, determine whether the iteration requirements are met, if so, perform model training and build an improved Kmeans-SMOTE-RF prediction model, if not, return to S3; S7. Optimize the parameters of the prediction model to obtain the optimal model and output the prediction results.

6. A coal mine area management system based on digital twins as claimed in claim 5, characterized in that: The S5 further includes: S51. Pull the out-of-bounds population back to the border; S52, determine whether it exceeds the boundary, if so, return to S51, if not, update the position of the pathfinder.

7. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: It also includes a fault alarm module, which monitors the deviation between the twin and the physical entity in real time, issues a fault alarm when the deviation is greater than a normal range, and notifies the operator through the human-computer interaction module.

8. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: Establish a data-driven model, use statistical analysis methods and deep learning algorithms to mine the characteristics of historical data, predict future data changes based on current data, integrate data prediction results and measured data, and optimize the digital twin model.

9. A coal mine area management system based on digital twins as claimed in claim 1, characterized in that: The digital twin model is presented in real time on the human-computer interaction port through visualization technology.

10. A coal mine area management method based on digital twins, characterized in that: The method comprises: S1. Collect various parameter information of coal mining area; S2. Use digital twin technology to digitize the parameter information of the coal mining area, map the real objects in the coal mining area into the virtual space, and build a digital twin model of the coal mining area; S3. Use the monitoring system to monitor the changes in various parameter information in the coal mining area in real time, and synchronously map the real-time parameter information to the virtual space, update the digital twin model of the coal mining area, and predict the data of each area in the coal mining area; S4. Determine whether the predicted data information is within the normal value range. If it exceeds the normal value range, a fault warning is issued. At the same time, the synchronous mapping performance of the digital twin technology is combined with the fault diagnosis technology to locate the fault area, perform fault diagnosis and warning; S5. Provide a human-computer interaction port to display the dynamic tracking and prediction results of the coal mining area in real time, and provide command feedback on the operation of various parameters in the coal mining area in a human-computer operation mode.

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