Coal spontaneous combustion early warning big data platform

Abstract

The invention discloses a coal spontaneous combustion early warning big data platform, which belongs to the technical field of mine fire prevention and extinguishing systems and comprises a coal spontaneous combustion early warning big data acquisition sub-platform, a coal spontaneous combustion early warning big data analysis sub-platform and a coal spontaneous combustion early warning big data release sub-platform which are connected in sequence. The coal spontaneous combustion early warning big data platform has the functions of data information acquisition, mining, analysis, early warning, suggestion pushing and fire extinguishing equipment operation control, and realizes graded management of mine coal spontaneous combustion disasters and guidance of disaster prevention and emergency rescue.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine fire prevention and extinguishing systems, and in particular relates to a coal spontaneous combustion early warning big data platform. Background Art

[0002] At present, the intelligent construction of mines is in full swing, and good results have been achieved in disaster prevention and control. However, due to the concealment and complexity of the development of coal spontaneous combustion fires, the intelligent level of its monitoring, early warning and disposal is low. The relevant software platform has only completed the real-time summary and preliminary analysis of coal spontaneous combustion fire monitoring data, and failed to achieve more specific coal spontaneous combustion hazard area determination, further coal spontaneous combustion hazard analysis and more accurate coal spontaneous combustion prevention and control.

[0003] The big data platform is a system that mines a large amount of data information to discover and utilize the most valuable data. All systems in coal mines generate data all the time. How to use this data to predict the development trend of coal spontaneous combustion fires and control them is a key step in realizing intelligent prevention and control of coal spontaneous combustion fires. Summary of the invention

[0004] The purpose of the present invention is to provide a coal spontaneous combustion early warning big data platform with the functions of data information collection, mining, analysis, early warning, and push suggestions, and control the operation of fire extinguishing equipment, so as to realize the hierarchical management of coal spontaneous combustion disasters in mines and guide disaster prevention and emergency rescue.

[0005] The technical solution adopted by the present invention is a coal spontaneous combustion early warning big data platform, which includes a coal spontaneous combustion early warning big data collection sub-platform, a coal spontaneous combustion early warning big data analysis sub-platform and a coal spontaneous combustion early warning big data release sub-platform connected in sequence.

[0006] The present invention is also characterized in that: The coal spontaneous combustion early warning big data collection sub-platform is used to input, collect, process and classify and store the basic information of the mine, the coal spontaneous combustion monitoring and early warning system and the disposal system; the coal spontaneous combustion early warning big data collection sub-platform includes the mine basic information input module, the coal spontaneous combustion prediction and forecasting system data collection module, the mine safety monitoring and surveillance system data collection module, the mine fire prevention and extinguishing system information collection module and other data input modules; The mine basic information entry module is used to process and classify and store manually entered geological conditions, basic parameters of the working face, and coal spontaneous combustion characteristic parameters; The data acquisition module of the coal spontaneous combustion prediction and forecasting system is used to collect, process and classify and store information of the bundle tube monitoring system, optical fiber temperature measurement system and distributed monitoring system; The data acquisition module of the mine safety monitoring system is used to collect, process and classify and store gas sensor system information, smoke sensor system information, and temperature sensor system information; The mine fire prevention and extinguishing system information acquisition module is used to collect, process and classify and store nitrogen injection system information, grouting system information and inhibitor system information; Other data input modules are used to process and classify and store manually entered manual analysis data, daily inspection reports, and supervisory and regulatory data.

[0007] Each module in the coal spontaneous combustion early warning big data collection sub-platform uses natural language processing technology and knowledge graph technology to clean, classify and integrate the collected and entered data to form structured data, and store them in the corresponding modules.

[0008] The coal spontaneous combustion early warning big data analysis sub-platform analyzes the dangerous areas and dangers of coal spontaneous combustion based on the mine data provided by the coal spontaneous combustion early warning big data collection sub-platform, and warns and evaluates the dangerous state; the coal spontaneous combustion early warning big data analysis sub-platform includes the goaf flow field distribution simulation analysis module, goaf spontaneous combustion danger area analysis module, coal spontaneous combustion classification multi-state early warning module, and mine spontaneous combustion danger evaluation module; The goaf flow field distribution simulation analysis module is connected to the goaf spontaneous combustion hazard area analysis module and the coal spontaneous combustion prediction and forecasting system data acquisition module; the coal spontaneous combustion graded multi-state warning module is connected to the mine spontaneous combustion hazard evaluation module, the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module, and other data entry modules; the mine spontaneous combustion hazard evaluation module is connected to the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module; The goaf flow field distribution simulation and analysis module is used to construct the working face flow field model using CFD simulation software with the data provided by the coal spontaneous combustion prediction and forecasting data acquisition module; the working face flow field model includes air leakage flow field model, oxygen concentration flow field model, and temperature field model; The goaf spontaneous combustion hazard zone analysis module uses the working face flow field model provided by the goaf flow field distribution simulation analysis module combined with the oxygen concentration method to divide the goaf into three spontaneous combustion zones: heat dissipation zone, oxidation zone and asphyxiation zone. The oxidation zone is the goaf spontaneous combustion hazard zone, and the minimum advancement speed of the working face is calculated based on the oxidation zone. The calculation formula for the minimum advancement speed of the working face is as follows:

[0009] In the formula, is the minimum safe propulsion speed, m / d; is the safety factor; is the maximum width of the oxidation zone, m; is the shortest natural combustion period of the coal seam, d; The coal spontaneous combustion graded multi-state early warning module, based on the built-in coal spontaneous combustion degree graded early warning system, compares the gas and temperature data collected by the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring system data acquisition module and other data entry modules with the threshold of the coal spontaneous combustion degree graded early warning system, and warns the development trend of coal spontaneous combustion and outputs the early warning results; The mine spontaneous combustion hazard assessment module is used to evaluate the current coal spontaneous combustion hazard level based on the warning results output by the coal spontaneous combustion graded multi-state warning module, combined with the data provided by the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module, using the fuzzy comprehensive evaluation method.

[0010] The coal spontaneous combustion early warning big data publishing sub-platform displays and pushes the coal spontaneous combustion early warning information and disposal management information in a multi-state manner according to the analysis and early warning results output by the coal spontaneous combustion early warning big data analysis sub-platform, and controls the remote control of the fire prevention and extinguishing system; the coal spontaneous combustion early warning big data publishing sub-platform includes the mine daily hierarchical management suggestion module, the expert intelligent auxiliary decision-making suggestion module, the fire warning information icon display module, the fire warning information push module, and the fire prevention and extinguishing system remote control module; The fire warning information icon display module is connected to the fire warning information push module, the coal spontaneous combustion graded multi-state warning module, and the mine spontaneous combustion hazard assessment module; the fire prevention and extinguishing system remote control module is connected to the mine daily graded management suggestion module and the expert intelligent auxiliary decision-making suggestion module; The mine daily hierarchical management suggestion module is used to divide the mine daily management level and push hierarchical management measures suggestions based on industry standards and mine production status; The expert intelligent auxiliary decision-making suggestion module pushes targeted measures and suggestions that match the current warning level and danger based on the coal spontaneous combustion hazard analysis results output by the mine spontaneous combustion hazard assessment module, combined with industry standards and expert knowledge base; The fire warning information icon display module displays continuous data, curves and graphics based on the coal spontaneous combustion development trend and hazard level output by the coal spontaneous combustion graded multi-state warning module and the mine spontaneous combustion hazard assessment module; The fire warning information push module is used to push the data and curves in the fire warning information chart display module to the monitoring room sound and light alarm, mobile phone text messages and APP messages; The remote control module of the fire prevention and extinguishing system is used for data transmission between the coal spontaneous combustion early warning big data platform and various fire prevention and extinguishing systems on the coal mine site. According to the measures recommended by the mine daily hierarchical management suggestion module and the expert intelligent auxiliary decision-making suggestion module, it remotely sends instructions to control the start or shut down of the fire prevention and extinguishing equipment and feedback the operating parameters of the equipment.

[0011] The beneficial effects of the present invention are: The coal spontaneous combustion early warning big data platform of the present invention establishes a coal spontaneous combustion early warning big data platform from three aspects: data collection, data analysis, and result release. It can obtain the coal spontaneous combustion hazard in key areas by collecting, classifying, correlating, mining, analyzing and publishing data information related to underground spontaneous combustion fires, predict the scope and degree of possible spontaneous combustion, push coal spontaneous combustion graded early warning results and targeted management and disposal suggestions, and control the operation of related fire prevention and extinguishing equipment, so as to realize the graded management of coal spontaneous combustion disasters in mines and guide disaster prevention and emergency rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a structural schematic diagram of the coal spontaneous combustion early warning big data platform of the present invention; Figure 2 It is a schematic diagram of the structure of the acquisition sub-platform of the coal spontaneous combustion early warning big data platform of the present invention; Figure 3 It is a schematic diagram of the structure of the analysis sub-platform of the coal spontaneous combustion early warning big data platform of the present invention; Figure 4 It is a schematic diagram of the structure of the publishing sub-platform of the coal spontaneous combustion early warning big data platform of the present invention. DETAILED DESCRIPTION

[0013] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] The coal spontaneous combustion early warning big data platform of the present invention is as follows: Figure 1 As shown, it includes a coal spontaneous combustion early warning big data collection sub-platform, a coal spontaneous combustion early warning big data analysis sub-platform and a coal spontaneous combustion early warning big data release sub-platform which are connected in sequence.

[0015] The coal spontaneous combustion early warning big data collection sub-platform is used to input, collect, process and classify the basic information of the mine, the coal spontaneous combustion monitoring and early warning system, and the disposal system, providing basic data for further analysis of the coal spontaneous combustion status.

[0016] The coal spontaneous combustion early warning big data collection sub-platform includes mine basic information entry module, coal spontaneous combustion prediction and forecasting system data collection module, mine safety monitoring and surveillance system data collection module, mine fire prevention and extinguishing system information collection module, and other data input modules, such as Figure 2 shown.

[0017] The mine basic information entry module is used to process and classify and store manually entered geological conditions, basic parameters of the working face, and coal spontaneous combustion characteristic parameters; The data acquisition module of the coal spontaneous combustion prediction and forecasting system is used to collect, process and classify and store information of the bundle tube monitoring system, optical fiber temperature measurement system and distributed monitoring system; The data acquisition module of the mine safety monitoring system is used to collect, process and classify and store gas sensor system information, smoke sensor system information, and temperature sensor system information; The mine fire prevention and extinguishing system information acquisition module is used to collect, process and classify and store nitrogen injection system information, grouting system information and inhibitor system information; Other data input modules are used to process and classify and store manually entered manual analysis data, daily inspection reports, and supervisory and regulatory data.

[0018] Among them, the data acquisition module of the coal spontaneous combustion prediction and forecasting system, the data acquisition module of the mine safety monitoring and surveillance system, and the information acquisition module of the mine fire prevention and extinguishing system connect data information to the coal spontaneous combustion early warning big data acquisition sub-platform through a hybrid transmission method combining wired and wireless transmission, thereby realizing the intelligent collection of coal spontaneous combustion early warning data information, and can add monitoring systems, sensor systems, and fire prevention and extinguishing systems according to actual conditions.

[0019] The coal spontaneous combustion early warning big data collection sub-platform uses natural language processing technology and knowledge graph technology to clean, classify and integrate the collected data information to form structured data, and store it in categories for further query, call and analysis by the coal spontaneous combustion early warning big data analysis sub-platform.

[0020] The coal spontaneous combustion early warning big data analysis sub-platform, based on the basic data provided by the coal spontaneous combustion early warning big data collection sub-platform, analyzes the dangerous areas and dangers of coal spontaneous combustion, and warns and evaluates the dangerous status.

[0021] The coal spontaneous combustion early warning big data analysis sub-platform includes the goaf flow field distribution simulation analysis module, the goaf spontaneous combustion hazard area analysis module, the coal spontaneous combustion classification multi-state early warning module, and the mine spontaneous combustion hazard assessment module. Figure 3 As shown. Among them, the goaf flow field distribution simulation analysis module is connected to the goaf spontaneous combustion hazard area analysis module and the coal spontaneous combustion prediction and forecasting system data acquisition module; the coal spontaneous combustion graded multi-state warning module is connected to the mine spontaneous combustion hazard assessment module, the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module, and other data entry modules; the mine spontaneous combustion hazard assessment module is connected to the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module.

[0022] The goaf flow field distribution simulation analysis module is used to construct the working face flow field model using CFD simulation software with the data provided by the coal spontaneous combustion prediction and forecasting data acquisition module, and provide it to the goaf spontaneous combustion hazard area analysis module for dividing the goaf spontaneous combustion "three zones" and calculating the minimum advancement speed of the working face. The working face flow field model includes the air leakage flow field model, the oxygen concentration flow field model, and the temperature field model.

[0023] The goaf spontaneous combustion hazard zone analysis module uses the working face flow field model provided by the goaf flow field distribution simulation analysis module combined with the oxygen concentration method to divide the goaf into three spontaneous combustion zones: heat dissipation zone (oxygen concentration>18%), oxidation zone (5%≤oxygen concentration≤18%) and asphyxiation zone (oxygen concentration<5%), thereby obtaining the range and location of the three spontaneous combustion zones in the goaf, among which the oxidation zone range is the goaf spontaneous combustion hazard zone, and the minimum advancement speed of the working face is calculated based on the oxidation zone. The minimum advancement speed calculated based on the oxidation zone range is output to the daily hierarchical management suggestion module and the expert intelligent auxiliary decision-making suggestion module to provide the mine with a safe reference value for the daily advancement speed.

[0024] The calculation formula for the minimum advancement speed of the working face is as follows:

[0025] In the formula, is the minimum safe propulsion speed, m / d; is the safety factor; is the maximum width of the oxidation zone, m; is the shortest natural combustion period of coal seam, d.

[0026] The coal spontaneous combustion graded multi-state early warning module, based on the built-in coal spontaneous combustion degree graded early warning system, compares the gas and temperature data collected by the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and surveillance system data acquisition module and other data entry modules with the threshold of the coal spontaneous combustion degree graded early warning system, and warns of the development trend of coal spontaneous combustion and outputs the early warning results.

[0027] The coal spontaneous combustion degree classification warning system can adopt the warning method system of patent number CN109184800B, set the corresponding threshold value according to the current production situation of the mine, and then compare the gas and temperature data collected by the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module and other data entry modules with the set threshold value to obtain the warning level under the current gas and temperature, and carry out graded warning of the coal spontaneous combustion degree of the mine according to the spontaneous combustion ignition stage corresponding to the level. Table 1 is an example of the coal spontaneous combustion degree classification warning system.

[0028] Table 1 Classification and early warning system for coal spontaneous combustion degree

[0029] The mine spontaneous combustion hazard assessment module is used to evaluate the current coal spontaneous combustion hazard level based on the warning results output by the coal spontaneous combustion graded multi-state warning module, combined with the data provided by the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module, using the fuzzy comprehensive evaluation method.

[0030] The evaluation method is as follows: Step 1, construct an evaluation index set; The mining process design, coal spontaneous combustion properties, coal seam geological structure and fire prevention and extinguishing technology in the data provided by the mine basic information entry module, coal spontaneous combustion prediction and forecasting system data acquisition module, and mine fire prevention and extinguishing system information acquisition module are set as first-level indicators, and the variables included in each first-level indicator are set as corresponding second-level indicators. The evaluation indicator set is constructed as follows: (1) In the formula, is the evaluation index set; Each secondary indicator, is the number of secondary indicators; Step 2: Construct an evaluation set; (2) In the formula, V is the constructed evaluation and v represents the evaluation level, which is divided into safe, low risk, medium risk and high risk; is the number of evaluation levels; Step 3: Determine the weight of the evaluation indicators; The analytic hierarchy process is used to determine the weights of each indicator in step 1, and each secondary indicator The weight of ; is the weight of each secondary indicator; Step 4: Establish membership; Based on the evaluation indicators in step 1 and the evaluation set in step 2, the fuzzy relationship matrix of each indicator is established by expert scoring: (3) In the formula, R is the fuzzy relationship matrix of each indicator; The degree of membership of each secondary indicator corresponding to different evaluation levels; Step 5: Calculate the fuzzy comprehensive evaluation set; (4) In the formula, is the fuzzy comprehensive evaluation set, is the degree of membership of the evaluation level.

[0031] The coal spontaneous combustion early warning big data publishing sub-platform, based on the analysis and early warning results output by the coal spontaneous combustion early warning big data analysis sub-platform, displays and pushes the coal spontaneous combustion early warning information and disposal management information in a polymorphic manner in real time, and controls the remote control of the fire prevention and extinguishing system.

[0032] The coal spontaneous combustion early warning big data publishing sub-platform includes daily mine graded management suggestion module, expert intelligent auxiliary decision suggestion module, fire warning information icon display module, fire warning information push module, and fire prevention and extinguishing system remote control module. Figure 4 The fire warning information icon display module is connected to the fire warning information push module, the coal spontaneous combustion graded multi-state warning module, and the mine spontaneous combustion hazard assessment module; the fire prevention and extinguishing system remote control module is connected to the mine daily graded management suggestion module and the expert intelligent auxiliary decision suggestion module.

[0033] The mine daily hierarchical management suggestion module is used to divide the mine daily management level and push hierarchical management measures suggestions based on industry standards and mine production status; The expert intelligent auxiliary decision-making suggestion module pushes targeted measures and suggestions that match the current warning level and danger based on the coal spontaneous combustion hazard analysis results output by the mine spontaneous combustion hazard assessment module, combined with industry standards and expert knowledge base; The fire warning information icon display module displays continuous data, curves and graphics based on the coal spontaneous combustion development trend and hazard level output by the coal spontaneous combustion graded multi-state warning module and the mine spontaneous combustion hazard assessment module; The fire warning information push module is used to push the data and curves in the fire warning information chart display module to the monitoring room sound and light alarm, mobile phone text messages and APP messages; The remote control module of the fire prevention and extinguishing system is used for data transmission between the coal spontaneous combustion early warning big data platform and various fire prevention and extinguishing systems on the coal mine site. According to the measures recommended by the mine daily hierarchical management suggestion module and the expert intelligent auxiliary decision-making suggestion module, it remotely sends instructions to control the start or shut down of the fire prevention and extinguishing equipment and feedback the operating parameters of the equipment.

[0034] The coal spontaneous combustion early warning big data publishing sub-platform can issue specific recommended measures to on-site operators based on the analysis and early warning results output by the coal spontaneous combustion early warning big data analysis sub-platform, and intelligently control the operating status of the fire prevention and extinguishing system.

[0035] Example 1 This embodiment provides a coal spontaneous combustion early warning big data platform, such as Figure 1 As shown, it includes a coal spontaneous combustion early warning big data collection sub-platform, a coal spontaneous combustion early warning big data analysis sub-platform and a coal spontaneous combustion early warning big data release sub-platform which are connected in sequence.

[0036] Example 2 On the basis of Example 1, Figure 2As shown, the coal spontaneous combustion early warning big data collection sub-platform is used to input, collect, process and classify and store the basic information of the mine, the coal spontaneous combustion monitoring and early warning system, and the disposal system; the coal spontaneous combustion early warning big data collection sub-platform includes a mine basic information input module, a coal spontaneous combustion prediction and forecasting system data collection module, a mine safety monitoring and surveillance system data collection module, a mine fire prevention and extinguishing system information collection module, and other data input modules; The mine basic information entry module is used to process and classify and store manually entered geological conditions, basic parameters of the working face, and coal spontaneous combustion characteristic parameters; The data acquisition module of the coal spontaneous combustion prediction and forecasting system is used to collect, process and classify and store information of the bundle tube monitoring system, optical fiber temperature measurement system and distributed monitoring system; The data acquisition module of the mine safety monitoring system is used to collect, process and classify and store gas sensor system information, smoke sensor system information, and temperature sensor system information; The mine fire prevention and extinguishing system information acquisition module is used to collect, process and classify and store nitrogen injection system information, grouting system information and inhibitor system information; Other data input modules are used to process and classify and store manually entered manual analysis data, daily inspection reports, and supervisory and regulatory data.

[0037] Each module in the coal spontaneous combustion early warning big data collection sub-platform uses natural language processing technology and knowledge graph technology to clean, classify and integrate the collected and entered data to form structured data, and store them in the corresponding modules.

[0038] Example 3 On the basis of Example 2, Figure 3 As shown, the coal spontaneous combustion early warning big data analysis sub-platform, based on the mine data provided by the coal spontaneous combustion early warning big data collection sub-platform, analyzes the dangerous areas and dangers of coal spontaneous combustion, and warns and evaluates the dangerous state; the coal spontaneous combustion early warning big data analysis sub-platform includes goaf flow field distribution simulation analysis module, goaf spontaneous combustion danger area analysis module, coal spontaneous combustion graded multi-state early warning module, and mine spontaneous combustion danger evaluation module; The goaf flow field distribution simulation analysis module is connected to the goaf spontaneous combustion hazard area analysis module and the coal spontaneous combustion prediction and forecasting system data acquisition module; the coal spontaneous combustion graded multi-state warning module is connected to the mine spontaneous combustion hazard evaluation module, the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module, and other data entry modules; the mine spontaneous combustion hazard evaluation module is connected to the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module; The goaf flow field distribution simulation and analysis module is used to construct the working face flow field model using CFD simulation software with the data provided by the coal spontaneous combustion prediction and forecasting data acquisition module; the working face flow field model includes air leakage flow field model, oxygen concentration flow field model, and temperature field model; The goaf spontaneous combustion hazard zone analysis module uses the working face flow field model provided by the goaf flow field distribution simulation analysis module combined with the oxygen concentration method to divide the goaf into three spontaneous combustion zones: heat dissipation zone, oxidation zone and asphyxiation zone. The oxidation zone is the goaf spontaneous combustion hazard zone, and the minimum advancement speed of the working face is calculated based on the oxidation zone. The calculation formula for the minimum advancement speed of the working face is as follows:

[0039] In the formula, is the minimum safe propulsion speed, m / d; is the safety factor; is the maximum width of the oxidation zone, m; is the shortest natural combustion period of the coal seam, d; The coal spontaneous combustion graded multi-state early warning module, based on the built-in coal spontaneous combustion degree graded early warning system, compares the gas and temperature data collected by the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring system data acquisition module and other data entry modules with the threshold of the coal spontaneous combustion degree graded early warning system, and warns the development trend of coal spontaneous combustion and outputs the early warning results; The mine spontaneous combustion hazard assessment module is used to evaluate the current coal spontaneous combustion hazard level based on the warning results output by the coal spontaneous combustion graded multi-state warning module, combined with the data provided by the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module, using the fuzzy comprehensive evaluation method.

[0040] like Figure 4 As shown, the coal spontaneous combustion early warning big data publishing sub-platform displays and pushes the coal spontaneous combustion early warning information and disposal management information in a polymorphic manner according to the analysis and early warning results output by the coal spontaneous combustion early warning big data analysis sub-platform, and controls the remote control of the fire prevention and extinguishing system; the coal spontaneous combustion early warning big data publishing sub-platform includes a mine daily hierarchical management suggestion module, an expert intelligent auxiliary decision-making suggestion module, a fire warning information icon display module, a fire warning information push module, and a fire prevention and extinguishing system remote control module; The fire warning information icon display module is connected to the fire warning information push module, the coal spontaneous combustion graded multi-state warning module, and the mine spontaneous combustion hazard assessment module; the fire prevention and extinguishing system remote control module is connected to the mine daily graded management suggestion module and the expert intelligent auxiliary decision-making suggestion module; The mine daily hierarchical management suggestion module is used to divide the mine daily management level and push hierarchical management measures suggestions based on industry standards and mine production status; The expert intelligent auxiliary decision-making suggestion module pushes targeted measures and suggestions that match the current warning level and danger based on the coal spontaneous combustion hazard analysis results output by the mine spontaneous combustion hazard assessment module, combined with industry standards and expert knowledge base; The fire warning information icon display module displays continuous data, curves and graphics based on the coal spontaneous combustion development trend and hazard level output by the coal spontaneous combustion graded multi-state warning module and the mine spontaneous combustion hazard assessment module; The fire warning information push module is used to push the data and curves in the fire warning information chart display module to the monitoring room sound and light alarm, mobile phone text messages and APP messages; The remote control module of the fire prevention and extinguishing system is used for data transmission between the coal spontaneous combustion early warning big data platform and various fire prevention and extinguishing systems on the coal mine site. According to the measures recommended by the mine daily hierarchical management suggestion module and the expert intelligent auxiliary decision-making suggestion module, it remotely sends instructions to control the start or shut down of the fire prevention and extinguishing equipment and feedback the operating parameters of the equipment.

Claims

1. Coal spontaneous combustion early warning big data platform, characterized by: It includes a coal spontaneous combustion early warning big data collection sub-platform, a coal spontaneous combustion early warning big data analysis sub-platform and a coal spontaneous combustion early warning big data release sub-platform which are connected in sequence.

2. The coal spontaneous combustion early warning big data platform according to claim 1 is characterized in that: The coal spontaneous combustion early warning big data collection sub-platform is used to input, collect, process and classify and store the basic information of the mine, the coal spontaneous combustion monitoring and early warning system, and the disposal system; the coal spontaneous combustion early warning big data collection sub-platform includes a mine basic information input module, a coal spontaneous combustion prediction and forecasting system data collection module, a mine safety monitoring and control system data collection module, a mine fire prevention and extinguishing system information collection module, and other data input modules; The mine basic information input module is used to process and classify and store manually entered geological conditions, working face basic parameters, and coal spontaneous combustion characteristic parameters; The data acquisition module of the coal spontaneous combustion prediction and forecasting system is used to collect, process and classify and store information of the bundle tube monitoring system, information of the optical fiber temperature measurement system and information of the distributed monitoring system; The mine safety monitoring and control system data acquisition module is used to collect, process and classify and store gas sensor system information, smoke sensor system information and temperature sensor system information; The mine fire prevention and extinguishing system information acquisition module is used to collect, process and classify and store nitrogen injection system information, grouting system information and inhibitor system information; The other data input modules are used to process and classify and store manually entered manual analysis data, daily inspection reports, and supervisory and regulatory data.

3. The coal spontaneous combustion early warning big data platform according to claim 2 is characterized in that: Each module in the coal spontaneous combustion early warning big data collection sub-platform uses natural language processing technology and knowledge graph technology to clean, classify and integrate the collected and entered data to form structured data, and classify and store them in the corresponding modules.

4. The coal spontaneous combustion early warning big data platform according to claim 2 or 3, characterized in that: The coal spontaneous combustion early warning big data analysis sub-platform analyzes the dangerous areas and dangers of coal spontaneous combustion risks, and warns and evaluates dangerous states based on the mine data provided by the coal spontaneous combustion early warning big data collection sub-platform; the coal spontaneous combustion early warning big data analysis sub-platform includes a goaf flow field distribution simulation analysis module, a goaf spontaneous combustion danger area analysis module, a coal spontaneous combustion graded multi-state early warning module, and a mine spontaneous combustion danger evaluation module; The goaf flow field distribution simulation analysis module is connected to the goaf spontaneous combustion hazard area analysis module and the coal spontaneous combustion prediction and forecasting system data acquisition module; the coal spontaneous combustion graded multi-state early warning module is connected to the mine spontaneous combustion hazard assessment module, the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module, and other data entry modules; the mine spontaneous combustion hazard assessment module is connected to the mine basic information entry module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module; The goaf flow field distribution simulation and analysis module is used to construct a working face flow field model using CFD simulation software based on the data provided by the coal spontaneous combustion prediction and forecasting data acquisition module; the working face flow field model includes an air leakage flow field model, an oxygen concentration flow field model, and a temperature field model; The goaf spontaneous combustion hazard zone analysis module uses the working face flow field model provided by the goaf flow field distribution simulation analysis module combined with the oxygen concentration method to divide the goaf into three spontaneous combustion zones: heat dissipation zone, oxidation zone and asphyxiation zone, among which the oxidation zone is the goaf spontaneous combustion hazard zone, and the minimum advancement speed of the working face is calculated based on the oxidation zone; The calculation formula for the minimum advancement speed of the working face is as follows: In the formula, is the minimum safe propulsion speed, m / d; is the safety factor; is the maximum width of the oxidation zone, m; is the shortest natural combustion period of the coal seam, d; The coal spontaneous combustion graded polymorphic early warning module, based on the built-in coal spontaneous combustion degree graded early warning system, compares the gas and temperature data collected by the coal spontaneous combustion prediction and forecasting system data acquisition module, the mine safety monitoring and control system data acquisition module and other data entry modules with the threshold value of the coal spontaneous combustion degree graded early warning system, and warns the development trend of coal spontaneous combustion and outputs the early warning result; The mine spontaneous combustion hazard assessment module is used to evaluate the current coal spontaneous combustion hazard level using a fuzzy comprehensive evaluation method based on the warning results output by the coal spontaneous combustion graded multi-state warning module, combined with the data provided by the mine basic information input module, the coal spontaneous combustion prediction and forecasting system data acquisition module, and the mine fire prevention and extinguishing system information acquisition module.

5. The coal spontaneous combustion early warning big data platform according to claim 4 is characterized in that: The coal spontaneous combustion early warning big data publishing sub-platform displays and pushes the coal spontaneous combustion early warning information and disposal management information in a polymorphic manner according to the analysis and early warning results output by the coal spontaneous combustion early warning big data analysis sub-platform, and controls the remote control of the fire prevention and extinguishing system; the coal spontaneous combustion early warning big data publishing sub-platform includes a mine daily hierarchical management suggestion module, an expert intelligent auxiliary decision-making suggestion module, a fire warning information icon display module, a fire warning information push module, and a fire prevention and extinguishing system remote control module; The fire warning information icon display module is connected to the fire warning information push module, the coal spontaneous combustion graded multi-state warning module, and the mine spontaneous combustion risk assessment module; the fire prevention and extinguishing system remote control module is connected to the mine daily graded management suggestion module and the expert intelligent auxiliary decision-making suggestion module; The mine daily hierarchical management suggestion module is used to divide the mine daily management level and push hierarchical management measures suggestions in combination with industry norms and mine production status; The expert intelligent auxiliary decision-making suggestion module pushes targeted measures and suggestions matching the current warning level and danger based on the coal spontaneous combustion hazard analysis results output by the mine spontaneous combustion hazard assessment module, combined with industry specifications and expert knowledge base; The fire warning information icon display module performs continuous data display, curve display and graphic display according to the coal spontaneous combustion development trend and hazard level output by the coal spontaneous combustion graded multi-state warning module and the mine spontaneous combustion hazard assessment module; The fire warning information push module is used to push the data and curves in the fire warning information chart display module to the monitoring room sound and light alarm, mobile phone text messages and APP messages; The fire prevention and extinguishing system remote control module is used for data transmission between the coal spontaneous combustion early warning big data platform and various fire prevention and extinguishing systems on the coal mine site. It remotely sends instructions to control the startup or shutdown of the fire prevention and extinguishing equipment based on the measures recommended by the mine daily hierarchical management suggestion module and the expert intelligent auxiliary decision-making suggestion module, and feeds back the operating parameters of the equipment.

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