Coal mine safety situation risk quantification method based on three-dimensional convolution superposition

Abstract

The invention relates to a coal mine safety situation risk quantification method based on three-dimensional convolution superposition, and belongs to the technical field of coal mine safety monitoring. Aiming at the problems that multi-disaster coupling risk modeling is insufficient, disaster dynamic diffusion characteristics are not quantified and personnel safety priorities are lacked in the prior art, the following scheme is provided: firstly, constructing a disaster distribution function to quantify underground disaster space intensity; secondly, generating a personnel density function through Zigbee radio frequency positioning; and finally, superposing disaster diffusion influence and personnel distribution by adopting three-dimensional convolution, and establishing a safety situation risk function. The method has the advantages that multi-disaster coupling risk dynamic modeling is achieved, the high risk of a crowded area is accurately recognized, the disaster space diffusion process is quantified, early warning information and disaster avoiding routes are pushed in real time through the three-dimensional visualization platform, and the active risk avoiding capacity of a mine is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal mine safety monitoring and relates to a coal mine safety situation risk quantification method based on three-dimensional convolution superposition. Background Art

[0002] As coal mining depths increase annually, the environmental complexity of deep coal seams has significantly increased. Traditional coal mine hazards such as flooding, fires, gas hazards, roof failures, and dust disasters are becoming increasingly severe. Simultaneously, the risk of coal-rock dynamic hazards has surged, and the spatiotemporal coupling effects between these hazards are becoming increasingly prominent. Currently, underground coal mines generally adopt a decentralized disaster prevention and control management model, with the communications and prevention department, geodesy department, and production department each responsible for different disaster prevention and control tasks. This results in independent and fragmented management of the disaster prevention and control system, making it difficult to adapt to the development needs of high-yield and high-efficiency mines.

[0003] The existing comprehensive early warning system for coal mine disasters has obvious technical shortcomings: First, the mainstream early warning system mainly conducts in-depth research on the occurrence mechanism and early warning technology of a single disaster, and the comprehensive risk assessment under the coupling of multiple disasters is only achieved through the weight distribution combination of sub-disaster warning results, and lacks the dynamic modeling capability of the coupling effect of multiple disasters; secondly, the existing disaster early warning model mostly relies on the threshold-level alarm of single-point monitoring data, and does not fully consider the dynamic diffusion characteristics of disasters such as gas outburst diffusion and impact ground pressure wave range. The model is only limited to the judgment of whether a disaster has occurred, and does not quantify the impact of the disaster diffusion process on the spatial distribution of risks; more importantly, the current various early warning models have not included the density of underground personnel in the risk assessment system, and ensuring personnel safety and avoiding mass deaths and injuries are the primary tasks of coal mine disaster prevention and control. The existing technology cannot achieve dynamic risk priority assessment with personnel safety as the core.

[0004] Therefore, there is an urgent need for a safety situation risk quantification method that can integrate the diffusion characteristics of multiple disaster types and the distribution characteristics of personnel, break through the limitations of disaster dispersion warning, and provide accurate decision-making support for underground personnel to avoid risks. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a coal mine safety situation risk quantification method based on three-dimensional convolution superposition. By quantifying the coupling relationship between disaster intensity, diffusion range and population density, it can realize dynamic and accurate assessment of underground safety situation, solve the dynamic risk modeling problem under the coupling of multiple disasters, and highlight the risk priority of densely populated areas.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A coal mine safety situation risk quantification method based on three-dimensional convolution superposition includes the following steps:

[0008] S1: Spatial distribution of underground disasters

[0009] Based on the mine geological dynamic zoning and the dynamic evolution law of disasters, the distribution function D of the i-th disaster is constructed. i (x,y,z,f i ), where (x, y, z) is the spatial position coordinate f i is the disaster intensity; calculate the average disaster intensity:

[0010]

[0011] S2: Personnel focus area division

[0012] Based on Zigbee radio frequency positioning technology, the location of people is obtained in real time, and the population density distribution function P(x, y, z) is constructed;

[0013] S3: 3D Convolutional Modeling of Security Situation

[0014] The safety situation risk function is generated by superimposing the impact of multiple disasters and population density through three-dimensional convolution:

[0015]

[0016] Among them, ω i is the weight coefficient of the i-th disaster, satisfying ω i ≥0 and ∑ω i =1;K i (Δx, Δy, Δz) is the three-dimensional diffusion kernel function of the i-th disaster, (Δx, Δy, Δz) is the position offset; (x', y', z') is the coordinates of the disaster location.

[0017] Furthermore, in S1, the distribution function D i (x,y,z,f i ) includes:

[0018] Based on the geodynamic zoning method, the fault structure and ground stress field of the well field are analyzed, and combined with the numerical simulation of the disaster-prone environment, the intensity probability density of the disaster in the spatial location is determined.

[0019] Furthermore, in S2, the construction of the population density distribution function P(x, y, z) includes:

[0020] Personnel location data is collected through Zigbee radio frequency positioning technology, and the distance between people is estimated based on the received signal strength attenuation model (Received Signal Strength Indication, RSSI), signal round-trip time (Time of Flight, TOF) or angle of arrival (Angle of Arrival, AOA), and a density scalar function is generated through node number statistics and signal density analysis.

[0021] Furthermore, in S3, the three-dimensional diffusion kernel function K i (Δx, Δy, Δz) is a three-dimensional Gaussian kernel function:

[0022]

[0023] Among them, σ x,i , σ y,i , σ z,i is the diffusion coefficient of the i-th disaster in the x, y, and z directions.

[0024] Furthermore, the diffusion coefficient is configured differently according to the disaster type:

[0025] Gas disaster: σ x,i =σ y,i >σ z,i ;

[0026] Fire or fire disaster: x,i =σ y,i <σ z,i

[0027] The diffusion coefficient value is determined through historical accident data or numerical simulation.

[0028] Furthermore, the weight coefficient ω i It is set based on the severity of disaster consequences, including casualty rate or economic loss indicators, and quantified through analysis of historical accident data.

[0029] Furthermore, it also includes S4: Risk visualization and early warning:

[0030] Real-time calculation of H total (x, y, z) and generate a three-dimensional risk distribution cloud map. When the risk value exceeds the threshold, the three-dimensional Geographic Information System (GIS) platform will trigger the sound and light alarm, and push warning information and disaster avoidance routes to mobile terminal applications (Application, APP), emergency broadcasts and individual equipment.

[0031] A coal mine safety situation risk quantification system based on three-dimensional convolution superposition, used to implement the method, includes:

[0032] Disaster location module, used to construct disaster distribution functions based on geodynamic zoning and numerical simulation;

[0033] The personnel monitoring module is used to collect personnel location data in real time through the Zigbee radio frequency positioning network and generate a personnel density function;

[0034] a convolution processing module, connected to the disaster location module and the personnel monitoring module respectively, for receiving the disaster distribution function and the personnel density function, configuring diffusion kernel function parameters and disaster weights, and performing a three-dimensional convolution operation to generate a safety situation risk function;

[0035] The early warning execution module is connected to the convolution processing module and is used to trigger multi-terminal early warnings for high-risk areas and push disaster avoidance routes based on the security situation risk function.

[0036] Furthermore, the convolution processing module includes:

[0037] Scattered core configuration unit, used to store the diffusion coefficients of different disaster types;

[0038] A weight allocation unit, used to dynamically adjust disaster weights based on a historical accident database;

[0039] A convolution operation unit is respectively connected to the diffusion kernel configuration unit, the weight distribution unit, the disaster location module and the personnel monitoring module, and is used to perform a convolution operation based on the diffusion coefficient, the disaster weight, the disaster distribution function and the personnel density function, and output a safety situation risk function in real time.

[0040] Furthermore, the early warning execution module is connected to the three-dimensional GIS platform, mobile terminal application APP, underground emergency guidance screen and individual intelligent equipment to realize multi-channel synchronous push of early warning information.

[0041] The beneficial effects of the present invention are:

[0042] (1) Breaking through the limitations of traditional single disaster warning, integrating the diffusion characteristics of multiple disasters such as water disasters, fire, gas disasters, roof disasters and dust disasters, quantifying the dynamic propagation process of disasters through three-dimensional Gaussian kernel functions, solving the problem of comprehensive risk modeling under the spatiotemporal coupling of multiple disasters, and significantly improving the comprehensiveness and accuracy of risk assessment.

[0043] (2) For the first time, the population density is included as a core variable in the risk function. Based on Zigbee radio frequency positioning technology, the distribution of people is tracked in real time. Through convolution superposition, the impact of disaster spread is dynamically associated with densely populated areas, achieving accurate identification of high-risk areas and redistribution of risk levels, ensuring that risk avoidance resources are tilted towards densely populated areas.

[0044] (3) In view of the dynamic diffusion characteristics of disasters such as gas outburst and rock burst, a differentiated three-dimensional diffusion kernel function is constructed. The diffusion coefficient is optimized by combining historical accident data with numerical simulation, breaking through the static limitations of traditional single-point threshold alarms, and realizing spatial continuous quantification of the disaster impact range, providing a scientific basis for predicting the spread trend of disasters.

[0045] (4) Generate a three-dimensional risk distribution cloud map for the underground mine and update it dynamically. Through the three-dimensional geographic information system platform, mobile terminal applications and underground emergency guidance equipment, multi-channel simultaneous push of high-risk area warning information and the optimal disaster avoidance route, significantly shortening the emergency response time and improving the proactive risk avoidance capabilities of underground personnel.

[0046] (5) Promote the transformation from decentralized disaster prevention and control to integrated early warning of multiple disaster types, provide a unified risk quantification framework for the coal mine safety management system, assist managers in formulating precise disaster prevention strategies, reduce the risk of mass casualties from the source, and support the sustainable development of high-yield and high-efficiency mines.

[0047] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0049] Figure 1 A working principle diagram of a specific embodiment of the present invention;

[0050] Figure 2 A diagram showing a specific implementation technology and equipment structure of the present invention;

[0051] Figure 3 A structural diagram of a partial technology and equipment sub-method of the present invention;

[0052] Figure 4 This is a structural diagram of the numerical simulation of the disaster diffusion process in the present invention. DETAILED DESCRIPTION

[0053] The following describes the embodiments of the present invention by means of specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0054] Among them, the accompanying drawings are only for illustrative purposes and represent only schematic diagrams rather than actual pictures, and should not be understood as limiting the present invention. In order to better illustrate the embodiments of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the dimensions of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions may be omitted in the accompanying drawings.

[0055] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "back", etc. indicating directions or positional relationships, they are based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operate in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0056] Figure 1 This is a working principle diagram of a specific implementation method of the coal mine safety situation risk quantification method of the present invention. Through breakthroughs in three core technologies, namely, positioning of the spatial distribution area of ​​underground disasters, division of key personnel attention areas, and three-dimensional convolution modeling of safety situation, the three-dimensional spatial convolution superposition of disaster spread and personnel distribution is achieved, and a coal mine safety situation risk quantification method based on multi-disaster convolution superposition is established. The positioning of the spatial distribution area of ​​underground disasters requires quantitative analysis of the mine field geodynamic disaster risk based on the geodynamic zoning method, "theoretical analysis + numerical simulation" deduction of the whole process of disaster pregnancy, disaster change, and spread, as well as unified collection, integrated display and fusion analysis of disaster information. The division of key personnel attention areas needs to solve the problem of identifying densely populated areas and density based on Zigbee radio frequency technology, and identifying "low-scoring" personnel with unsafe behaviors based on the coal mine safety production risk classification management and accident hazard investigation and control system. The three-dimensional convolution modeling of safety situation requires three-dimensional Gaussian diffusion function modeling of disasters, personnel density function modeling, and three-dimensional convolution modeling of regional safety situation.

[0057] Figure 2 This is a diagram of the specific implementation technology and equipment structure of the coal mine safety situation risk quantification method of the present invention. First, the theory of continental drift, the division of far-field continental plates, the division of China's coalfield geological structure, and the division of wellfield geological structure are used to achieve wellfield fault structure modeling. Second, the geodynamic hazard risk of the mine is quantified through the measurement of wellfield in-situ stress and the modeling of mine stress field and wellfield fault structure. This further realizes the quantitative analysis of the geodynamic hazard risk of the wellfield based on the geodynamic zoning method. The "theoretical analysis + numerical simulation" approach to deducing the entire process of disaster initiation, catastrophe, and spread primarily involves two fundamental tasks: analysis of the mine disaster initiation environment, causal factors, and mechanisms; and simulation of the entire underground three-dimensional disaster process ("occurrence → spread → disaster"), along with asynchronous spatial and temporal deduction. This analysis is achieved by analyzing the inherent properties of disasters through coal seam endowment and production processes. Furthermore, through theoretical deduction using specialized knowledge in physics, mechanics, and statistics, numerical simulation of the disaster spread process, and interactive services for multi-hazard data, this process is simulated and asynchronously deduced in three dimensions ("occurrence → spread → disaster") underground. The unified collection, integrated display, and integrated analysis of disaster information require the construction of a central database and disaster warning models. These models primarily include a series of sub-disaster warning models, including gas over-limit warning models, coal and gas outburst warning models, gas explosion warning models, internal fire warning models, external fire warning models, mine pressure disaster warning models, dust explosion warning models, water hazard warning models, and multi-hazard integrated warning models. The method for identifying densely populated areas and their density based on Zigbee radio frequency technology can be broken down into three major technical components: Zigbee communication technology, precise personnel positioning technology, and personnel density analysis. The implementation of precise personnel positioning technology mainly involves estimating distance through the received signal strength attenuation model using RSSI, estimating distance through the round-trip time of TOF signals, and analyzing signal direction through the AOA (angle of arrival) antenna array. The implementation of personnel density analysis mainly involves node count and signal density analysis. Based on the coal mine safety production risk classification management and accident hazard investigation and control system, personnel with "low scores" for unsafe behavior can be identified. This technology requires the use of smart contract technology to automatically trigger the hazard rectification process, blockchain technology to record risk investigations and store rectification results, and a dynamic evaluation mechanism to dynamically update the shared database and interconnect individual equipment such as smart bracelets.

[0058] Figure 3 This is a structural diagram of a partial technology and equipment sub-method of the coal mine safety situation risk quantification method of the present invention. Figure 4This is a diagram of the numerical simulation structure of the disaster diffusion process in the present invention. The numerical simulation of the disaster diffusion process and diffusion range is composed of a series of coal mine disaster numerical simulation methods, mainly including the analysis of gas flow field changes through FLUENT simulation, the analysis of stope stress distribution and roof stability through FELAC, the analysis of water gushing process and channel through HGS simulation, the analysis of coal body gas penetration process through COMET2.11 simulation, the analysis of dust explosion and gas diffusion through PyroSim simulation, the analysis of fire smoke, temperature, toxic gas diffusion and fire spread process through PyroSim simulation, the prediction of the evolution of the plastic zone of the surrounding rock of the rock burst stope and the energy accumulation-release process through FLAC3D simulation, and the analysis of the damage of the shock wave to the tunnel support structure through COMSOL Multiphysics simulation. Multi-disaster data interaction services mainly include multiple big data service methods such as extraction and fusion of multiple data sources, fusion of multiple types of ETL methods, real-time streaming computing, fusion of multi-source data services, and artificial intelligence algorithms. The multiple data sources mainly include equipment definition information, equipment monitoring real-time information, equipment monitoring historical information, equipment monitoring alarm information, equipment monitoring statistical information, gas warning information, water hazard warning information, fire warning information, roof warning information, integrated warning information, disaster warning text messages, and other types of disaster-related monitoring equipment and monitoring information.

[0059] Through the coal mine safety situation risk quantification method based on three-dimensional convolution superposition of the present invention, the dynamic coupling effect of convolution superposition quantification of multiple disasters and personnel distribution is studied, and the disaster intensity, diffusion range and personnel location are updated in real time when a complex disaster occurs, thereby improving the timeliness and effectiveness of early warning, and ultimately realizing key monitoring and early warning of safety situation risks in densely populated areas, thereby minimizing the risk of casualties in accidents.

[0060] Example 1

[0061] Step 1: Data collection and preprocessing

[0062] Obtain disaster monitoring data such as location, temperature, gas, hydrology, and microseismic data through the sensor network to construct the disaster distribution function D i (x,y,z,f i )

[0063] Use Zigbee radio frequency tags to locate personnel positions and calculate the personnel density function P(x,y,z).

[0064] Step 2: Parameter configuration

[0065] Set disaster weights based on historical accident data, disaster appraisal reports, etc. i (For example, gas disaster ω1=0.2, water disaster ω2=0.4, etc.)

[0066] Set the diffusion kernel function parameter σ (e.g. gas outburst diffusion σ = 20m, rock burst σ = 100m, water disaster σ = 15m, etc.)

[0067] Step 3: Risk Calculation and Visualization

[0068] Real-time calculation of H total (x,y,z), generate a three-dimensional risk distribution cloud map underground.

[0069] High-risk areas (H total > threshold) triggers the sound and light alarm of the 3D GIS visualization platform, and simultaneously pushes warning information and disaster avoidance routes to mobile terminal APP, regional emergency broadcast, individual equipment, emergency guidance screens, etc.

[0070] Example 2

[0071] 1. Data Collection and Disaster Modeling

[0072] A gas concentration sensor network is arranged at the mining face to monitor the position coordinates and concentration values ​​in real time, and a gas disaster distribution function D is constructed. 瓦斯 (x,y,z,f 瓦斯 The gas enrichment area is determined by geodynamic zoning analysis, and the gas diffusion law is simulated by FLUENT numerical simulation to calculate the average disaster intensity E[f 瓦斯 ].

[0073] 2. Personnel positioning and density calculation

[0074] Underground personnel wear Zigbee radio frequency tags, and the positioning base station uses TOF technology to track their location in real time.

[0075] The number of people is counted in a spatial unit of 10m×10m×5m, and the population density function P(x,y,z) is generated.

[0076] 3. 3D Convolution Risk Calculation

[0077] Configuration parameters: Gas weight ω 瓦斯 =0.25, diffusion coefficient σ x =σ y =25m (strong horizontal diffusion), σ z =10m (vertical diffusion is weak).

[0078] Perform convolution operation: H 瓦斯 (x,y,z)=P(x,y,z)·∫∫∫E[f 瓦斯 ]·K 瓦斯 (Δx,Δy,Δz)dx

[0079] When the return air channel has a dense population area P>30 people / unit and H 瓦斯When >0.8, it is judged as high risk.

[0080] 4. Dynamic early warning and risk avoidance

[0081] The 3D GIS platform generates a red risk cloud map and simultaneously pushes warnings to the smart wristbands of people in the affected areas.

[0082] The emergency guidance screen displays the evacuation route: evacuate along the air intake tunnel to the main wellhead.

[0083] Example 3

[0084] 1. Global disaster modeling

[0085] Integrate water disaster (HGS simulation), roof disaster (FLAC3D stress analysis), gas disaster data to build D i (i=1,2,3).

[0086] Set weights through the historical accident database: ω 水害 =0.3,ω 顶板 =0.25,ω 瓦斯 =0.2.

[0087] 2. Dynamic personnel distribution update

[0088] Predict personnel flow trends based on mining plans and update the P(x,y,z) function every 5 minutes.

[0089] 3. Real-time convolution calculation

[0090] The convolution operation unit uses GPU parallel computing to update the H of 100,000 grid points in the entire mine every second. total value.

[0091] Highlight the intersection area between the coal mining face and the drainage tunnel (H total >1.0 in orange high-risk areas).

[0092] 4. Systematic disaster prevention decision-making

[0093] The early warning platform automatically generates prevention and control plans:

[0094] Start drainage system pressure boosting in high-risk flood areas;

[0095] Restrict personnel from entering the roof risk area and strengthen support;

[0096] Push customized disaster avoidance roadmaps to affected areas.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. A coal mine safety situation risk quantification method based on three-dimensional convolution superposition, characterized by: The following steps are involved: S1: Spatial distribution of underground disasters Based on the mine geological dynamic zoning and the dynamic evolution law of disasters, the distribution function D of the i-th disaster is constructed. i (x,y,z,f i ), where (x, y, z) is the spatial position coordinate f i is the disaster intensity; calculate the average disaster intensity: S2: Personnel focus area division Based on Zigbee radio frequency positioning technology, the location of people is obtained in real time, and the population density distribution function P(x, y, z) is constructed; S3: 3D Convolutional Modeling of Security Situation The safety situation risk function is generated by superimposing the impact of multiple disasters and population density through three-dimensional convolution: Among them, ω i is the weight coefficient of the i-th disaster, satisfying ω i ≥0 and ∑ω i =1;K i (Δx, Δy, Δz) is the three-dimensional diffusion kernel function of the i-th disaster, (Δx, Δy, Δz) is the position offset; (x', y', z') is the coordinates of the disaster location.

2. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 1 is characterized in that: In S1, the distribution function D i (x,y,z,f i ) includes: Based on the geodynamic zoning method, the fault structure and ground stress field of the well field are analyzed, and combined with the numerical simulation of the disaster-prone environment, the intensity probability density of the disaster in the spatial location is determined.

3. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 1 is characterized in that: In S2, the construction of the population density distribution function P(x, y, z) includes: Personnel location data is collected through Zigbee radio frequency positioning technology, and the distance between people is estimated based on the received signal strength attenuation model (Received Signal Strength Indication, RSSI), signal round-trip time (Time of Flight, TOF) or angle of arrival (Angle of Arrival, AOA), and a density scalar function is generated through node number statistics and signal density analysis.

4. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 1 is characterized in that: In S3, the three-dimensional diffusion kernel function K i (Δx, Δy, Δz) is a three-dimensional Gaussian kernel function: Among them, σ x,i , σ y,i , σ z,i is the diffusion coefficient of the i-th disaster in the x, y, and z directions.

5. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 4 is characterized in that: The diffusion coefficient is configured differently according to the disaster type: Gas disaster: σ x,i =σ y,i >σ z,i ; Fire or fire disaster: x,i =σ y,i <σ z,i The diffusion coefficient value is determined through historical accident data or numerical simulation.

6. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 1 is characterized in that: The weight coefficient ω i It is set based on the severity of disaster consequences, including casualty rate or economic loss indicators, and quantified through analysis of historical accident data.

7. The method for quantifying coal mine safety situation risk based on three-dimensional convolution and superposition according to claim 1 is characterized in that: Also includes S4: Risk Visualization and Early Warning: Real-time calculation of H total (x, y, z) and generate a three-dimensional risk distribution cloud map. When the risk value exceeds the threshold, the three-dimensional Geographic Information System (GIS) platform will trigger the sound and light alarm, and push warning information and disaster avoidance routes to mobile terminal applications (Application, APP), emergency broadcasts and individual equipment.

8. A coal mine safety situation risk quantification system based on three-dimensional convolution superposition, used to implement the method described in any one of claims 1 to 7, characterized in that: include: Disaster location module, used to construct disaster distribution functions based on geodynamic zoning and numerical simulation; The personnel monitoring module is used to collect personnel location data in real time through the Zigbee radio frequency positioning network and generate a personnel density function; a convolution processing module, connected to the disaster location module and the personnel monitoring module respectively, for receiving the disaster distribution function and the personnel density function, configuring diffusion kernel function parameters and disaster weights, and performing a three-dimensional convolution operation to generate a safety situation risk function; The early warning execution module is connected to the convolution processing module and is used to trigger multi-terminal early warnings for high-risk areas and push disaster avoidance routes based on the security situation risk function.

9. The coal mine safety situation risk quantification system based on three-dimensional convolution and superposition according to claim 8 is characterized by: The convolution processing module includes: Scattered core configuration unit, used to store the diffusion coefficients of different disaster types; A weight allocation unit, used to dynamically adjust disaster weights based on a historical accident database; A convolution operation unit is respectively connected to the diffusion kernel configuration unit, the weight distribution unit, the disaster location module and the personnel monitoring module, and is used to perform a convolution operation based on the diffusion coefficient, the disaster weight, the disaster distribution function and the personnel density function, and output a safety situation risk function in real time.

10. The coal mine safety situation risk quantification system based on three-dimensional convolution and superposition according to claim 8, characterized in that: The early warning execution module is connected to the three-dimensional GIS platform, mobile terminal application APP, underground emergency guidance screen and individual intelligent equipment to realize multi-channel synchronous push of early warning information.

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