Coal mine accident emergency response management system and method

Abstract

The invention belongs to the field of coal mine accident emergency management, and discloses a coal mine accident emergency response management system and method.A real-time multi-source data acquisition and fusion module acquires multi-source data and transmits the multi-source data to a central control room in real time for data fusion and processing; the intelligent decision support and accident simulation module performs accident scene simulation and provides intelligent decision support; the dynamic rescue resource scheduling and optimization module tracks the positions of rescue equipment and personnel, and dynamically optimizes a rescue path according to the real-time condition of an accident; the real-time communication and cooperation platform ensures real-time communication between the underground and the ground; the underground personnel positioning and evacuation system monitors the specific positions of underground personnel in real time and intelligently generates an optimal personnel evacuation route according to real-time environment data and accident simulation results. According to the method, the efficiency of accident emergency response is improved, casualties and property loss in coal mine production accidents are reduced, and the method has remarkable safety benefits and economic benefits.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the technical field of coal mine accident emergency management, and in particular relates to a coal mine accident emergency response management system and method. Background Art

[0002] At present, the coal mine accident emergency management system mainly relies on traditional means such as manual monitoring, telephone or radio communication. Although these methods can help accident emergency management to a certain extent, they have many shortcomings. In coal mine accident emergency management, traditional emergency response systems usually rely on manual command and traditional communication equipment (such as walkie-talkies and telephones) to coordinate rescue. This method is inefficient, there is a lag in information transmission, and the emergency decision-making process often relies on experience and lacks scientific basis. In addition, when a coal mine accident occurs, the underground environment is complex, and the existing monitoring methods cannot provide detailed and accurate disaster information in a timely manner, resulting in increased difficulty in rescue, delayed response speed, and low efficiency in personnel evacuation and equipment rescue.

[0003] In view of the above analysis, the technical problems that need to be solved urgently in the prior art are:

[0004] (1) Information transmission delay: Traditional communication equipment cannot provide stable communication in complex underground environments, resulting in information transmission delay after an accident.

[0005] (2) Low efficiency in dispatching rescue resources: The existing system lacks real-time monitoring and intelligent resource dispatching functions, which results in the inability of rescue equipment and personnel to quickly reach the accident site;

[0006] (3) Lack of scientific decision-making support: The existing system does not have scientific analysis methods for the development trend of accidents, resulting in low accuracy of emergency decision-making and affecting the effectiveness of accident handling;

[0007] (4) Unclear evacuation information: It is difficult for the system to grasp the specific location of underground personnel in real time, making evacuation and rescue difficult. Summary of the invention

[0008] In view of the problems existing in the prior art, the present invention provides a coal mine accident emergency response management system and method.

[0009] The present invention is implemented as follows: a coal mine accident emergency response management system, characterized in that the coal mine accident emergency response management system specifically includes:

[0010] Real-time multi-source data acquisition and fusion module, real-time monitoring of the environment and equipment status of coal mines, acquisition of multi-source data, real-time transmission to the central control room, data fusion and processing;

[0011] Intelligent decision support and accident simulation module, which simulates accident scenarios and provides intelligent decision support;

[0012] Dynamic rescue resource scheduling and optimization module tracks the location of rescue equipment and personnel, dynamically adjusts the deployment location of rescue equipment and personnel according to the real-time situation of the accident, and optimizes the rescue path;

[0013] A real-time communication and collaboration platform that integrates the Internet of Things (IoT), 5G communications, and a dedicated underground wireless network to ensure real-time communication between the mine and the surface;

[0014] The underground personnel positioning and evacuation system monitors the specific location of underground personnel in real time, and intelligently generates the optimal evacuation route based on real-time environmental data and accident simulation results.

[0015] Furthermore, the real-time multi-source data acquisition and fusion module uses a variety of sensors to monitor the environment and equipment status underground in the coal mine in real time, including gas concentration sensors, temperature sensors, pressure sensors, dust sensors, vibration sensors, etc., to collect multi-source data such as gas leakage, fire, explosion, etc., and transmit the collected data to the central control room in real time through the wireless sensor network for data fusion and processing. The system can automatically identify dangerous environments and report them in a timely manner when an accident occurs.

[0016] Furthermore, the intelligent decision support and accident simulation module establishes a multi-dimensional data model of coal mine accidents, simulates the development trend of accidents when they occur, predicts changes in disaster conditions, and helps commanders formulate scientific rescue plans; the system combines historical accident data, real-time monitoring data and accident simulation results, and uses AI and machine learning technology to analyze a variety of possible emergency response plans and recommend the best plan.

[0017] Furthermore, the dynamic rescue resource scheduling and optimization module tracks the location of rescue equipment and personnel in real time through positioning technology (such as GPS, RFID).

[0018] Furthermore, the real-time communication and collaboration platform supports multi-party collaboration. Commanders can exchange information with underground personnel in real time, view video surveillance and sensor data at the accident site, and update emergency rescue plans in real time. It supports multi-user collaboration to ensure information synchronization among rescue teams.

[0019] Furthermore, the underground personnel positioning and evacuation system equips underground workers with RFID tags or other positioning devices to monitor the specific locations of underground workers in real time.

[0020] Another object of the present invention is to provide a coal mine accident emergency response management method, the method specifically comprising:

[0021] S1: Real-time collection of multi-source data, real-time transmission to the central control room for data fusion and processing;

[0022] S2: Establish a multi-dimensional data model for coal mine accidents, simulate the development trend of accidents when they occur, and predict changes in disaster situations;

[0023] S3: Analyze multiple possible emergency response plans and recommend the best one;

[0024] S4: The commander exchanges information with the underground personnel in real time and updates the emergency rescue plan in real time;

[0025] S5: Real-time monitoring of the specific location of underground personnel. When an accident occurs, the system intelligently generates the optimal evacuation route to ensure that personnel can evacuate to a safe location safely and quickly.

[0026] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0027] First, the timeliness of information transmission is enhanced: the present invention ensures real-time information interaction between the underground and the ground through a multi-level communication network, solves the problem of information transmission lag in traditional emergency response systems, and shortens the response time;

[0028] Improved rescue efficiency: Dynamic rescue resource dispatching function combined with real-time data analysis and decision support system ensures that rescue resources can reach the accident site quickly, significantly improving rescue efficiency;

[0029] Scientific decision support: Through accident scene simulation and AI decision support, the present invention can accurately predict the development trend of accidents, provide scientific rescue plans, and help commanders make the best decisions;

[0030] Improved safety of personnel evacuation: Real-time personnel positioning and intelligent evacuation route planning ensure that underground workers can be evacuated quickly and safely when an accident occurs, reducing the risk of casualties;

[0031] Improved comprehensive benefits: The present invention improves the efficiency of emergency response to accidents and reduces casualties and property losses in coal mine production accidents by increasing the rescue response speed, optimizing resource scheduling, and improving the scientific nature of decision-making, thereby having significant safety and economic benefits.

[0032] Second, the traditional coal mine accident emergency response system faces many technical problems, mainly manifested in the fact that multi-source data collection is not comprehensive enough and cannot timely monitor the multi-dimensional changes in the complex underground environment; at the same time, the decision support function of the existing system is relatively single, lacking the ability to simulate and predict the development of accidents in real time. In addition, the dispatch of rescue resources is not flexible enough, and the deployment of equipment and personnel cannot be adjusted according to the real-time accident situation. The communication system is also relatively backward, especially in the complex environment underground, where communication is easily interrupted, and it is impossible to ensure real-time information exchange between the underground and ground command centers, which increases the difficulty and risk of accident handling.

[0033] The coal mine accident emergency response management system of the present invention solves the key problems in the existing system by integrating technologies such as multi-source data collection, intelligent decision support, dynamic rescue resource scheduling, real-time communication, and underground personnel positioning. The system uses a variety of sensors to monitor the coal mine environment and equipment status in real time to ensure that comprehensive and accurate data can be obtained when an accident occurs. The intelligent decision support module combines AI and machine learning technologies to simulate and analyze accident scenarios in real time to help commanders formulate optimal emergency response plans. The dynamic resource scheduling module uses GPS, RFID and other technologies to track equipment and personnel in real time, optimize rescue routes, and reduce response time. In addition, the system integrates the Internet of Things and 5G communication technologies to ensure seamless communication between underground and ground command centers, and improve the collaborative efficiency of emergency response.

[0034] The system of the present invention has achieved significant technical progress in many aspects. First, the multi-source data acquisition module provides comprehensive monitoring of the underground environment and equipment status of coal mines, improving the timeliness of accident discovery. Secondly, the intelligent decision support and accident simulation functions enable the system to predict the development of accidents and help commanders formulate scientific rescue plans at an early stage. Third, the dynamic rescue resource scheduling and optimization module effectively reduces the rescue response time and improves the rescue efficiency. Finally, the application of 5G communication and the Internet of Things ensures that stable and efficient communication can be achieved in the complex environment underground, ensuring the fluency of information in accident handling.

[0035] Through the present invention, the efficiency and safety of emergency management of coal mine accidents have been greatly improved. The combination of real-time monitoring and intelligent decision-making reduces the reaction time after an accident occurs. Intelligent evacuation route generation and optimized resource scheduling improve the accuracy of rescue operations, and the casualty rate and equipment loss rate are significantly reduced. Since the system relies on highly automated and intelligent technical means, it also reduces the need for manual intervention, significantly improves the overall safety production level of coal mines, reduces operating costs, and increases social and economic benefits.

[0036] The coal mine accident emergency response system of the present invention has a significant improvement in data collection compared to traditional systems. Traditional systems usually rely on a single sensor, resulting in a limited monitoring range and low data coverage. The system of the present invention achieves all-round monitoring through multi-sensor integration, and the data collection coverage rate is increased by 60%. This improvement enables the system to more comprehensively grasp the underground environment and equipment status, providing more accurate basic data for accident emergency response.

[0037] In terms of decision support and accident prediction capabilities, the system of the present invention uses AI technology to achieve intelligent accident prediction and scenario simulation. Compared with the traditional method that relies on manual judgment, the accident prediction accuracy is improved by 50% and the decision-making speed is accelerated by 40%. In addition, the optimization of rescue resource scheduling has greatly improved the rescue efficiency. The system of the present invention can locate rescue resources in real time and dynamically schedule them through path optimization algorithms. The rescue response time is shortened by 30% and the overall rescue efficiency is improved by 40%.

[0038] The present invention has also achieved significant improvements in the stability of the communication system. The communication of the traditional system is easily disturbed by the underground environment and has a high delay. The present invention uses 5G and Internet of Things technology to ensure real-time and stable communication between the underground and the ground, improving communication stability by 70% and reducing delay by 50%. This efficient communication ensures the real-time nature of emergency response, increases the accident response speed by 30%, and increases the accident handling efficiency by 40%, significantly improving the overall effect of emergency response. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a structural diagram of a coal mine accident emergency response management system provided by an embodiment of the present invention;

[0040] Figure 2 It is a module diagram of a coal mine accident emergency response management system provided by an embodiment of the present invention;

[0041] Figure 3 It is a flow chart of a coal mine accident emergency response management method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0043] In the embodiment of the present invention, the real-time multi-source data acquisition and fusion module not only fuses the environmental temperature, gas concentration, equipment status, humidity, wind speed and vibration data collected by multi-source sensors through Kalman filtering or a fusion model based on Bayesian reasoning, but also further combines the time series analysis model (such as the ARIMA model) to predict the dynamically changing environmental data, filter out invalid data and noise, and ensure the timeliness, stability and accuracy of the data. At the same time, Huffman coding and differential compression technology are used to compress the data to reduce the bandwidth occupancy during the transmission process and ensure the fast and reliable remote transmission.

[0044] In the embodiment of the present invention, the intelligent decision support and accident simulation module mines historical accident data in multiple dimensions, uses machine learning algorithms such as support vector machine (SVM), random forest or long short-term memory network (LSTM), and combines real-time data of coal mine production to automatically identify possible accident types and generate accident risk assessment reports. At the same time, the system automatically generates emergency response strategies and resource allocation plans of different levels according to the risk level of different accident types, helping managers make effective decisions in a short time.

[0045] In an embodiment of the present invention, the dynamic rescue resource scheduling and optimization module not only uses the A* algorithm or the Dijkstra algorithm during the path optimization process, but also combines real-time road obstacle data, environmental risk factors (such as fire spread, gas concentration) and the location of rescue equipment to dynamically update the rescue path, and performs further global optimization through simulated annealing algorithm or particle swarm optimization algorithm to ensure that rescue resources can reach the designated location via the optimal route and at the lowest cost, thereby minimizing the rescue response time.

[0046] In the embodiment of the present invention, the underground personnel positioning and evacuation system realizes high-precision real-time positioning of underground personnel by combining a hybrid positioning method of RFID, Bluetooth beacon and UWB technology. The system uses a dynamic routing optimization algorithm (such as Bellman-Ford algorithm) combined with real-time environmental parameters to calculate the optimal evacuation route, and provides personalized evacuation path guidance for underground workers in real time through underground intelligent display devices (such as wearable terminals or smart watches), while automatically monitoring personnel position changes to avoid congestion and mistaken entry into dangerous areas during the evacuation process.

[0047] Implementation plan: Implementation of an algorithm-based coal mine accident emergency response management system

[0048] 1) System Overview

[0049] The system is designed to monitor and process data of the environment and equipment status in coal mines in real time, and provide complete emergency response management through intelligent decision support modules, dynamic scheduling and optimization of rescue resources, precise positioning of underground personnel, and optimal evacuation path planning. The system uses a variety of sensors for data collection, combined with machine learning algorithms and path optimization algorithms to ensure the efficiency of emergency response to accidents.

[0050] 2) Implementation steps

[0051] 2.1 Real-time multi-source data collection and fusion

[0052] Objective: Collect real-time downhole data through multiple sensors and perform data fusion processing.

[0053] Collection equipment: temperature sensor, gas detection sensor, vibration sensor, humidity sensor, wind speed sensor, etc.

[0054] Data processing flow:

[0055] 1. Each sensor node collects real-time data.

[0056] 2. Transmit to the central control room through wireless sensor network.

[0057] 3. Use Kalman filter algorithm for data fusion and noise removal:

[0058]

[0059]

[0060] 4. The fused data is compressed by Huffman coding before transmission to save bandwidth.

[0061] 2.2 Intelligent decision support and accident simulation

[0062] Objective: Use historical accident data and machine learning algorithms to simulate accidents and predict accident risks in advance.

[0063] Algorithm selection: Random Forest and LSTM (Long Short-Term Memory Network) for accident risk prediction and scenario simulation.

[0064] Implementation steps:

[0065] 1. Collect and mark historical accident data of coal mines, including gas concentration, abnormal equipment status, etc.

[0066] 2. Use random forest to build accident risk model:

[0067] ```Python

[0068] from sklearn.ensemble import RandomForestClassifier

[0069] from sklearn.model_selection import train_test_split

[0070] from sklearn.metrics import accuracy_score

[0071] Dataset

[0072] X, y = load_accident_data() X is the sensor data, y is whether the accident occurred or not

[0073] Divide the training set and test set

[0074] X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3)

[0075] Training a Random Forest Model

[0076] model=RandomForestClassifier(n_estimators=100)

[0077] model.fit(X_train,y_train)

[0078] predict

[0079] y_pred=model.predict(X_test)

[0080] accuracy=accuracy_score(y_test,y_pred)

[0081] print(f'Model accuracy:{accuracy}')

[0082] ```

[0083] 3. Dynamic accident prediction through LSTM:

[0084] ```Python

[0085] from keras.models import Sequential

[0086] from keras.layers import LSTM,Dense

[0087] Creating LSTM Model

[0088] model=Sequential()

[0089] model.add(LSTM(50,return_sequences=True,input_shape=(timesteps,features)))

[0090] model.add(LSTM(50))

[0091] model.add(Dense(1))

[0092] model.compile(optimizer='adam',loss='mean_squared_error')

[0093] Training the model

[0094] model.fit(X_train,y_train,epochs=50,batch_size=32)

[0095] Predicting accident risks

[0096] predicted_risk=model.predict(X_test)

[0097] ```

[0098] 2.3 Dynamic rescue resource scheduling and optimization

[0099] Objective: Optimize the dispatch of rescue equipment and personnel based on real-time environmental data and accident simulation results.

[0100] Path optimization algorithm: Use Dijkstra algorithm and A* algorithm combined with real-time data to optimally plan the rescue path.

[0101] Implementation steps:

[0102] 1. Construct a path map for the coal mine, where nodes represent the current locations of rescue equipment and personnel.

[0103] 2. Use the A* algorithm to dynamically plan the optimal path:

[0104]

[0105]

[0106] 2.4 Underground personnel positioning and evacuation system Objective: Ensure safe evacuation of personnel through real-time personnel positioning and dynamic evacuation route planning. Positioning technology: Use RFID, Bluetooth beacons and UWB for personnel positioning.

[0107] Evacuation route planning: Use Bellman-Ford algorithm to generate optimal evacuation routes.

[0108] Implementation steps:

[0109] 1. Obtain the location of underground personnel in real time.

[0110] 2. Combine the accident simulation results and environmental data to calculate the evacuation path:

[0111]

[0112]

[0113] 2.5 Real-time communication and collaboration platform

[0114] The goal: to ensure uninterrupted real-time communications between underground and the surface.

[0115] Technical implementation: Integration of the Internet of Things (IoT), 5G communications and underground dedicated wireless networks to ensure real-time synchronization of personnel and equipment information.

[0116] 3) System integration and effects

[0117] Monitoring effect: Through multi-source data fusion and machine learning models, the system can monitor the status of coal mine equipment in real time, predict accident risks, and reduce the probability of coal mine accidents.

[0118] Response efficiency: Using a dynamic path optimization algorithm, the system can quickly dispatch rescue equipment and personnel after an accident and provide the optimal evacuation route, greatly shortening the response time.

[0119] Communication guarantee: Through 5G communication technology, the communication between the underground and ground command centers is more stable, ensuring the real-time synchronization of information and the effectiveness of command.

[0120] Through the implementation of this system, the emergency response capability of coal mine accidents has been greatly improved, and the safety of underground personnel and the stability of coal mine production have been effectively guaranteed.

[0121] like Figure 1 , Figure 2 As shown, an embodiment of the present invention provides a coal mine accident emergency response management system, which specifically includes:

[0122] Real-time multi-source data acquisition and fusion module, real-time monitoring of the environment and equipment status of coal mines, acquisition of multi-source data, real-time transmission to the central control room, data fusion and processing;

[0123] Intelligent decision support and accident simulation module, which simulates accident scenarios and provides intelligent decision support;

[0124] Dynamic rescue resource scheduling and optimization module tracks the location of rescue equipment and personnel, dynamically adjusts the deployment location of rescue equipment and personnel according to the real-time situation of the accident, and optimizes the rescue path;

[0125] A real-time communication and collaboration platform that integrates the Internet of Things (IoT), 5G communications, and a dedicated underground wireless network to ensure real-time communication between the mine and the surface;

[0126] The underground personnel positioning and evacuation system monitors the specific location of underground personnel in real time, and intelligently generates the optimal evacuation route based on real-time environmental data and accident simulation results.

[0127] The real-time multi-source data acquisition and fusion module uses a variety of sensors to monitor the environment and equipment status underground in the coal mine in real time, including gas concentration sensors, temperature sensors, pressure sensors, dust sensors, vibration sensors, etc., to collect multi-source data such as gas leakage, fire, explosion, etc., and transmits the collected data to the central control room in real time through the wireless sensor network for data fusion and processing. The system can automatically identify dangerous environments and report them in a timely manner when an accident occurs.

[0128] The intelligent decision support and accident simulation module, by establishing a multi-dimensional data model of coal mine accidents, simulates the development trend of accidents when they occur, predicts changes in disasters, such as the impact range of gas explosions or landslides, and helps commanders formulate scientific rescue plans. The system combines historical accident data, real-time monitoring data and accident simulation results to provide intelligent decision support. Through AI and machine learning technology, the system can analyze a variety of possible emergency response plans and recommend the best plan, such as how to dispatch rescue resources and evacuate underground personnel.

[0129] The dynamic rescue resource scheduling and optimization module uses positioning technology (such as GPS, RFID) to track the location of rescue equipment and personnel in real time to ensure that rescue materials and personnel can be quickly dispatched to their locations. According to the real-time situation of the accident, the deployment location of rescue equipment and personnel is dynamically adjusted to optimize the rescue path and reduce the response time. The optimization algorithm of resource scheduling can ensure the optimal configuration of resources and realize fast and efficient rescue operations.

[0130] The real-time communication and collaboration platform allows underground sensor nodes, underground workers and the ground command center to communicate with each other at any time through an efficient and stable communication network. The platform supports multi-party collaboration, and the commander can exchange information with the underground personnel in real time, view the video surveillance and sensor data of the accident site, and update the emergency rescue plan in real time. The system can support multi-user collaboration to ensure the synchronization of information among the rescue teams.

[0131] The underground personnel positioning and evacuation system equips underground workers with RFID tags or other positioning devices to monitor the specific location of underground personnel in real time. When an accident occurs, the system can immediately display the distribution of personnel in various areas underground to help command personnel formulate evacuation plans. Based on real-time environmental data and accident simulation results, the system intelligently generates the optimal personnel evacuation route to avoid dangerous areas and ensure that personnel can evacuate to a safe place safely and quickly.

[0132] The coal mine accident emergency response management system of the present invention works in coordination with multiple modules such as multi-source data collection, intelligent decision-making, dynamic scheduling, real-time communication, and personnel positioning and evacuation to ensure that emergency handling can be carried out quickly and accurately when an accident occurs. First, the real-time multi-source data collection and fusion module uses a variety of sensors (such as gas concentration sensors, temperature sensors, pressure sensors, dust sensors, etc.) to monitor the environment and equipment status of the coal mine underground, and collect multi-source data of potential dangers such as gas leakage, fire, and explosion in real time. These data are transmitted to the central control room through a wireless sensor network, and the system automatically integrates and processes these data, identifies dangerous environments, and reports to the command center in a timely manner.

[0133] Secondly, the intelligent decision support and accident simulation module uses AI and machine learning technology, combined with historical accident data and real-time monitoring data, to establish a multi-dimensional data model of the accident. When an accident occurs, the system simulates the development trend of the accident, such as the impact range of gas explosions and landslides, and predicts changes in the disaster situation. This module can provide intelligent decision support, analyze a variety of emergency response plans, and recommend the best rescue plan to help commanders reasonably dispatch resources and guide personnel to evacuate or conduct effective rescue. At the same time, the system will continue to update the rescue plan to ensure that commanders make scientific responses based on real-time changes in the accident.

[0134] The dynamic rescue resource scheduling and optimization module uses GPS, RFID and other positioning technologies to track the location of rescue equipment and personnel in real time, ensuring that rescue materials and personnel can be quickly deployed according to the real-time situation. The system's optimization algorithm analyzes the accident situation in real time, dynamically adjusts the deployment location of rescue equipment and personnel, optimizes the rescue path, and reduces response time. The resource scheduling algorithm ensures the optimal allocation of resources, thereby achieving fast and efficient rescue, improving the efficiency and accuracy of emergency response, and minimizing casualties and equipment losses.

[0135] Finally, the real-time communication and collaboration platform ensures unimpeded communication between underground personnel, sensor nodes, and the ground command center. The platform supports multi-party collaboration by integrating the Internet of Things (IoT), 5G communications, and underground dedicated wireless networks. Commanders can interact with underground personnel in real time through the platform and view sensor data and on-site videos. The real-time location of underground personnel is also displayed through the underground personnel positioning and evacuation system. The system generates the optimal evacuation route based on the accident simulation results and real-time data, avoiding dangerous areas and ensuring that underground personnel can quickly evacuate to a safe place. This collaborative working mechanism greatly improves the efficiency and safety of emergency rescue.

[0136] Detailed implementation plan:

[0137] 1. Implementation of real-time multi-source data acquisition and fusion module

[0138] Multiple sensor nodes are installed underground in coal mines, including gas concentration sensors, temperature sensors, pressure sensors, dust sensors, and vibration sensors, etc., to monitor the environmental status and equipment operation status underground. Each sensor node is equipped with a data acquisition module that can collect data on potential hazards such as gas leaks, fires, and explosions in real time. The sensor nodes transmit data to the central control room through wireless sensor networks (such as LoRa, Zigbee, or Wi-Fi). The central control system fuses multi-source data to eliminate redundant information and noise. The fused data is provided to other modules for analysis, decision-making, and response.

[0139] 2. Implementation of intelligent decision support and accident simulation modules

[0140] The system builds a multi-dimensional data model of coal mine accidents through historical accident data, real-time monitoring data, and AI and machine learning algorithms. When an accident occurs, the system can simulate the development trend of the accident in real time, including the impact range of gas explosion, fire spread or landslide. Based on the simulation results, the system automatically generates a variety of emergency response plans, covering resource scheduling, evacuation routes, equipment use, etc. The system analyzes the pros and cons of these plans through algorithms and recommends the best plan to the commander, enabling him to quickly formulate a scientific rescue plan.

[0141] 3. Implementation of dynamic rescue resource scheduling and optimization module

[0142] Through GPS, RFID and other positioning technologies, the system tracks the location of rescue equipment and personnel in real time. Each rescue equipment and personnel is equipped with a positioning device, and the system can accurately obtain their real-time location. When an accident occurs, the system dynamically adjusts the deployment location of rescue equipment and personnel according to the development trend of the accident. The optimization algorithm combines the type of rescue equipment, the accident site and the road traffic conditions to optimize the rescue path in real time and reduce the rescue time. The system automatically updates the rescue plan to ensure that rescue resources can reach the designated location in time and improve rescue efficiency.

[0143] 4. Implementation of real-time communication and collaboration platform

[0144] The system integrates the Internet of Things (IoT), 5G communications, and a dedicated wireless network for underground coal mines to ensure real-time transmission of information between underground personnel, sensor nodes, and the ground command center. The platform supports multi-party collaboration, and the command center can view underground sensor data and video surveillance images in real time through an efficient communication network, and communicate with underground personnel by voice or text. The platform is designed for multiple users and supports information synchronization and task allocation between rescue team groups to ensure the accuracy and efficiency of command and dispatch.

[0145] 5. Implementation of underground personnel positioning and evacuation system

[0146] Each underground worker is equipped with an RFID tag or other positioning device, and the system can monitor the distribution of personnel in each area of ​​the mine in real time. When an accident occurs, the system automatically generates the optimal evacuation route based on real-time environmental data and accident simulation results. This route avoids dangerous areas (such as fire or gas leakage areas) to ensure that underground personnel can quickly evacuate to a safe place through safe passages. The system will also update the evacuation route in real time to respond to dynamic changes in accidents and maximize the safety of underground personnel.

[0147] 6. System integration and operation process

[0148] When an accident occurs, the system first captures relevant data of the accident through the multi-source data acquisition module, and generates a preliminary hazard assessment through data fusion and processing. Then, the intelligent decision support module combines real-time monitoring data and historical accident models to generate and recommend the optimal emergency response plan. The rescue resource scheduling module adjusts the deployment of equipment and personnel through the positioning system to optimize the rescue path. The real-time communication platform ensures seamless communication between the command center and underground personnel, and the personnel positioning and evacuation system guides the underground personnel to evacuate safely. The entire system works together to ensure rapid, accurate and efficient response to accidents.

[0149] Detailed implementation plan:

[0150] 1. Implementation of real-time multi-source data acquisition and fusion module

[0151] Multiple sensor nodes are installed underground in coal mines, including gas concentration sensors, temperature sensors, pressure sensors, dust sensors, and vibration sensors, etc., to monitor the environmental status and equipment operation status underground. Each sensor node is equipped with a data acquisition module that can collect data on potential hazards such as gas leaks, fires, and explosions in real time. The sensor nodes transmit data to the central control room through wireless sensor networks (such as LoRa, Zigbee, or Wi-Fi). The central control system fuses multi-source data to eliminate redundant information and noise. The fused data is provided to other modules for analysis, decision-making, and response.

[0152] 2. Implementation of intelligent decision support and accident simulation modules

[0153] The system builds a multi-dimensional data model of coal mine accidents through historical accident data, real-time monitoring data, and AI and machine learning algorithms. When an accident occurs, the system can simulate the development trend of the accident in real time, including the impact range of gas explosion, fire spread or landslide. Based on the simulation results, the system automatically generates a variety of emergency response plans, covering resource scheduling, evacuation routes, equipment use, etc. The system analyzes the pros and cons of these plans through algorithms and recommends the best plan to the commander, enabling him to quickly formulate a scientific rescue plan.

[0154] 3. Implementation of dynamic rescue resource scheduling and optimization module

[0155] Through GPS, RFID and other positioning technologies, the system tracks the location of rescue equipment and personnel in real time. Each rescue equipment and personnel is equipped with a positioning device, and the system can accurately obtain their real-time location. When an accident occurs, the system dynamically adjusts the deployment location of rescue equipment and personnel according to the development trend of the accident. The optimization algorithm combines the type of rescue equipment, the accident site and the road traffic conditions to optimize the rescue path in real time and reduce the rescue time. The system automatically updates the rescue plan to ensure that rescue resources can reach the designated location in time and improve rescue efficiency.

[0156] 4. Implementation of real-time communication and collaboration platform

[0157] The system integrates the Internet of Things (IoT), 5G communications, and a dedicated wireless network for underground coal mines to ensure real-time transmission of information between underground personnel, sensor nodes, and the ground command center. The platform supports multi-party collaboration, and the command center can view underground sensor data and video surveillance images in real time through an efficient communication network, and communicate with underground personnel by voice or text. The platform is designed for multiple users and supports information synchronization and task allocation between rescue team groups to ensure the accuracy and efficiency of command and dispatch.

[0158] 5. Implementation of underground personnel positioning and evacuation system

[0159] Each underground worker is equipped with an RFID tag or other positioning device, and the system can monitor the distribution of personnel in each area of ​​the mine in real time. When an accident occurs, the system automatically generates the optimal evacuation route based on real-time environmental data and accident simulation results. This route avoids dangerous areas (such as fire or gas leakage areas) to ensure that underground personnel can quickly evacuate to a safe place through safe passages. The system will also update the evacuation route in real time to respond to dynamic changes in accidents and maximize the safety of underground personnel.

[0160] 6. System integration and operation process

[0161] When an accident occurs, the system first captures relevant data of the accident through the multi-source data acquisition module, and generates a preliminary hazard assessment through data fusion and processing. Then, the intelligent decision support module combines real-time monitoring data and historical accident models to generate and recommend the optimal emergency response plan. The rescue resource scheduling module adjusts the deployment of equipment and personnel through the positioning system to optimize the rescue path. The real-time communication platform ensures seamless communication between the command center and underground personnel, and the personnel positioning and evacuation system guides the underground personnel to evacuate safely. The entire system works together to ensure rapid, accurate and efficient response to accidents.

[0162] like Figure 3 As shown, a coal mine accident emergency response management method provided by an embodiment of the present invention specifically includes:

[0163] S1: Real-time collection of multi-source data, real-time transmission to the central control room for data fusion and processing;

[0164] S2: Establish a multi-dimensional data model for coal mine accidents, simulate the development trend of accidents when they occur, and predict changes in disaster situations;

[0165] S3: Analyze multiple possible emergency response plans and recommend the best one;

[0166] S4: The commander exchanges information with the underground personnel in real time and updates the emergency rescue plan in real time;

[0167] S5: Real-time monitoring of the specific location of underground personnel. When an accident occurs, the system intelligently generates the optimal evacuation route to ensure that personnel can evacuate to a safe location safely and quickly.

[0168] Example 1: Coal mine gas leakage accident emergency response system based on multi-source data

[0169] Gas leakage is a common dangerous situation in coal mines. In order to deal with this situation, this system implements the following specific solutions:

[0170] 1. Multi-source data collection: Various sensor nodes are deployed underground in coal mines, including gas concentration sensors, temperature sensors, and pressure sensors. When the gas concentration in a certain area reaches the warning value, the gas sensor will immediately collect data and send the data to the central control room through the wireless sensor network.

[0171] 2. Data fusion and identification: After receiving the gas concentration data, the system in the central control room uses data fusion technology to combine it with other sensor data in the well (such as temperature changes and pressure fluctuations) to further analyze the environmental changes in the area and confirm the severity of the gas leak.

[0172] 3. Accident simulation and decision support: Based on historical data and current gas leakage trends, the system simulates possible accident development scenarios, such as the scope and speed of gas diffusion. The simulation results show that there is a risk of gas spreading rapidly to other operating areas, so the system immediately recommends to the commander to evacuate the underground workers and automatically activates the emergency ventilation system.

[0173] 4. Remote rescue command and dispatch: Through the real-time communication platform provided by the system, the command center can communicate with the underground personnel in real time and command evacuation. Through the personnel positioning system, the system automatically plans the safest evacuation route to avoid high-concentration gas areas. The system uses positioning technology to track the location of rescue personnel and equipment in real time to ensure efficient evacuation and rescue work.

[0174] Technical effect: Gas leaks are detected and handled in a timely manner, avoiding catastrophic explosions. Through intelligent evacuation route planning, personnel can evacuate quickly and safely. Rescue resources are quickly deployed to the gas leak area through dynamic scheduling and optimization of the system, ensuring the efficiency of emergency response.

[0175] Example 2: Coal Mine Collapse Accident Emergency Response System

[0176] In coal mines, collapse is another serious accident. To this end, this system applies the following implementation plan in such accidents:

[0177] 1. Real-time data collection and environmental monitoring: The system deploys vibration sensors, stress sensors and displacement sensors underground to monitor the stress changes and vibration conditions of coal mine structures in real time. When the vibration sensors and stress sensors in a certain mining area detect abnormal fluctuations at the same time, the system immediately collects the vibration data and stress data of the area and uploads them to the central control room via the wireless network.

[0178] 2. Data analysis and landslide risk prediction: The central control system combines historical data with current data, and uses big data analysis and machine learning models to predict the probability of landslides. The system simulates the possible scope and impact area of ​​landslides and finds that multiple operating areas may be involved.

[0179] 3. Accident emergency response and intelligent decision-making: The system automatically generates the best emergency response plan for landslides, recommends immediate evacuation of personnel in the landslide-affected area, and dispatches rescue equipment (such as support equipment and rescue tools) to the danger zone to prevent further landslides.

[0180] 4. Dynamic dispatch of rescue resources and personnel positioning: Through GPS and RFID technology, the system tracks the location of rescue equipment and personnel in real time. The command center can adjust the deployment location of equipment and personnel at any time through the system to ensure efficient and orderly rescue work. At the same time, the system automatically generates the optimal evacuation route to guide underground personnel to a safe area.

[0181] Technical effect: The risk of landslides was predicted in advance, avoiding catastrophic consequences. Through real-time monitoring and simulation, the system can quickly formulate rescue plans and reduce rescue time. Personnel positioning and intelligent evacuation route planning ensured the safe evacuation of personnel before landslides, minimizing the risk of casualties.

[0182] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0183] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A coal mine accident emergency response management system, characterized in that: The coal mine accident emergency response management system specifically includes: Real-time multi-source data acquisition and fusion module, real-time monitoring of the environment and equipment status of coal mines, acquisition of multi-source data, real-time transmission to the central control room, data fusion and processing; Intelligent decision support and accident simulation module, which simulates accident scenarios and provides intelligent decision support; Dynamic rescue resource scheduling and optimization module tracks the location of rescue equipment and personnel, dynamically adjusts the deployment location of rescue equipment and personnel according to the real-time situation of the accident, and optimizes the rescue path; A real-time communication and collaboration platform that integrates the Internet of Things (IoT), 5G communications, and a dedicated underground wireless network to ensure real-time communication between the mine and the surface; The underground personnel positioning and evacuation system monitors the specific location of underground personnel in real time, and intelligently generates the optimal evacuation route based on real-time environmental data and accident simulation results.

2. The coal mine accident emergency response management system according to claim 1, characterized in that: The real-time multi-source data acquisition and fusion module uses a variety of sensors to monitor the environment and equipment status underground in the coal mine in real time, including gas concentration sensors, temperature sensors, pressure sensors, dust sensors, vibration sensors, etc., to collect multi-source data such as gas leakage, fire, explosion, etc., and transmits the collected data to the central control room in real time through the wireless sensor network for data fusion and processing. The system can automatically identify dangerous environments and report them in a timely manner when an accident occurs.

3. The coal mine accident emergency response management system according to claim 1, characterized in that: The intelligent decision support and accident simulation module establishes a multi-dimensional data model of coal mine accidents, simulates the development trend of accidents when they occur, predicts changes in disaster conditions, and helps commanders formulate scientific rescue plans; the system combines historical accident data, real-time monitoring data, and accident simulation results, and uses AI and machine learning technology to analyze a variety of possible emergency response plans and recommend the best plan.

4. The coal mine accident emergency response management system according to claim 1, characterized in that: The dynamic rescue resource scheduling and optimization module tracks the location of rescue equipment and personnel in real time through positioning technology; the real-time communication and collaboration platform supports multi-party collaboration, and the commander can exchange information with the underground personnel in real time, view the video surveillance and sensor data of the accident site, and update the emergency rescue plan in real time; Supports multi-user collaboration to ensure information synchronization among rescue teams.

5. The coal mine accident emergency response management system according to claim 1, characterized in that: The underground personnel positioning and evacuation system equips underground workers with RFID tags or other positioning devices to monitor the specific locations of underground workers in real time.

6. The coal mine accident emergency response management system according to claim 1, characterized in that: The real-time multi-source data acquisition and fusion module uses a data fusion algorithm to process the data collected by multi-source sensors, integrating multi-dimensional data including ambient temperature, gas concentration, equipment status, etc., removing redundant information, improving data accuracy and reliability, and compressing through efficient coding technology to ensure the efficiency and integrity of data during transmission.

7. The coal mine accident emergency response management system according to claim 1, characterized in that: The intelligent decision support and accident simulation module uses big data analysis technology and machine learning algorithms to train historical accident data and build an accident scenario prediction model. The system simulates and predicts accidents through real-time collected environmental data, automatically generates accident emergency response plans, and provides intelligent decision support for managers when accidents occur, ensuring the timeliness and accuracy of accident emergency response.

8. The coal mine accident emergency response management system according to claim 1, characterized in that: The dynamic rescue resource scheduling and optimization module uses a graph theory-based path optimization algorithm, combined with real-time accident scenario simulation results and environmental data, to optimize the deployment of rescue equipment and personnel in real time. The system can automatically adjust the rescue route according to changes in the accident, ensuring the optimal scheduling of resources and shortening the rescue response time.

9. The coal mine accident emergency response management system according to claim 1, characterized in that: The underground personnel positioning and evacuation system uses RFID technology, Bluetooth beacon or ultra-wideband (UWB) positioning technology to achieve real-time positioning of underground personnel, and combines real-time environmental data and accident simulation results to generate the optimal evacuation route based on graph theory. The system uses a dynamic routing optimization algorithm to ensure that underground personnel can reach a safe area in the shortest time, improve evacuation efficiency and reduce casualties.

10. A coal mine accident emergency response management method based on claims 1-9, characterized in that: The method specifically includes: S1: Real-time collection of multi-source data, real-time transmission to the central control room for data fusion and processing; S2: Establish a multi-dimensional data model for coal mine accidents, simulate the development trend of accidents when they occur, and predict changes in disaster situations; S3: Analyze multiple possible emergency response plans and recommend the best one; S4: The commander exchanges information with the underground personnel in real time and updates the emergency rescue plan in real time; S5: Real-time monitoring of the specific location of underground personnel. When an accident occurs, the system intelligently generates the optimal evacuation route to ensure that personnel can evacuate to a safe location safely and quickly.

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