Mine disaster rescue method and device

Abstract

The application discloses a mine disaster rescue method and device. The method comprises the following steps: obtaining disaster monitoring data of a mine; performing disaster risk assessment based on the disaster monitoring data to obtain an assessment result; in response to the assessment result meeting disaster risk conditions, performing disaster situation deduction and disaster rescue decision based on the assessment result and the disaster monitoring data to obtain a target rescue mode; and sending an emergency dispatch instruction according to the target rescue mode, wherein the emergency dispatch instruction is used for guiding emergency dispatch rescue operation on the mine. The application solves the technical problems of low intelligent level and low rescue efficiency of the mine disaster rescue method provided by the prior art.

Description

Technical Field

[0001] This invention relates to the field of mine safety technology, and more specifically, to a mine disaster rescue method and apparatus. Background Technology

[0002] During coal mining, the complex mining systems, varied geological conditions, and harsh production conditions, coupled with the fact that workplaces are mostly located in confined underground spaces, make them vulnerable to safety accidents and natural disasters such as water inrush, fire, gas, coal dust, roof falls, and toxic gases. Currently, to ensure timely and effective emergency rescue in the event of mine disasters, many mines have deployed auxiliary systems such as communication and disaster early warning systems, enhancing their emergency rescue capabilities.

[0003] However, existing mine disaster relief methods still have some shortcomings, such as: lack of integration with underground monitoring and sensing equipment, lack of emergency rescue auxiliary decision-making capabilities, and lack of efficient and comprehensive intelligent emergency rescue management and dispatching methods. As a result, when major mine disasters occur, emergency rescue cannot be carried out in a comprehensive, timely and efficient manner, which in turn causes serious casualties.

[0004] There is currently no effective solution to the problems of low intelligence and low rescue efficiency in the existing mine disaster rescue methods provided by the above-mentioned technologies. Summary of the Invention

[0005] This invention provides a mine disaster rescue method and apparatus to at least solve the technical problems of low intelligence and low rescue efficiency in existing mine disaster rescue methods.

[0006] According to one aspect of the present invention, a mine disaster rescue method is provided, comprising:

[0007] Acquire disaster monitoring data of the mine; conduct disaster risk assessment based on the disaster monitoring data to obtain assessment results; respond to the assessment results meeting the disaster risk conditions, conduct disaster situation simulation and disaster relief decision-making based on the assessment results and disaster monitoring data to obtain the target relief method; send emergency dispatch instructions according to the target relief method, wherein the emergency dispatch instructions are used to guide the emergency dispatch and relief operations carried out in the mine.

[0008] Optionally, the disaster monitoring data includes first data and second data. Obtaining disaster monitoring data in the mine includes: obtaining first data, wherein the first data is collected in real time by various information collection devices installed in the mine, including: environmental parameter collection devices, video collection devices, personnel information collection devices, and equipment information collection devices; monitoring and statistically analyzing the first data to obtain second data, wherein the second data includes structured datasets and unstructured datasets.

[0009] Optionally, a disaster risk assessment of the mine is conducted based on disaster monitoring data, and the assessment results include: using a risk assessment model to monitor the trend of indicators in the disaster monitoring data to obtain monitoring results, wherein the risk assessment model is a neural network model obtained by machine learning using the historical risk assessment data corresponding to the mine; and using the monitoring results and preset early warning intervals to determine the assessment results.

[0010] Optionally, the assessment results are determined by using monitoring results and preset warning intervals, including: determining multiple current indicator values ​​of multiple disaster risk indicators corresponding to the mine based on monitoring results; calculating comprehensive situation parameters using multiple current indicator values; and determining that the assessment results meet the disaster risk conditions in response to the comprehensive situation parameters being within the preset warning interval.

[0011] Optionally, in response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are conducted based on the assessment results and disaster monitoring data to obtain the target relief method, including: using a simulation analysis model to simulate the disaster situation based on the assessment results and disaster monitoring data, generating disaster simulation results, wherein the simulation analysis model is a neural network model obtained by machine learning using historical disaster situation simulation data corresponding to the mine; and using a decision analysis model to make disaster relief decisions based on the disaster simulation results and disaster monitoring data to determine the target relief method, wherein the decision analysis model is a neural network model obtained by machine learning using historical disaster relief decision data corresponding to the mine.

[0012] Optionally, the simulation analysis model includes: a multi-disaster situation analysis sub-model, a resource scheduling analysis sub-model, and a big data analysis sub-model. The simulation analysis model is used to perform disaster situation simulations based on the assessment results and disaster monitoring data, generating disaster simulation results. This includes: analyzing the assessment results using the multi-disaster situation analysis sub-model to obtain a first analysis result; analyzing the assessment results and emergency resource data and historical disaster data from the disaster monitoring data using the resource scheduling analysis sub-model to obtain a second analysis result; and optimizing the first and second analysis results using the big data analysis sub-model to generate the disaster simulation results.

[0013] Optionally, disaster relief decisions are made using a decision analysis model based on disaster simulation results and disaster monitoring data to determine the target relief method. This includes: modeling emergency routes based on disaster simulation results and disaster monitoring data to obtain an initial relief route; using the disaster analysis sub-model in the decision analysis model to perform real-time analysis of disaster monitoring data to obtain real-time disaster results; updating the initial relief route based on the real-time disaster results using the route decision sub-model in the decision analysis model to obtain the target relief route, where the target relief route includes evacuation routes and rescue routes; and determining the target relief method based on the target relief route.

[0014] Optionally, sending emergency dispatch instructions based on the target rescue method includes at least one of the following: generating and issuing emergency command instructions based on the target rescue method, wherein the emergency command instructions are used to guide emergency command operations for various types of personnel corresponding to the mine; assisting in emergency dispatch and rescue operations for the mine; generating and sending emergency communication instructions based on the target rescue method, wherein the emergency communication instructions are used to guide the emergency establishment operation of the real-time communication system corresponding to the mine; generating and sending disaster early warning instructions based on the target rescue method, wherein the disaster early warning instructions are used to guide the emergency release operation of disaster early warning information corresponding to the mine.

[0015] Optionally, after conducting emergency dispatch and rescue of the mine according to the target rescue method, the mine disaster rescue method further includes: calculating rescue effectiveness parameters based on the rescue log data corresponding to the target rescue method, wherein the rescue log data is used to record the full-process event information corresponding to the emergency dispatch and rescue, and the rescue effectiveness parameters are used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to the emergency dispatch and rescue; and using the rescue effectiveness parameters to revise and update the risk assessment model, extrapolation analysis model and decision analysis model corresponding to the mine.

[0016] According to another aspect of the present invention, a mine disaster rescue device is also provided, comprising:

[0017] The acquisition module is used to acquire disaster monitoring data of the mine; the assessment module is used to conduct disaster risk assessment based on the disaster monitoring data and obtain the assessment results; the decision-making module is used to respond to the assessment results meeting the disaster risk conditions, and to conduct disaster situation simulation and disaster relief decision-making based on the assessment results and disaster monitoring data to obtain the target relief method; the relief module is used to send emergency dispatch instructions according to the target relief method, wherein the emergency dispatch instructions are used to guide the emergency dispatch and relief operations carried out in the mine.

[0018] Optionally, the above-mentioned acquisition module is further used for: disaster monitoring data including first data and second data, acquiring disaster monitoring data of the mine includes: acquiring first data, wherein the first data is collected in real time by a variety of information acquisition devices installed in the mine, the variety of information acquisition devices including: environmental parameter acquisition devices, video acquisition devices, personnel information acquisition devices and equipment information acquisition devices; monitoring and statistically analyzing the first data to obtain second data, wherein the second data includes structured datasets and unstructured datasets.

[0019] Optionally, the above assessment module is also used to: conduct disaster risk assessment of the mine based on disaster monitoring data, and obtain assessment results including: using a risk assessment model to monitor the trend of indicators of disaster monitoring data to obtain monitoring results, wherein the risk assessment model is a neural network model obtained by machine learning using the historical risk assessment data corresponding to the mine; and using the monitoring results and preset early warning intervals to determine the assessment results.

[0020] Optionally, the aforementioned assessment module is also used to: determine the assessment results using monitoring results and preset warning intervals, including: determining multiple current indicator values ​​of multiple disaster risk indicators corresponding to the mine based on monitoring results; calculating comprehensive situation parameters using multiple current indicator values; and determining that the assessment results meet disaster risk conditions in response to the comprehensive situation parameters being within the preset warning interval.

[0021] Optionally, the decision-making module is further configured to: respond to the assessment results meeting the disaster risk conditions, perform disaster situation simulation and disaster relief decision-making based on the assessment results and disaster monitoring data, and obtain the target relief method, including: using a simulation analysis model to perform disaster situation simulation on the assessment results and disaster monitoring data, generating disaster simulation results, wherein the simulation analysis model is a neural network model obtained by machine learning using historical disaster situation simulation data corresponding to the mine; and using a decision analysis model to perform disaster relief decision-making on the disaster simulation results and disaster monitoring data, determining the target relief method, wherein the decision analysis model is a neural network model obtained by machine learning using historical disaster relief decision data corresponding to the mine.

[0022] Optionally, the aforementioned decision-making module is further used for: The simulation analysis model includes: multiple disaster situation analysis sub-models, resource scheduling analysis sub-models, and big data analysis sub-models. The simulation analysis model is used to perform disaster situation simulations on the assessment results and disaster monitoring data, generating disaster simulation results including: analyzing the assessment results using the multiple disaster situation analysis sub-models to obtain a first analysis result; analyzing the assessment results and emergency resource data and historical disaster data in the disaster monitoring data using the resource scheduling analysis sub-model to obtain a second analysis result; and optimizing the first and second analysis results using the big data analysis sub-model to generate disaster simulation results.

[0023] Optionally, the aforementioned decision-making module is also used to: make disaster relief decisions based on disaster simulation results and disaster monitoring data using a decision analysis model, and determine the target relief method, including: modeling emergency routes based on disaster simulation results and disaster monitoring data to obtain an initial relief route; using the disaster situation analysis sub-model in the decision analysis model to perform real-time analysis of disaster monitoring data to obtain real-time disaster situation results; based on the real-time disaster situation results, updating the initial relief route using the route decision sub-model in the decision analysis model to obtain a target relief route, wherein the target relief route includes a disaster avoidance route and a disaster relief route; and determining the target relief method based on the target relief route.

[0024] Optionally, the above-mentioned rescue module is further configured to: send emergency dispatch instructions according to the target rescue method, including at least one of the following: generate and issue emergency command instructions according to the target rescue method, wherein the emergency command instructions are used to guide emergency command operations for various types of personnel corresponding to the mine; assist in emergency dispatch and rescue operations for the mine; generate and send emergency communication instructions according to the target rescue method, wherein the emergency communication instructions are used to guide the emergency establishment operation of the real-time communication system corresponding to the mine; generate and send disaster early warning instructions according to the target rescue method, wherein the disaster early warning instructions are used to guide the emergency release operation of disaster early warning information corresponding to the mine.

[0025] Optionally, the mine disaster rescue device further includes: an update module, used to calculate rescue effectiveness parameters based on the rescue log data corresponding to the target rescue method after emergency dispatch and rescue of the mine according to the target rescue method. The rescue log data is used to record the full-process event information corresponding to the emergency dispatch and rescue, and the rescue effectiveness parameters are used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to the emergency dispatch and rescue. The rescue effectiveness parameters are used to correct and update the risk assessment model, inference analysis model and decision analysis model corresponding to the mine.

[0026] In this embodiment of the invention, firstly, disaster monitoring data of the mine is acquired, then a disaster risk assessment is conducted based on the disaster monitoring data to obtain the assessment result. When the assessment result meets the disaster risk conditions, a disaster situation simulation and disaster relief decision are made based on the assessment result and the disaster monitoring data to obtain the target rescue method. Finally, an emergency dispatch instruction is sent according to the target rescue method, wherein the emergency dispatch instruction is used to guide the emergency dispatch and rescue operation carried out on the mine.

[0027] It is easy to understand that the above-mentioned mine disaster rescue method provided by the present invention achieves the goal of optimizing the entire process of mine disaster rescue through processes such as disaster risk assessment, disaster situation simulation, disaster rescue decision-making, and sending emergency dispatch instructions. This achieves the technical effect of optimizing the entire process of mine disaster rescue to improve the intelligence level of mine disaster rescue methods and enhance the efficiency of mine disaster rescue, thereby solving the technical problems of low intelligence level and low rescue efficiency of existing mine disaster rescue methods. Attached Figure Description

[0028] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0029] Figure 1 This is a flowchart of a mine disaster rescue method according to an embodiment of the present invention;

[0030] Figure 2 This is a schematic diagram of an optional mine disaster relief emergency platform according to an embodiment of the present invention;

[0031] Figure 3 This is a flowchart of an optional mine disaster rescue process according to an embodiment of the present invention;

[0032] Figure 4 This is a structural block diagram of a mine disaster rescue device according to an embodiment of the present invention;

[0033] Figure 5 This is a structural block diagram of another mine disaster rescue device according to an embodiment of the present invention. Detailed Implementation

[0034] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0036] According to an embodiment of the present invention, an embodiment of a mine disaster rescue method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0037] Figure 1 This is a flowchart of a mine disaster rescue method according to an embodiment of the present invention, such as... Figure 1 As shown, Figure 1 The illustrated embodiments may include at least the following implementation steps, namely, the technical approach implemented by steps S11 to S14 below:

[0038] Step S11: Obtain disaster monitoring data for the mine;

[0039] In one optional solution provided in step S11 above, the disaster monitoring data can be dynamic data from the actual production process of the coal mining enterprise, including but not limited to: gas environment monitoring data, equipment information, underground worker information, and spatial information. It should also be noted that the disaster monitoring data can be real-time data acquired by mine monitoring equipment (or institutions), which can include but are not limited to: sensors, actuators, substations, and master stations.

[0040] Step S12: Conduct a disaster risk assessment based on disaster monitoring data to obtain the assessment results;

[0041] In one optional scheme provided by step S12 above, the assessment result can be used to characterize the safety status of the mine, that is, the assessment result can be used to predict whether there is a risk of disaster in the mine. It should also be noted that the assessment result can be a quantitative result obtained by mathematical calculation of the disaster monitoring data, or it can be a combination of the quantitative result and the result of disaster analysis inference.

[0042] The solution provided by this invention involves conducting a disaster risk assessment based on disaster monitoring data to obtain an assessment result. Specifically, in one optional embodiment, a single pre-trained disaster risk assessment model is used to analyze and assess the disaster monitoring data to obtain a disaster assessment result. In another optional embodiment, multiple pre-trained disaster risk assessment models are used to analyze and assess the disaster monitoring data respectively, and the average of the multiple assessment results is taken as the target assessment result.

[0043] Step S13: In response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are carried out based on the assessment results and disaster monitoring data to obtain the target relief method;

[0044] In one optional solution provided by step S13 above, the aforementioned disaster risk conditions can be used to determine whether there is a risk of a disaster occurring, or they can be used to determine the development trend of a disaster when it occurs. It should also be noted that the disaster risk conditions may include one or more risk thresholds. When one or more risk parameters reach the corresponding risk threshold, it can be determined that there is a risk of a disaster occurring in the mine.

[0045] It can also be understood that the aforementioned targeted rescue methods can be rescue methods corresponding to specific mine disasters. Specifically, for example, when a mine fire occurs, the location of the fire source and the extent of the fire's spread are first determined, and then the corresponding ventilation method is determined. Another example is when a mine flooding accident occurs, rescue methods such as drainage, dredging, blocking, and drilling are selected based on the mine's conditions. Yet another example is when a mine explosion occurs, rescue methods include first predicting the accident's development, determining the explosion's range and the possibility of secondary explosions, and organizing the rapid evacuation of personnel from the danger zone.

[0046] In the solution provided by this invention, in response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are performed based on the assessment results and disaster monitoring data to obtain the target rescue method. Specifically, in an optional embodiment, it is assumed that the disaster monitoring data includes the initial gas release velocity, the coal mine's firmness coefficient, and the original coal seam gas pressure. Simultaneously, it is assumed that the disaster risk conditions include a threshold of 10 for the initial gas release velocity, a threshold of 0.5 for the coal mine's firmness coefficient, and a threshold of 0.74 P / MPa for the original coal seam gas pressure. When the initial gas release velocity is 15, the coal mine's firmness coefficient is 0.3, and the original coal seam gas pressure is 1 P / MPa, it is determined that there is a risk of gas explosion in the coal mine. Then, a gas diffusion model is used to simulate the gas diffusion situation in the coal mine. Simultaneously, the rescue decisions are analyzed and determined to include: personnel evacuation strategies and fire extinguishing strategies, thereby obtaining a series of target rescue methods to carry out emergency rescue in a timely and efficient manner.

[0047] Step S14: Send an emergency dispatch instruction according to the target rescue method, wherein the emergency dispatch instruction is used to guide the emergency dispatch and rescue operation in the mine.

[0048] In one optional solution provided by step S14 above, the emergency dispatch instruction can be used to dispatch rescue personnel to carry out emergency rescue when a mine disaster occurs. This emergency dispatch instruction can include dispatch instructions issued by the emergency rescue central control center, or dispatch instructions issued by various emergency rescue departments. The aforementioned emergency dispatch and rescue operation can be one or more emergency rescue actions requiring manual intervention, specifically, for example: bomb disposal, manual firefighting, and casualty rescue.

[0049] In the solution provided by this invention, emergency dispatch instructions are sent according to the target rescue method. Specifically, when a mine fire accident occurs, the emergency rescue control center sends fire extinguishing instructions (which may include the number of firefighters needed and the number of various fire extinguishing equipment) to the fire department through the communication system, and sends rescue instructions (which may include the number of medical staff needed, the number of rescue vehicles, and the number of medical devices) to the nearby hospital.

[0050] In this embodiment of the invention, firstly, disaster monitoring data of the mine is acquired, then a disaster risk assessment is conducted based on the disaster monitoring data to obtain the assessment result. When the assessment result meets the disaster risk conditions, a disaster situation simulation and disaster relief decision are made based on the assessment result and the disaster monitoring data to obtain the target rescue method. Finally, an emergency dispatch instruction is sent according to the target rescue method, wherein the emergency dispatch instruction is used to guide the emergency dispatch and rescue operation carried out on the mine.

[0051] It is easy to understand that the above-mentioned mine disaster rescue method provided by the present invention achieves the goal of optimizing the entire mine disaster rescue process through processes such as disaster risk assessment, disaster situation simulation, disaster rescue decision-making, and sending emergency dispatch instructions. This achieves the technical effect of optimizing the entire mine disaster rescue process to improve the intelligence level and efficiency of mine disaster rescue methods, thereby solving the technical problems of low intelligence level and low rescue efficiency of existing mine disaster rescue methods.

[0052] The methods described in the above embodiments of the present invention will be further described below.

[0053] In an optional embodiment, in step S11, the disaster monitoring data includes first data and second data, and acquiring the mine's disaster monitoring data includes:

[0054] Step S111: Obtain first data, wherein the first data is collected in real time by a variety of information collection devices installed in the mine, including: environmental parameter collection devices, video collection devices, personnel information collection devices and equipment information collection devices;

[0055] Step S112: Monitor and statistically analyze the first data to obtain the second data, wherein the second data includes structured datasets and unstructured datasets.

[0056] In one optional solution provided by steps S111 to S112 above, the first data may include, but is not limited to: gas environment monitoring data, equipment information, underground worker information, and spatial information. The environmental parameter acquisition devices may include, but are not limited to: temperature sensors and gas sensors. The video acquisition devices may include, but are not limited to: cameras, lenses, pan-tilt units, and monitoring equipment. The personnel information acquisition devices may include, but are not limited to: identity information scanners and facial recognition cameras. The equipment information acquisition devices may include, but are not limited to: visual monitoring instruments and vibration monitoring and analysis instruments.

[0057] In one optional scheme provided by steps S111 to S112 above, the structured dataset may include, but is not limited to: the original instantaneous value of the first data, the average value of the first data, and the cumulative value of the first data. The unstructured dataset may include, but is not limited to: mine maps, datasets contained in a Geographic Information System (GIS), monitoring videos and images, emergency knowledge, contingency plans, and accident cases.

[0058] The following combination Figure 2 The above methods will be further explained.

[0059] Figure 2 This is a schematic diagram of an optional mine disaster rescue emergency platform according to an embodiment of the present invention, such as... Figure 2 As shown, the intelligent emergency platform 200 can be used for pre-disaster monitoring, risk analysis and assessment, disaster situation simulation, modeling and analysis, and post-disaster model optimization in mines. The data management module 201 can be used to collect, process, and store mine data. The data analysis module 202 can be used for safety risk warnings before disasters occur, to simulate disaster development trends during disasters, to create 3D models of emergency routes, and to analyze and evaluate the effectiveness of emergency decisions and strengthen mine disaster analysis models after disasters. The emergency command module 203 can be used for disseminating emergency information and for emergency command and dispatch.

[0060] Still as Figure 2As shown, specifically, the data acquisition system 204 of the data management module 201 can be used to collect system data (i.e., the aforementioned first data) from multiple systems included in the intelligent emergency platform 200. These multiple systems may include, but are not limited to,: emergency management department information systems, coal mine enterprise industrial safety video monitoring systems, underground worker management systems, and major equipment monitoring systems. It should also be noted that the data acquisition system 204 can perform statistical processing on the real-time collected first data to obtain structured and unstructured datasets (i.e., the aforementioned second data) corresponding to the first data. Furthermore, the database 205 of the data management module 201 can be used to store all coal mine-related data (including the aforementioned first data).

[0061] In the above optional implementation, the technical effects that can be achieved are: real-time monitoring of mine safety-related conditions (such as production status, personnel status, equipment status, etc.), and real-time collection and storage of monitoring data, which facilitates the acquisition and utilization of a large amount of monitoring data (including historical monitoring data and real-time monitoring data) for disaster risk analysis, thereby improving the accuracy of disaster risk analysis and enabling timely and efficient mine disaster emergency rescue.

[0062] In an optional embodiment, in step S12, a disaster risk assessment of the mine is conducted based on disaster monitoring data, and the assessment results include:

[0063] Step S121: Use the risk assessment model to monitor the trend of disaster monitoring data and obtain the monitoring results. The risk assessment model is a neural network model obtained by machine learning using historical risk assessment data corresponding to the mine.

[0064] Step S122: Determine the evaluation results using the monitoring results and preset warning intervals.

[0065] In one optional scheme provided by steps S121 to S122 above, the risk assessment model can be a personalized model adapted to a specific mine disaster. Specifically, for example, the gas explosion risk assessment model for mine 1 corresponds to model a, the coal mine collapse risk assessment model for mine 1 corresponds to model b, the gas explosion risk assessment model for mine 2 corresponds to model c, and the coal mine collapse risk assessment model for mine 2 corresponds to model d. The monitoring results can include, but are not limited to: the development trend of multiple risk indicators, whether there is a risk in the mine, and what kind of risk exists in the mine. The historical risk assessment data can be the risk assessment data obtained by analyzing and predicting historical disaster monitoring data using the risk assessment model. The preset early warning interval can be the risk value range (or risk level) corresponding to multiple risk indicators respectively. Specifically, for example, the risk value range of the initial gas emission velocity ΔP is ΔP≥15, the risk value range of the coal mine firmness coefficient F is F≤0.5, and the risk level of the coal mine damage type is III, IV, or V.

[0066] In the solution provided by this invention, a risk assessment model is used to monitor the trend of disaster monitoring data to obtain monitoring results. Then, the monitoring results and a preset early warning interval are used to determine the assessment results. Specifically, the method can be as follows: based on one or more data in the disaster monitoring data, the corresponding risk indicators are determined, thereby determining multiple risk indicators. The risk assessment model is used to monitor and analyze the multiple risk indicators to determine the development trend of the multiple risk indicators. Then, the development trend of the multiple risk indicators is compared and analyzed with the preset early warning interval to obtain the mine disaster risk assessment results.

[0067] In an optional embodiment, in step S122, determining the evaluation result using the monitoring results and the preset warning interval includes:

[0068] Step S1221: Determine multiple current indicator values ​​for multiple disaster risk indicators corresponding to the mine based on the monitoring results;

[0069] Step S1222: Calculate using multiple current indicator values ​​to obtain comprehensive situation parameters;

[0070] Step S1223: In response to the comprehensive situation parameters being within the preset early warning range, determine that the assessment results meet the disaster risk conditions.

[0071] In one optional scheme provided by steps S1221 to S1223 above, the aforementioned multiple disaster risk indicators may include, but are not limited to: the risk level of the coal mine damage type, the initial gas emission velocity, and the original gas pressure of the coal seam. These multiple disaster risk indicators can be used to predict mine disasters and to extrapolate the development trend of disasters. It should also be noted that a combination of one or more of these multiple disaster risk indicators can correspond to different disaster risk levels. Specifically, for example, risk level III of the coal mine damage type corresponds to a low risk of coal mine collapse, risk level IV of the coal mine damage type corresponds to a low risk of coal mine collapse, and risk level V of the coal mine damage type corresponds to a low risk of coal mine collapse.

[0072] In one optional scheme provided by steps S1221 to S1223 above, the comprehensive situation parameters can be comprehensive parameters that correspond to specific mine disasters, such as the collapse index corresponding to coal mine collapse disasters and the gas index corresponding to coal mine gas explosion disasters (e.g., an index obtained by combining gas concentration and gas diffusion rate).

[0073] The following combination Figure 2 The above methods will be further explained.

[0074] Still as Figure 2 As shown, the 3D modeling system 206 is used to create 3D models of emergency routes based on disaster monitoring data collected by the data acquisition system 204. The risk warning system 207 is used to scientifically assess the overall situation of mine disasters based on their characteristics and mine data. Specifically, based on the characteristics of mine disasters and combined with basic data, real-time monitoring data, and historical disaster data of the mine area, it uses a disaster risk assessment model to analyze and monitor the changing trends of risk factors (i.e., the aforementioned multiple disaster risk indicators), and evaluate the degree to which various risk states deviate from the warning line (i.e., the aforementioned preset warning interval), thus scientifically assessing the overall situation and achieving disaster warning. Furthermore, the risk warning system 207 can also be used to send warning signals to the decision-making level. The warning system analyzes and processes the risk indicators based on the evaluation indicator system (which can be predetermined or determined in real time), and comprehensively evaluates the evaluation indicator system according to the warning model. Finally, based on the evaluation results, it sets warning intervals and determines the corresponding emergency rescue strategies for each warning interval.

[0075] In the above optional embodiments, the technical effects that can be achieved are: by performing three-dimensional modeling based on disaster monitoring data and combining multiple data such as disaster risk indicators and comprehensive situation parameters to conduct risk warnings for mine disasters, the mine disaster warning process is optimized, and the intelligent communication between the mine disaster warning system and other systems (such as decision-making systems) is strengthened. This can improve the accuracy of disaster risk warning results, enhance the intelligence level of mine disaster rescue methods, and further improve the efficiency of mine disaster emergency rescue.

[0076] In an optional embodiment, in step S13, in response to the assessment result meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are performed based on the assessment result and disaster monitoring data to obtain the target relief method, including:

[0077] Step S131: Use the simulation analysis model to simulate the disaster situation based on the assessment results and disaster monitoring data, and generate disaster simulation results. The simulation analysis model is a neural network model obtained by machine learning using historical disaster situation simulation data corresponding to the mine.

[0078] Step S132: Use the decision analysis model to make disaster relief decisions based on the disaster simulation results and disaster monitoring data, and determine the target relief method. The decision analysis model is a neural network model obtained by machine learning using historical disaster relief decision data corresponding to the mine.

[0079] In one optional scheme provided by steps S131 to S132 above, the aforementioned simulation analysis model may include, but is not limited to: multiple disaster situation analysis models, resource demand analysis and proximity scheduling models, and big data analysis models. The disaster simulation results may be the trend of the disaster situation within a preset time period, for example, the diffusion trend of methane gas inside the mine within one hour. The aforementioned historical disaster situation simulation data may include, but is not limited to: historical disaster situation simulation process data (such as historical disaster risk indicators, historical comprehensive situation parameters), and historical disaster situation simulation result data (such as historical risk assessment results). The aforementioned decision analysis model can, based on the target mine disaster determined by the disaster simulation results and combined with disaster monitoring data, provide a rescue strategy for the target mine disaster. The aforementioned historical disaster rescue decision data may include rescue strategies generated by historical decision analysis models or existing decision analysis models when target mine disasters occurred in the past.

[0080] In an optional embodiment, in step S131, the simulation analysis model includes: multiple disaster situation analysis sub-models, resource scheduling analysis sub-models, and big data analysis sub-models. The simulation analysis model is used to perform disaster situation simulation based on the assessment results and disaster monitoring data, generating disaster simulation results including:

[0081] Step S1311: Analyze the assessment results using multiple disaster situation analysis sub-models to obtain the first analysis result;

[0082] Step S1312: Analyze the assessment results and emergency resource data and historical disaster data in the disaster monitoring data using the resource scheduling analysis sub-model to obtain the second analysis result;

[0083] Step S1313: Use the big data analysis sub-model to perform situational simulation and optimization on the first and second analysis results, and generate disaster simulation results.

[0084] In one optional scheme provided by steps S1311 to S1312 above, each sub-model in the above-mentioned multiple disaster situation analysis sub-models can be used to analyze the assessment results of one or more disaster risk indicators. Each sub-model in the above-mentioned resource scheduling analysis sub-model can be used to analyze and determine the scheduling strategy for specific emergency resource data. The above-mentioned emergency resource data (including one or more of the aforementioned specific emergency resource data) may include, but is not limited to: fire-fighting resources and medical resources.

[0085] The following combination Figure 2 The above method will be further explained. As before... Figure 2 As shown, the auxiliary decision-making system 208 can assist mine disaster decision-makers in assessing the future development trend of current mine disasters and provide current mine disaster response plans and resource allocation plans. Specifically, based on comprehensive risk assessment results data, forecast data, emergency resource data, and other disaster-related data, it uses various disaster situation analysis models, resource demand analysis and local dispatch models, and big data analysis to generate disaster development trend projection results.

[0086] In the above optional embodiments, the technical effects that can be achieved are: by using multiple analysis models to conduct comprehensive and intelligent analysis of mine disaster-related data, the intelligence level of the mine disaster rescue decision-making process can be improved, the accuracy of mine disaster rescue decisions can be increased, and thus the efficiency of mine disaster rescue can be improved.

[0087] In an optional embodiment, in step S132, a disaster relief decision is made using a decision analysis model based on the disaster simulation results and disaster monitoring data, and the target relief method is determined, including:

[0088] Step S1321: Based on the disaster simulation results and disaster monitoring data, emergency route modeling is performed to obtain the initial rescue route;

[0089] Step S1322: Use the disaster analysis sub-model in the decision analysis model to perform real-time analysis on the disaster monitoring data to obtain real-time disaster results;

[0090] Step S1323: Based on the real-time disaster situation results, the initial rescue route is updated using the route decision sub-model in the decision analysis model to obtain the target rescue route, which includes the disaster avoidance route and the disaster relief route.

[0091] Step S1324: Determine the target rescue method based on the target rescue route.

[0092] In one optional scheme provided by steps S1321 to S1324 above, the initial rescue route can be obtained after preliminary three-dimensional modeling of disaster simulation results and disaster monitoring data. Specifically, this initial rescue route can be used to determine basic information about the rescue route, such as: overall rescue location, rescue depth, and total amount of rescue resources required. Each model in the above route decision sub-model can be used to determine detailed information about the rescue route, such as: detailed location of trapped personnel and allocation plan of rescue resources. The above disaster evacuation route can include one or more of the smoothest, shortest, and most optimized evacuation routes. The above disaster relief route can include one or more rescue routes for trapped individuals.

[0093] The following combination Figure 2 The above method will be further explained. As before... Figure 2 As shown, the auxiliary decision-making system 208 can also monitor on-site monitoring information, rescue progress, and resource allocation during mine disaster rescue operations in real time. During the rescue process, the system can acquire environmental monitoring data such as harmful gas concentration, temperature, and air volume, as well as personnel distribution in real time. It can also use decision analysis models combined with real-time disaster information to analyze the development of the disaster, dynamically update evacuation routes and rescue routes, and formulate and adjust disaster relief plans.

[0094] In the above optional embodiments, the technical effects that can be achieved are: timely modeling of emergency rescue routes for mine disasters, and rapid and intelligent determination of target rescue routes using decision analysis models based on real-time monitoring data, thereby improving the intelligence level of mine disaster rescue decision-making processes, increasing the accuracy of mine disaster rescue decisions, and thus improving the efficiency of mine disaster rescue and reducing casualties.

[0095] In an optional embodiment, in step S14, sending an emergency dispatch instruction according to the target rescue method includes at least one of the following:

[0096] Step S141: Generate and issue emergency command instructions based on the target rescue method. The emergency command instructions are used to guide emergency command operations for various types of personnel in the mine.

[0097] Step S142, assisting in emergency dispatch and rescue operations in the mine;

[0098] Step S143: Generate and send emergency communication instructions according to the target rescue method, wherein the emergency communication instructions are used to guide the emergency establishment operation of the real-time communication system corresponding to the mine;

[0099] Step S144: Generate and send a disaster warning instruction based on the target rescue method. The disaster warning instruction is used to guide the emergency release of disaster warning information corresponding to the mine.

[0100] In one of the optional solutions provided by steps S141 to S144 above, the above-mentioned multiple types of personnel may include, but are not limited to: decision-makers, dispatchers, duty personnel, rescuers, and experts. Each type of personnel can perform corresponding emergency rescue tasks.

[0101] The following combination Figure 2 The above method will be further explained. As before... Figure 2 As shown, the user management system 210 of the emergency command module 203 can be used to classify the user group of the intelligent emergency platform 200 into decision-makers, dispatchers, duty personnel, rescuers, and experts. The real-time communication system 211 of the emergency command module 203 can be a converged communication system that facilitates the transmission of text messages, data, voice, and video communication between two or more people. The early warning information release system 212 of the emergency command module 203 can automatically generate natural disaster early warning information based on the disaster emergency plan system, comprehensive risk assessment results, and disaster situation analysis results, according to early warning rules. In one optional implementation, the early warning information release system 212 can use message push technology based on the Socket-based Transmission Control Protocol (TCP) long connection method to push early warning information to relevant responsible persons, staff, and the general public in a targeted and accurate manner. The command and dispatch system 213 of the emergency command module 203 can conduct real-time command and dispatch of relevant responsible persons and staff based on the disaster development trend simulation results and the disaster response and resource allocation plans provided by the auxiliary decision-making system.

[0102] In the above optional embodiments, the technical effects that can be achieved are: optimizing the emergency command process for mine disasters, thereby improving the intelligence level of the emergency command process for mine disasters, improving the accuracy of emergency command and dispatch strategies for mine disasters, and thus improving the efficiency of mine disaster rescue and reducing casualties.

[0103] In an optional embodiment, after emergency dispatch and rescue of the mine according to the target rescue method, the mine disaster rescue method further includes:

[0104] Step S15: Calculate the rescue effectiveness parameter based on the rescue log data corresponding to the target rescue method. The rescue log data is used to record the full-process event information corresponding to emergency dispatch and rescue, and the rescue effectiveness parameter is used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to emergency dispatch and rescue.

[0105] Step S16: Use the rescue effectiveness parameters to revise and update the risk assessment model, extrapolation analysis model, and decision analysis model corresponding to the mine.

[0106] In one optional solution provided by steps S15 to S16 above, the rescue log data can be stored in... Figure 2 The database 205 of the intelligent emergency platform 200 shown can record intermediate data (such as rescue results for a certain time period) and outcome data (such as rescue data statistics) generated during the execution of the target rescue method. The aforementioned rescue effectiveness parameters can be used to evaluate the quality (or effectiveness) of the entire mine disaster emergency rescue process. The aforementioned estimated rescue losses can be obtained by utilizing... Figure 2 The data analysis module 202 shown estimates the rescue losses. The aforementioned actual rescue losses can be the actual losses incurred during the rescue operation conducted according to the target rescue method.

[0107] The following combination Figure 2 The above method will be further explained. As before... Figure 2 As shown, the post-disaster assessment system 209 of the data analysis module 202 can intuitively display information such as the cause of the disaster, the development process, and the results of the handling after the emergency rescue work of the mine disaster is completed. It can also evaluate the effectiveness of emergency decision-making and calculate the rescue benefits through model analysis. Furthermore, it can revise the disaster risk assessment model, the disaster situation analysis model, and the emergency plan assessment model by comparing the losses estimated by the model with the actual losses.

[0108] In the above optional embodiments, the technical effect that can be achieved is: to conduct a detailed analysis of the effectiveness of mine disaster rescue after a mine disaster occurs, and to promptly revise and update the data model of the entire mine disaster rescue process based on the analysis results, thereby improving the accuracy of the data model's modeling and analysis results, and thus comprehensively improving the rescue efficiency of each rescue process when a future mine disaster occurs.

[0109] The following combination Figure 3 The entire process of mine disaster rescue provided in the embodiments of the present invention is analyzed. Figure 3 This is a flowchart of an optional mine disaster rescue process according to an embodiment of the present invention. In one optional implementation, such as... Figure 3As shown, firstly, the data acquisition system collects real-time data from various front-end sensing devices, including emergency management department information systems, coal mine industrial safety video monitoring systems, underground worker management systems, and major equipment monitoring systems. This comprehensively monitors information such as enterprise safety production management processes, coal mine mining sites, working face safety officer information, coal mining faces, technical equipment, and air quality. Furthermore, the data acquisition system primarily divides the monitored data into structured data such as raw instantaneous values, average values, and cumulative values, as well as unstructured data such as mine maps, datasets from GIS, monitoring videos and images, emergency knowledge, contingency plans, and accident case studies. Finally, the collected data is stored in a database.

[0110] Still as Figure 3 As shown, the safety risk early warning system further utilizes various data points from the database for the current mining area, including spatial data and dynamic data from the actual production process of the coal mining enterprise. It analyzes these data using a disaster risk assessment model, monitors the changing trends of risk factors, and evaluates the degree to which various risk states deviate from the warning line, thus providing a scientific assessment of the overall situation. Furthermore, it determines whether there is a risk of disaster occurring in the current mining area. When such a risk exists, the early warning information dissemination system automatically generates natural disaster early warning information based on the disaster emergency response plan, comprehensive risk assessment results, and disaster situation analysis results, according to early warning rules. This information is then targeted and accurately pushed to relevant responsible persons, staff, and the general public to achieve disaster early warning.

[0111] Still as Figure 3 As shown, further, when there is a risk of disaster, an early warning signal is issued. At the same time, the auxiliary decision-making system, based on comprehensive risk assessment results, forecast data, emergency resource data and other disaster-related data, uses various disaster situation analysis models, resource demand analysis and local dispatch models and big data analysis to generate disaster development trend projection results, so as to assist decision-makers in judging the future development trend of disasters and provide disaster response plans and resource dispatch plans.

[0112] Still as Figure 3 As shown, the data acquisition system further collects on-site monitoring information, rescue progress, and resource allocation during disaster relief operations in real time. It also acquires environmental monitoring data such as harmful gas concentration, temperature, and air volume, as well as personnel distribution. Using analytical models (such as risk analysis models), it performs disaster analysis based on real-time disaster information, and then dynamically updates evacuation routes and rescue routes and formulates and adjusts disaster relief plans.

[0113] Still as Figure 3As shown, furthermore, the command and dispatch system is used to conduct real-time command and dispatch of relevant responsible persons and personnel. Simultaneously, decision-makers, dispatchers, on-duty personnel, rescue personnel, and experts can communicate in real-time using a converged communication system that transmits text messages, data, voice, and video. After the mine disaster rescue work is completed, information such as the cause of the disaster, its development process, and the results of the response is collected and stored in a database. Additionally, relevant data is retrieved using a post-disaster assessment system, and the effectiveness of emergency decisions is evaluated through model analysis, calculating benefits. By comparing the model-estimated losses with the actual losses, the disaster risk assessment model, disaster situation analysis model, and emergency plan evaluation model are revised.

[0114] The technical effects that can be achieved by the above-mentioned mine disaster rescue process provided in the embodiments of the present invention are as follows:

[0115] (1) Improve the scientific management level of coal mining;

[0116] (2) Enhance emergency rescue auxiliary decision-making capabilities and enrich efficient and comprehensive intelligent emergency rescue management and dispatch methods;

[0117] (3) To further improve emergency rescue capabilities and reduce the occurrence of major accidents and casualties.

[0118] In this embodiment, a mine disaster rescue device is also provided, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as described herein. As used below, a "module" is a combination of software and / or hardware that can perform a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0119] Figure 4 This is a structural block diagram of a mine disaster rescue device according to an embodiment of the present invention, such as... Figure 4 As shown, the device includes:

[0120] The acquisition module 401 is used to acquire disaster monitoring data of the mine;

[0121] Assessment module 402 is used to conduct disaster risk assessment based on disaster monitoring data and obtain assessment results;

[0122] Decision module 403 is used to respond to the assessment results meeting the disaster risk conditions, and to perform disaster situation simulation and disaster relief decision-making based on the assessment results and disaster monitoring data to obtain the target relief method;

[0123] The rescue module 404 is used to send emergency dispatch instructions according to the target rescue method. The emergency dispatch instructions are used to guide the emergency dispatch and rescue operations carried out in the mine.

[0124] Optionally, the acquisition module 401 is further configured to: acquire disaster monitoring data including first data and second data; and acquire disaster monitoring data of the mine including: acquiring first data, wherein the first data is acquired in real time by a variety of information acquisition devices installed in the mine, the variety of information acquisition devices including: environmental parameter acquisition devices, video acquisition devices, personnel information acquisition devices and equipment information acquisition devices; and monitor and statistically analyze the first data to obtain second data, wherein the second data includes structured datasets and unstructured datasets.

[0125] Optionally, the aforementioned assessment module 402 is further configured to: conduct a disaster risk assessment of the mine based on disaster monitoring data, and obtain assessment results including: using a risk assessment model to monitor the trend of indicators in the disaster monitoring data to obtain monitoring results, wherein the risk assessment model is a neural network model obtained by machine learning using the historical risk assessment data corresponding to the mine; and using the monitoring results and preset early warning intervals to determine the assessment results.

[0126] Optionally, the aforementioned assessment module 402 is further configured to: determine the assessment results using monitoring results and preset warning intervals, including: determining multiple current indicator values ​​of multiple disaster risk indicators corresponding to the mine based on monitoring results; calculating comprehensive situation parameters using multiple current indicator values; and determining that the assessment results meet disaster risk conditions in response to the comprehensive situation parameters being within the preset warning interval.

[0127] Optionally, the decision module 403 is further configured to: respond to the assessment results meeting the disaster risk conditions, perform disaster situation simulation and disaster relief decision-making based on the assessment results and disaster monitoring data, and obtain the target relief method, including: using a simulation analysis model to perform disaster situation simulation on the assessment results and disaster monitoring data, generating disaster simulation results, wherein the simulation analysis model is a neural network model obtained by machine learning using historical disaster situation simulation data corresponding to the mine; and using a decision analysis model to perform disaster relief decision-making on the disaster simulation results and disaster monitoring data, determining the target relief method, wherein the decision analysis model is a neural network model obtained by machine learning using historical disaster relief decision data corresponding to the mine.

[0128] Optionally, the decision module 403 is further configured to: use a simulation analysis model including a multi-disaster situation analysis sub-model, a resource scheduling analysis sub-model, and a big data analysis sub-model; use the simulation analysis model to perform disaster situation simulation on the assessment results and disaster monitoring data; and generate disaster simulation results by: using the multi-disaster situation analysis sub-model to analyze the assessment results and obtain a first analysis result; using the resource scheduling analysis sub-model to analyze the assessment results and emergency resource data and historical disaster data in the disaster monitoring data and obtain a second analysis result; and using the big data analysis sub-model to perform situation simulation optimization on the first analysis result and the second analysis result, thereby generating disaster simulation results.

[0129] Optionally, the decision module 403 is further configured to: make disaster relief decisions based on disaster simulation results and disaster monitoring data using a decision analysis model, and determine the target relief method, including: modeling emergency routes based on disaster simulation results and disaster monitoring data to obtain an initial relief route; using the disaster analysis sub-model in the decision analysis model to perform real-time analysis of disaster monitoring data to obtain real-time disaster results; updating the initial relief route based on the real-time disaster results using the route decision sub-model in the decision analysis model to obtain a target relief route, wherein the target relief route includes a disaster avoidance route and a disaster relief route; and determining the target relief method based on the target relief route.

[0130] Optionally, the rescue module 404 is further configured to: send emergency dispatch instructions according to the target rescue method, including at least one of the following: generating and issuing emergency command instructions according to the target rescue method, wherein the emergency command instructions are used to guide emergency command operations for various types of personnel corresponding to the mine; assisting in emergency dispatch and rescue operations for the mine; generating and sending emergency communication instructions according to the target rescue method, wherein the emergency communication instructions are used to guide the emergency establishment operation of the real-time communication system corresponding to the mine; generating and sending disaster warning instructions according to the target rescue method, wherein the disaster warning instructions are used to guide the emergency release operation of disaster warning information corresponding to the mine.

[0131] Optionally, Figure 5 This is a structural block diagram of another mine disaster rescue device according to an embodiment of the present invention, such as... Figure 5 As shown, the device includes Figure 4 In addition to all the modules shown, it also includes: an update module 405, which is used to calculate rescue effectiveness parameters based on the rescue log data corresponding to the target rescue method after emergency dispatch and rescue of the mine according to the target rescue method. The rescue log data is used to record the full-process event information corresponding to the emergency dispatch and rescue, and the rescue effectiveness parameters are used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to the emergency dispatch and rescue. The rescue effectiveness parameters are used to correct and update the risk assessment model, extrapolation analysis model and decision analysis model corresponding to the mine.

[0132] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0133] According to another aspect of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to perform the following steps via the computer program:

[0134] Step S1: Obtain disaster monitoring data for the mine;

[0135] Step S2: Conduct a disaster risk assessment based on disaster monitoring data to obtain the assessment results;

[0136] Step S3: In response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are carried out based on the assessment results and disaster monitoring data to obtain the target relief method;

[0137] Step S4: Send an emergency dispatch instruction according to the target rescue method. The emergency dispatch instruction is used to guide the emergency dispatch and rescue operations carried out in the mine.

[0138] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and their optional implementations, which will not be repeated here.

[0139] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0140] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0141] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces; the indirect coupling or communication connection of units or modules can be electrical or other forms.

[0142] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0145] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for mine disaster rescue, characterized in that, include: Obtain disaster monitoring data from mines; The disaster monitoring data is monitored for indicator trends using a risk assessment model to obtain monitoring results. The risk assessment model is a neural network model obtained by machine learning using historical risk assessment data corresponding to the mine. Based on the monitoring results, multiple current index values ​​of multiple disaster risk indicators corresponding to the mine are determined, wherein the multiple disaster risk indicators include the risk level of coal mine damage type, initial gas emission velocity, and original gas pressure of coal seam. The comprehensive situation parameters are obtained by calculating using the multiple current indicator values. If the comprehensive situation parameters are within the preset early warning range, the assessment results are determined to meet the disaster risk conditions. In response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are carried out based on the assessment results and the disaster monitoring data to obtain the target relief method; An emergency dispatch instruction is sent according to the target rescue method, wherein the emergency dispatch instruction is used to guide the emergency dispatch and rescue operation carried out on the mine; After conducting emergency dispatch and rescue of the mine according to the target rescue method, the mine disaster rescue method further includes: calculating rescue effectiveness parameters based on rescue log data corresponding to the target rescue method, wherein the rescue log data is used to record the full-process event information corresponding to the emergency dispatch and rescue, and the rescue effectiveness parameters are used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to the emergency dispatch and rescue; and using the rescue effectiveness parameters to correct and update the risk assessment model, inference analysis model, and decision analysis model corresponding to the mine, wherein the inference analysis model is a neural network model obtained by machine learning using historical disaster situation inference data corresponding to the mine, and the decision analysis model is a neural network model obtained by machine learning using historical disaster rescue decision data corresponding to the mine.

2. The mine disaster rescue method according to claim 1, characterized in that, The disaster monitoring data includes first data and second data. Obtaining the disaster monitoring data of the mine includes: The first data is acquired in real time by a variety of information acquisition devices installed in the mine, including: environmental parameter acquisition devices, video acquisition devices, personnel information acquisition devices, and equipment information acquisition devices. The first data is monitored and statistically analyzed to obtain the second data, which includes structured datasets and unstructured datasets.

3. The mine disaster rescue method according to claim 1, characterized in that, In response to the assessment results meeting the disaster risk conditions, disaster situation simulation and disaster relief decision-making are conducted based on the assessment results and the disaster monitoring data, resulting in the following target relief methods: The disaster situation is simulated using the assessment results and the disaster monitoring data through a simulation analysis model, and disaster simulation results are generated. The decision analysis model is used to make disaster relief decisions based on the disaster simulation results and the disaster monitoring data, and to determine the target relief method.

4. The mine disaster rescue method according to claim 3, characterized in that, The simulation analysis model includes: multiple disaster situation analysis sub-models, resource scheduling analysis sub-models, and big data analysis models. Using the simulation analysis model, disaster situation simulations are performed on the assessment results and the disaster monitoring data, generating the disaster simulation results, including: The assessment results are analyzed using the aforementioned multiple disaster situation analysis sub-models to obtain the first analysis result; The resource scheduling analysis sub-model is used to analyze the assessment results and the emergency resource data and historical disaster data in the disaster monitoring data to obtain a second analysis result; The first analysis result and the second analysis result are optimized by using the big data analysis sub-model to generate the disaster simulation result.

5. The mine disaster rescue method according to claim 4, characterized in that, Using decision analysis models to make disaster relief decisions based on disaster simulation results and disaster monitoring data, the target relief methods include: Based on the disaster simulation results and the disaster monitoring data, an emergency route model is constructed to obtain an initial rescue route; The disaster analysis sub-model in the decision analysis model is used to perform real-time analysis on the disaster monitoring data to obtain real-time disaster results. Based on the real-time disaster situation results, the initial rescue route is updated using the route decision sub-model in the decision analysis model to obtain the target rescue route, wherein the target rescue route includes a disaster avoidance route and a disaster relief route; Based on the target rescue route, determine the target rescue method.

6. The mine disaster rescue method according to claim 1, characterized in that, Sending the emergency dispatch instruction according to the target rescue method includes at least one of the following: Emergency command instructions are generated and issued according to the target rescue method, wherein the emergency command instructions are used to guide emergency command operations for various types of personnel corresponding to the mine; To assist in emergency dispatch and rescue operations at the aforementioned mine; An emergency communication instruction is generated and sent according to the target rescue method, wherein the emergency communication instruction is used to guide the emergency establishment operation of the real-time communication system corresponding to the mine; A disaster warning instruction is generated and sent according to the target rescue method, wherein the disaster warning instruction is used to guide the emergency release operation of disaster warning information corresponding to the mine.

7. A mine disaster rescue device, characterized in that, include: The acquisition module is used to acquire disaster monitoring data from the mine. The assessment module is used to monitor the trend of indicators in the disaster monitoring data using a risk assessment model to obtain monitoring results. The risk assessment model is a neural network model obtained through machine learning using historical risk assessment data corresponding to the mine. Based on the monitoring results, the module determines multiple current indicator values ​​for multiple disaster risk indicators corresponding to the mine. These multiple disaster risk indicators include the risk level of the coal mine damage type, the initial gas emission velocity, and the original gas pressure of the coal seam. The module calculates comprehensive situation parameters using these multiple current indicator values. If the comprehensive situation parameters are within a preset warning range, the module determines that the assessment results meet the disaster risk conditions. The decision-making module is used to respond to the assessment results meeting the disaster risk conditions, and to perform disaster situation simulation and disaster relief decision-making based on the assessment results and the disaster monitoring data to obtain the target relief method; The rescue module is used to send emergency dispatch instructions according to the target rescue method, wherein the emergency dispatch instructions are used to guide the emergency dispatch and rescue operations carried out on the mine. After conducting emergency dispatch and rescue operations at the mine according to the target rescue method, the mine disaster rescue device is further used to calculate rescue effectiveness parameters based on the rescue log data corresponding to the target rescue method. The rescue log data is used to record the full-process event information corresponding to the emergency dispatch and rescue, and the rescue effectiveness parameters are used to characterize the difference between the estimated rescue loss and the actual rescue loss corresponding to the emergency dispatch and rescue. The rescue effectiveness parameters are then used to correct and update the risk assessment model, extrapolation analysis model, and decision analysis model corresponding to the mine.

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