A coal mine intelligent fire prevention and extinguishing early warning method and system

Abstract

The present application belongs to the technical field of intelligent fire prevention and early warning, and discloses a coal mine intelligent fire prevention and early warning method. The specific operation steps of the coal mine intelligent fire prevention and early warning are as follows: S1: identifying fire prevention and control objects, which include coal spontaneous combustion danger zones, fire zones and exogenous fire risk points; S2: measuring and evaluating the fire risk of the prevention and control objects; S3: setting corresponding early warnings according to the risk characteristics of the fire risk objects; S4: setting the indexes and grades of the early warnings, which include setting early warning indexes and setting early warning grades, and the early warning grades include normal, signs, development and disaster; and S5: implementing mine fire prevention and control measures according to the grades. This method can improve the limitation of early warning transmission, and can realize long-distance monitoring and control of fire monitoring, so as to improve the safety of coal mining.

Description

Technical Field

[0001] This invention belongs to the field of intelligent fire prevention and extinguishing early warning technology, specifically a method and system for intelligent fire prevention and extinguishing early warning in coal mines. Background Technology

[0002] my country is one of the world's largest consumers of mineral resources. With the rapid development of my country's economy, the demand for mineral resources is enormous. Coal is one of my country's main energy sources. Mine fires are prone to occur during coal mining. Currently, most coal mine fires are caused by spontaneous combustion. Related prediction technologies usually utilize the physical properties of coal, mainly using spectral analysis technology, supplemented by statistical techniques, to ultimately predict spontaneous combustion in coal mines. Existing coal mine fire monitoring technologies still tend to analyze hazards through smoke and open flames. This approach can easily lead to limited early warning dissemination and makes it difficult to achieve long-distance monitoring and control of fires, thus posing a significant obstacle to improving the safety of coal mining. Therefore, an intelligent coal mine fire prevention and extinguishing early warning method and system is proposed. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for intelligent fire prevention and extinguishing in coal mines, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent fire prevention and extinguishing early warning in coal mines, wherein the specific operation steps for intelligent fire prevention and extinguishing early warning in coal mines are as follows:

[0005] S1: Identify the targets for fire prevention and control.

[0006] The identified fire prevention targets include: coal spontaneous combustion hazard zones, fire zones, and external fire risk points.

[0007] The coal spontaneous combustion risk zone needs to establish the spontaneous combustion characteristics of the target coal seam, mainly including basic data such as indicator gas data determined by programmed temperature rise measurement of coal samples, coal seam characteristics, mining method of the working face and corresponding goaf characteristics, and regionally related air leakage characteristics.

[0008] The fire zone targets refer to the management of existing fire zones in the mine, including the fire zone closure time, basic sealing parameters, basic characteristics of fire zone combustion, main fire zone control measures, main fire zone management measures, and responsible persons. The external fire prevention targets mainly include: belt conveyors, electromechanical chambers, combustible material storage chambers, charging chambers, and underground explosives depots. Each of the external fire prevention targets also includes location, main fire risks, fire protection facilities and materials, and the types and number of alarm detectors.

[0009] S2: To determine and assess the fire risk of objects and prevent fire hazards;

[0010] S3: Set corresponding early warnings based on the risk characteristics of objects at risk of fire;

[0011] S4: Set the indicators and levels for early warning.

[0012] The set indicators and levels for early warning include: setting early warning indicators and setting early warning levels.

[0013] The defined early warning levels include normal, symptom, development, and disaster.

[0014] S5: Implement mine fire prevention measures according to the classification level.

[0015] Preferably, the intelligent fire prevention and extinguishing early warning system for coal mines includes a coal spontaneous combustion hazard assessment module, a coal spontaneous combustion early warning system module, and a coal spontaneous combustion emergency response module;

[0016] The coal spontaneous combustion hazard assessment module analyzes and identifies the coal spontaneous combustion hazard under the current environment by collecting underground environmental parameters.

[0017] The coal spontaneous combustion early warning system module establishes early warning indicators of gas characteristic environment through coal programmed heating experiments and obtains the analysis results of the current underground spontaneous combustion state by collecting and analyzing the gas and temperature characteristics of the underground environment.

[0018] The emergency response module for spontaneous combustion of coal includes nitrogen injection for fire extinguishing, grouting for fire extinguishing, and rapid fire extinguishing in confined spaces.

[0019] Preferably, the gas characteristics include the type of gas, the concentration of different types of gas, and the rate of increase of their concentrations.

[0020] Preferably, the coal spontaneous combustion early warning system module includes an underground ring network, a laser gas analyzer, a distributed fiber optic thermometer, and a communication base station connected to the underground ring network via optical fiber, a surface monitoring station connected to the communication base station via a photoelectric converter, and a database connected to the surface monitoring station.

[0021] The ground monitoring station receives temperature parameters and gas characteristic parameters measured by the underground laser gas analyzer and the distributed fiber optic thermometer, respectively, and transmits the parameters to the final early warning model in the database to analyze and judge the underground environmental conditions, and obtain the rate of increase of CO oxidation in the mine coal and the minimum warning threshold.

[0022] Preferably, the coal spontaneous combustion early warning system module further includes a coal programmed heating experimental system, which includes a sample container containing a coal sample that can be heated, a temperature probe and a gas chromatograph that can measure the ambient temperature and gas characteristics in the sample container;

[0023] The coal programmed heating experimental system constructs a simulated environment for the sample tank based on a large number of mine fire environments under different conditions. The measured parameters such as gas rise rate, gas type data, and temperature value are input into the training model in the database to learn and train the final early warning model and establish early warning indicators.

[0024] The beneficial effects of this invention are as follows:

[0025] 1. This invention focuses on the target of fire prevention and extinguishing, integrating monitoring probes and various monitoring data. It sets two types of early warning indicators: single-item and composite indicators, to provide tiered early warnings of mine fire risks. During the process of coal spontaneously combusting from self-heating, it releases various characteristic gases. The release patterns of these gases show a certain regularity with coal temperature. Because their concentration decreases with airflow as they propagate, the minimum threshold for fire early warning may differ for probes at different locations. The system designs and develops a coal spontaneous combustion discrimination model. Based on actual mine monitoring data, it can autonomously learn to determine the rate of increase in CO oxidation in mine coal and the minimum warning threshold, constructing a coal spontaneous combustion early warning model for the specific mine. This method can improve the limitation of early warning propagation and enable long-distance monitoring and control of fires, thereby ensuring improved safety in coal mining. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the system architecture of the present invention;

[0027] Figure 2 A schematic diagram of the architecture of a coal spontaneous combustion early warning system;

[0028] Figure 3 This is a data analysis diagram of the coal spontaneous combustion simulation experiment of the present invention;

[0029] Figure 4 This is a schematic diagram of the coal natural early warning practice system architecture of the present invention;

[0030] Figure 5 This is a comparison chart of the predicted and measured results of the coal spontaneous combustion discrimination model of this invention;

[0031] Figure 6 This is a flowchart of the model training process of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0033] like Figures 1 to 6 As shown in the figure, this invention provides a method for intelligent fire prevention and extinguishing early warning in coal mines. The specific operation steps for intelligent fire prevention and extinguishing early warning in coal mines are as follows:

[0034] S1: Identify the targets for fire prevention and control.

[0035] Identifying fire prevention targets includes: coal spontaneous combustion hazard zones, fire zones, and external fire risk points.

[0036] The risk zone for spontaneous combustion of coal requires the determination of the spontaneous combustion characteristics of the target coal seam. This mainly includes basic data such as indicator gas data determined by programmed temperature rise measurement of coal samples, coal seam characteristics, mining methods of the working face and corresponding goaf characteristics, and regionally related air leakage characteristics.

[0037] The fire zone targets refer to the management of existing fire zones in the mine, including the time of fire zone closure, basic sealing parameters, basic characteristics of fire zone combustion, main measures for fire zone control, main measures for fire zone management, and responsible persons. External fire prevention targets mainly include: belt conveyors, electromechanical chambers, combustible material storage chambers, charging chambers, and underground explosives depots. Each type of external fire prevention target also includes location, main fire risks, fire protection facilities and materials, and the types and number of alarm detectors.

[0038] S2: To determine and assess the fire risk of objects and prevent fire hazards;

[0039] S3: Set corresponding early warnings based on the risk characteristics of objects at risk of fire;

[0040] S4: Set the indicators and levels for early warning.

[0041] Setting early warning indicators and levels includes: setting early warning indicators and setting early warning levels.

[0042] The warning levels are categorized as normal, symptomatic, developing, and disaster.

[0043] S5: Implement mine fire prevention measures according to the classification level.

[0044] As shown in the figure, in one embodiment, the intelligent fire prevention and extinguishing early warning system for coal mines includes a coal spontaneous combustion hazard assessment module, a coal spontaneous combustion early warning system module, and a coal spontaneous combustion emergency response module.

[0045] The coal spontaneous combustion hazard assessment module analyzes and identifies the coal spontaneous combustion hazard under the current environment by collecting underground environmental parameters.

[0046] The coal spontaneous combustion early warning system module establishes early warning indicators of gas characteristic environment through coal programmed heating experiments and obtains the analysis results of the current underground spontaneous combustion state by collecting and analyzing the gas and temperature characteristics of the underground environment.

[0047] The emergency response module for spontaneous combustion of coal includes nitrogen injection for fire extinguishing, grouting for fire extinguishing, and rapid fire extinguishing in confined spaces.

[0048] The working principle and beneficial effects of the above technical solution are as follows: This design adopts the three-zone division of the goaf, coal spontaneous combustion stage analysis, and goaf gas explosiveness analysis technology, realizing functions such as coal spontaneous combustion prediction and gas explosiveness prediction in the goaf. It enhances the ability to prevent coal spontaneous combustion hazards and predict goaf gas explosions, improves fire and explosion prevention in the goaf and the safety production level of fully mechanized mining faces, strengthens the safety management level for preventing coal spontaneous combustion hazards and gas explosion dangers, reduces the number of personnel in fixed monitoring positions, and lowers the cost investment of coal mines in fire prevention and extinguishing. The system can measure the temperature at various locations such as the goaf, roadways, sealed areas, conveyor belts, and supports, and can accurately predict and forecast the safe operation of monitoring equipment and various internal and external fire stages. The system provides visualized comprehensive monitoring, prevention, and intelligent monitoring, early warning, and forecasting of coal mine fires. It analyzes spontaneous combustion conditions, causes, and locations in a timely and accurate manner, achieving automated and unmanned management, saving human resources and operating costs. Simultaneously, the system provides intuitive, effective, and accurate data support for the safe operation of coal mines, enabling dynamic online monitoring of coal mine fires and ensuring comprehensive overall observation of the mine. With advanced technology, stable operation, and real-time monitoring, the system will provide a powerful tool for underground coal mine fire monitoring and will play a vital role in the modernization and safety assurance of coal mines. The system promotes the development of coal mine informatization, guiding coal mines towards information expansion, high integration, comprehensive application, automatic control, forecasting, and intelligent decision-making.

[0049] As shown in the figure, in one embodiment, the gas characteristics include the type of gas, the concentration of different types of gas, and the rate of increase of their concentrations.

[0050] The working principle and beneficial effects of the above technical solution are as follows: This design utilizes the complex physical and chemical changes involved in coal spontaneous combustion, which is a variable, self-accelerating, and exothermic process. Different types and amounts of gases, such as CO, CO2, CH4, C2H4, C2H6, C3H8, and C2H2, will appear at different temperatures during spontaneous combustion. Identifying the spontaneous combustion state based on the temperature rise and gas release characteristics during the process is fundamental to mine fire prevention and control, and is crucial for the prevention and control of internal mine fires. Internal coal mine fires often occur in goaf areas, releasing large amounts of heat during the fire. Currently, the prediction method for endogenous coal mine fires mainly relies on a comprehensive forecasting approach combining local temperature monitoring and gas index analysis. This method determines the fire's occurrence based on the regular changes in temperature and the release of gases such as CO, CO2, alkanes, alkenes, and alkynes during the coal oxidation and heating process. Experimental measurements show that during the spontaneous oxidation of coal, carbon monoxide gas appears above 50℃ and persists throughout the entire process; ethylene gas appears at around 110℃, marking the accelerated oxidation stage of spontaneous combustion; and the presence of alkynes indicates that the coal has entered the combustion stage. Therefore, by monitoring temperature and selecting indicator gases, the stage and combustion state of spontaneous combustion in coal seams can be effectively determined. Furthermore, the temperature rise of the coal body and surrounding medium directly reflects the degree of spontaneous combustion. Temperature is the most direct and effective indicator for judging the degree and extent of spontaneous combustion. By determining the temperature field and its distribution at a specific coal seam, the degree and extent of spontaneous combustion in a given coal seam can be analyzed. Thermometry is the most direct and reliable method for detecting spontaneous combustion in coal and locating high-temperature points and ignition sources. However, due to the poor thermal conductivity of coal, the rate at which it dissipates heat through conduction is very slow. Often, by the time an abnormal temperature is detected at the exposed surface of the coal, an internal fire has already formed. Furthermore, the area for measuring temperature is limited. Therefore, applying thermometry to determine the degree of spontaneous combustion in coal has certain limitations.

[0051] The above analysis shows that a single method for detecting coal spontaneous combustion cannot reflect the situation in a timely and accurate manner. Relying solely on one monitoring method is insufficient to meet the needs of coal spontaneous combustion monitoring. Given the complementary advantages of gas analysis and thermometry in determining the degree of coal spontaneous combustion and high-temperature zones, the two methods can be applied in tandem. This can be achieved by optimizing the monitoring process, the location of measuring points, and monitoring indicators to address the current challenge of comprehensively, quickly, and accurately obtaining information on the characteristics of coal spontaneous combustion in goaf areas. Using a coal spontaneous combustion programmed temperature rise experimental platform, gas is sampled at each temperature increase. A gas chromatograph, capable of single-channel injection, is used for gas detection. After the gas is injected into the chromatograph, it undergoes adsorption, desorption, and dissolution processes on the chromatographic column, resulting in component separation. The separated components sequentially enter the detector system, where they are converted into electrical signals and sent to a recorder or integrator to plot the chromatogram and obtain the concentration parameters of the relevant components.

[0052] The gas composition produced at different stages of coal spontaneous combustion is different, and each stage corresponds to a maximum concentration of a certain gas component, which is a marker gas.

[0053] By identifying the characteristic gases at different stages, the stage of spontaneous combustion of coal can be determined, thereby establishing the fire warning level.

[0054] With other variables remaining constant, airflow is used as the variable. The effects of different airflow rates on the concentration and generation rate of gases released during the spontaneous combustion of coal are analyzed, and the gas generation patterns under different conditions are compared and obtained.

[0055] As shown in the figure, in one embodiment, the coal spontaneous combustion early warning system module includes an underground ring network, a laser gas analyzer, a distributed fiber optic thermometer, and a communication base station connected to the underground ring network via optical fiber, a surface monitoring station connected to the communication base station via a photoelectric converter, and a database connected to the surface monitoring station.

[0056] The ground monitoring station receives temperature parameters and gas characteristic parameters measured by the underground laser gas analyzer and the distributed fiber optic thermometer, respectively, and transmits the parameters to the final early warning model in the database to analyze and judge the underground environmental conditions, and obtain the rate of increase of CO oxidation in the mine coal and the minimum warning threshold.

[0057] The working principle and beneficial effects of the above technical solution are as follows: The downhole laser continuous monitoring system is an upgraded product of the infrared continuous monitoring system. In addition to its advantages such as fast response speed, higher measurement accuracy, and good stability and reliability, the laser continuous monitoring system can also monitor ethylene and acetylene, two important spontaneous combustion indicator gases, in real time. Therefore, by using a downhole bundled tube system based on laser analysis, it is possible to more effectively assist in the establishment of a mine spontaneous combustion sensing system.

[0058] Distributed fiber optic temperature sensors are a novel online temperature monitoring and alarm system. They are explosion-proof, flame-retardant, corrosion-resistant, and resistant to electromagnetic interference, ensuring safe operation in hazardous environments. Any point on the fiber optic cable serves as both a sensitive element and a transmission channel for other sensitive elements. By applying this technology for temperature detection, information on spatial and temporal temperature changes along the fiber's distribution range can be obtained, enabling temperature monitoring and effective location. Distributed fiber optic temperature detection technology is a feasible solution for monitoring spontaneous combustion in goaf areas.

[0059] This design enables intelligent monitoring and analysis of fire parameters, and provides intelligent prediction and early warning based on the analysis results. It achieves comprehensive early warning of coal mine fire status and trends. By collecting and processing fire monitoring data from goaf areas, it analyzes and subdivides the occurrence of monitored fire hazards, quickly locates the spatial position of fire hazards in goaf areas, and establishes a coal mine fire early warning operation control adjustment and analysis system.

[0060] As shown in the figure, in one embodiment, the coal spontaneous combustion early warning system module also includes a coal programmed heating experimental system, which includes a sample container containing a coal sample that can be heated, a temperature probe that can measure the ambient temperature and gas characteristics in the sample container, and a gas chromatograph.

[0061] The coal programmed heating experimental system constructs a simulated environment for the sample tank based on a large number of mine fire environments under different conditions. The measured parameters such as gas rise rate, gas type data and temperature value are input into the training model in the database to learn and train to obtain the final early warning model and establish early warning indicators.

[0062] The working principle and beneficial effects of the above technical solution are as follows: Taking the fire prevention and extinguishing target as the main body, it integrates monitoring probes and various monitoring data for the target, sets two types of early warning indicators: single indicators and composite indicators, and provides graded early warning of mine fire risk. During the process of coal from self-heating to spontaneous combustion, it releases a variety of characteristic gases. The release pattern of these gases shows a certain regularity with the coal temperature. As they move with the airflow during propagation, their concentration decreases with the dilution effect of the airflow. Therefore, the minimum threshold for fire early warning may be different for probes at different locations. Using a coal spontaneous combustion discrimination model, and based on the actual monitoring data of the mine, through self-learning, it determines the coal oxidation CO rise rate and the minimum warning threshold, and constructs a coal spontaneous combustion early warning model for this mine.

[0063] A coal mine fire detection system uses sensors and monitoring data to detect fire risks in different fire prevention and extinguishing targets and facilities. For a single fire prevention and extinguishing target, multiple monitoring sensors are often associated with it. During the process of coal undergoing self-heating and spontaneous combustion, it releases various characteristic gases. The release patterns of these gases show a certain regularity in relation to coal temperature. Because these gases move with the airflow, their concentration decreases as they propagate. Therefore, the minimum threshold for fire warning may differ for sensors located at different locations.

[0064] Because the oxidation characteristics of coal vary across different coal mines, there is no universally applicable CO warning threshold. This system designs a self-learning algorithm to determine the CO rise rate and minimum warning threshold for coals with different oxidation characteristics and for different mine gas generation patterns. Furthermore, multiple detector warnings often necessitate raising the warning level, and the presence of coal spontaneous combustion indicator gases signifies accelerated coal spontaneous combustion in the goaf or the formation of high-temperature ignition points. Available machine learning models include decision trees, random forests, support vector machines, and artificial neural networks.

[0065] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0066] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent fire prevention and extinguishing early warning in coal mines, characterized in that... The specific operational steps for intelligent fire prevention and early warning in coal mines are as follows: S1: Identify the targets for fire prevention and control. The identified fire prevention targets include: coal spontaneous combustion hazard zones, fire zones, and external fire risk points. The coal spontaneous combustion risk zone needs to establish the spontaneous combustion characteristics of the target coal seam, mainly including index gas data determined by programmed temperature rise measurement of coal samples, coal seam characteristics, mining method of the working face and corresponding goaf characteristics, and basic data on regional air leakage characteristics. The fire zone targets refer to the management of existing fire zones in the mine, including the time of fire zone closure, basic sealing parameters, basic characteristics of fire zone combustion, main measures for fire zone control, main measures for fire zone management, and responsible persons. External fire prevention targets mainly include: belt conveyors, electromechanical chambers, combustible material storage chambers, charging chambers, and underground explosives depots. Each of the external fire prevention targets also includes location, main fire risks, fire protection facilities and materials, and types and numbers of alarm detectors. S2: Determine, assess, and prevent fire risks of targets; specifically including: establishing an early warning model through a coal temperature-programmed heating experimental system, wherein the coal temperature-programmed heating experimental system includes a sample container containing coal samples that can be heated, a temperature probe capable of measuring the ambient temperature and gas characteristics in the sample container, and a gas chromatograph; the coal temperature-programmed heating experimental system constructs a simulated environment for the sample container based on a large number of mine fire environments under different conditions, and the measured parameters such as gas rise rate, gas type data, and temperature values ​​are input into a training model in the database for learning and training to obtain the final early warning model and establish early warning indicators; S3: Set corresponding early warnings based on the risk characteristics of fire-prone objects; specifically including: collecting actual monitoring data through an underground ring network, which includes a laser gas analyzer, a distributed fiber optic thermometer, and a communication base station connected by communication optical fibers. The laser gas analyzer and the distributed fiber optic thermometer measure temperature parameters and gas characteristic parameters, respectively. The ground monitoring station receives the temperature parameters and gas characteristic parameters monitored underground and transmits the parameters to the final early warning model in the database to analyze and judge the underground environmental status. Based on the actual monitoring data of the mine, the mine determines the coal oxidation CO rise rate and the minimum warning threshold through autonomous learning, and constructs a coal spontaneous combustion early warning model for this mine. S4: Set the indicators and levels for early warning. The set indicators and levels for early warning include: setting early warning indicators and setting early warning levels. The defined early warning levels include normal, symptom, development, and disaster. S5: Implement mine fire prevention measures according to the classification level.

2. A coal mine intelligent fire prevention and extinguishing early warning system, characterized in that: The intelligent fire prevention and extinguishing early warning system for coal mines includes a coal spontaneous combustion hazard assessment module, a coal spontaneous combustion early warning system module, and a coal spontaneous combustion emergency response module. The coal spontaneous combustion hazard assessment module analyzes and identifies the coal spontaneous combustion hazard under the current environment by collecting underground environmental parameters. The coal spontaneous combustion early warning system module establishes early warning indicators for gas characteristic environments through coal programmed heating experiments and obtains analysis results of the current underground spontaneous combustion state through the collection and analysis of gas and temperature characteristics of the underground environment; the coal spontaneous combustion early warning system module includes: The coal temperature-programmed experimental system includes a sample container holding a coal sample that can be heated, a temperature probe capable of measuring the ambient temperature and gas characteristics within the sample container, and a gas chromatograph. The system constructs a simulated environment for the sample container based on numerous mine fire scenarios under varying conditions. The measured gas rise rate, gas type data, and temperature parameters are input into a training model in a database to learn and train a final early warning model, establishing early warning indicators. An underground ring network is connected via optical fiber to a laser gas analyzer, a distributed optical fiber thermometer, and a communication base station. A ground monitoring station, connected to the communication base station via a photoelectric converter, receives temperature and gas characteristic parameters measured by the underground laser gas analyzer and the distributed optical fiber thermometer, transmitting these parameters to the final early warning model in the database for analysis and judgment of the underground environmental state. Based on actual mine monitoring data, the system autonomously learns to determine the coal oxidation CO rise rate and the minimum warning threshold. The emergency response module for spontaneous combustion of coal includes: nitrogen injection fire extinguishing, grouting fire extinguishing, and rapid confined space fire extinguishing.

3. The intelligent fire prevention and extinguishing early warning system for coal mines according to claim 2, characterized in that: Gas characteristics include the type of gas, the concentration of different types of gases, and the rate of increase in concentration.

4. The intelligent fire prevention and extinguishing early warning system for coal mines according to claim 2, characterized in that: The coal spontaneous combustion early warning system module includes an underground ring network, a laser gas analyzer, a distributed fiber optic thermometer, and a communication base station connected to the underground ring network via optical fiber, a surface monitoring station connected to the communication base station via a photoelectric converter, and a database connected to the surface monitoring station. The ground monitoring station receives temperature parameters and gas characteristic parameters measured by the underground laser gas analyzer and the distributed fiber optic thermometer, respectively, and transmits the parameters to the final early warning model in the database to analyze and judge the underground environmental conditions, and obtain the rate of increase of CO oxidation in the mine coal and the minimum warning threshold.

5. The intelligent fire prevention and extinguishing early warning system for coal mines according to claim 4, characterized in that: The coal spontaneous combustion early warning system module also includes a coal programmed heating experimental system, which includes a sample container containing a coal sample that can be heated, a temperature probe that can measure the ambient temperature and gas characteristics in the sample container, and a gas chromatography analyzer. The coal programmed heating experimental system constructs a simulated environment for the sample tank based on a large number of mine fire environments under different conditions. The measured gas rise rate, gas type data and temperature parameters are input into the training model in the database to learn and train the final early warning model and establish early warning indicators.

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