Method and system for monitoring closed coal mine gas leakage and preventing and controlling disasters

Abstract

The invention discloses a closed coal mine gas leakage monitoring and disaster prevention and control method and system, and relates to the technical field of gas leakage monitoring. Comprising the following steps: acquiring multi-dimensional monitoring data in each gas monitoring unit of the closed coal mine; the multi-dimensional monitoring data at least comprise gas concentration, gas pressure, temperature and rock stratum vibration parameters of different spatial positions in each gas monitoring unit. According to the method, the limitation of traditional single parameter monitoring is broken through by fusing multi-dimensional data such as gas concentration, gas pressure, temperature and rock stratum vibration, accurate characterization of the gas leakage risk is achieved by combining quantitative evaluation of the gas diffusion dynamic index and the structural integrity coefficient, the basis of initial risk evaluation is improved, and the risk assessment accuracy is improved. By introducing the influence correction coefficient and the leakage correlation effect of the adjacent monitoring units and through quantitative analysis of the fracture connectivity and the spatial distance, the risk value is dynamically corrected, and the problem of evaluation deviation caused by neglecting the regional correlation in a traditional method is solved.

Description

Technical Field

[0001] This invention relates to the field of gas leak monitoring technology, specifically to a method and system for monitoring and preventing gas leaks in closed coal mines. Background Technology

[0002] Closed coal mines are prone to gas leaks due to aging underground support structures, redistribution of rock stress, and failure of sealing facilities. The leak paths are often hidden, and the concentration fluctuates greatly. Traditional monitoring methods rely heavily on fixed-point sampling, which has drawbacks such as large blind spots and delayed response. In existing technologies, gas monitoring is mostly used for real-time management of producing mines. The dynamic monitoring system for closed coal mines is not very comprehensive. It lacks accurate characterization of gas leakage and diffusion patterns and quantitative assessment of the impact on the surrounding area, resulting in insufficient targeted disaster prevention and control measures and posing a threat to the safety of the surrounding environment and personnel.

[0003] Therefore, this application proposes a method and system for monitoring and preventing coal mine gas leaks. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for monitoring and preventing coal mine gas leaks, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for monitoring and preventing coal mine gas leaks, comprising: Acquire multidimensional monitoring data from each gas monitoring unit in the closed coal mine; the multidimensional monitoring data includes at least the gas concentration, gas pressure, temperature, and rock vibration parameters at different spatial locations within each gas monitoring unit; Based on monitoring data from various dimensions, initial risk values ​​for gas leakage at different spatial locations are obtained; these initial risk values ​​are used to characterize the likelihood of gas breaching the sealing structure at the corresponding location. Based on the initial risk value of gas leakage at different spatial locations, the influence correction coefficient corresponding to each gas monitoring unit is obtained; the influence correction coefficient is at least used to characterize the degree of correlation between the leakage risk of the corresponding gas monitoring unit and the leakage status of its adjacent gas monitoring units; Based on the aforementioned impact correction coefficient and the initial risk value of gas leakage, the corrected leakage risk value of each gas monitoring unit is obtained; Based on the revised leakage risk value, corresponding level of external leakage disaster prevention and control measures are initiated and dynamically adjusted.

[0006] As a specific solution to the technical solution of this application, the step of obtaining multi-dimensional monitoring data within each gas monitoring unit of the closed coal mine includes: Based on the distribution of shafts and tunnels, sealed areas, and rock fracture characteristics of the closed coal mine, the closed coal mine is divided into multiple first gas monitoring units; Based on the integrity of historical monitoring data and geological stability of each first gas monitoring unit, a second gas monitoring unit is obtained; the second gas monitoring unit is any area in each first gas monitoring unit where multidimensional data acquisition has not been completed or where data is abnormal; Based on the spatial distribution of the second gas monitoring unit, a monitoring network consisting of mobile monitoring equipment and fixed sensor nodes is deployed to collect real-time monitoring data at different spatial locations. The collected real-time monitoring data is processed for noise reduction and outlier removal to obtain multi-dimensional monitoring data of the second gas monitoring unit.

[0007] As a specific solution to the technical solution of this application, the step of obtaining the initial risk value of gas leakage at different spatial locations based on monitoring data from various dimensions includes: Based on the air pressure and temperature parameters at different spatial locations, a gas diffusion dynamic index is obtained; the gas diffusion dynamic index is used to characterize at least the magnitude of the dynamic force of gas flow in rock fissures; Based on the vibration parameters of the rock strata at different spatial locations, a structural integrity coefficient is obtained; the structural integrity coefficient is used at least to characterize the leakage resistance of the surrounding sealing structure and the rock strata at that location. Based on the gas diffusion dynamics index and the structural integrity coefficient, a gas leakage potential value is obtained; the gas leakage potential value is used to characterize at least the inherent probability of gas leakage at a single spatial location; By combining the gas concentration data and gas leakage potential value at the corresponding location, the initial risk value of gas leakage is obtained; the initial risk value of gas leakage is positively correlated with the gas concentration and leakage potential value.

[0008] As a specific solution to the technical solution of this application, the method of obtaining the gas diffusion dynamic index based on the air pressure and temperature parameters at different spatial locations includes: Based on the ideal gas law, a three-dimensional correlation model of gas pressure, temperature and gas concentration is established. Gas pressure and temperature data at different spatial locations are substituted into the model to obtain the theoretical gas diffusion rate. Select standard state parameters under the same geological conditions as the closed coal mine, namely standard air pressure P0 and standard temperature T0, and calculate the deviation values ​​ΔP and ΔT between the actual monitoring parameters and the standard parameters; Based on the theoretical gas diffusion rate and the deviation values ​​ΔP and ΔT, the gas diffusion dynamic index is obtained through weighted calculation, and the calculation formula is as follows:

[0009] Where D is the gas diffusion dynamic index, v is the theoretical gas diffusion rate, α, β, and γ are the weighting coefficients of rate, pressure deviation, and temperature deviation, respectively, and α+β+γ=1; ΔP is the difference between actual gas pressure and standard gas pressure, ΔT is the difference between actual temperature and standard temperature, P0 is the standard gas pressure, and T0 is the standard temperature.

[0010] As a specific solution to the technical solution of this application, the method of obtaining the structural integrity coefficient based on the rock strata vibration coefficient at different spatial locations includes: For any spatial location within the same gas monitoring unit, extract the frequency data of the rock strata vibration accelerometer within a continuous preset time period at that location; Based on vibration data, obtain the vibration amplitude variation coefficient C. v and the dominant frequency offset Δf; the vibration amplitude variation coefficient C v The ratio of the standard deviation to the mean of the vibration amplitude is given by Δf, and the main frequency offset Δf is the difference between the actual main frequency and the main frequency when the sealed structure is stable. Set the baseline coefficient of variation C for structural integrity. v The structural integrity coefficient is calculated using the following formula, taking 0 and the reference fundamental frequency offset Δf0 as the reference:

[0011] Where S is the structural integrity coefficient, with a value range of [0, 1]; δ and ε are the weighting coefficients of the coefficient of variation and the main frequency offset, respectively, and δ+ε=1; when S≤0, the structure is judged to have failed.

[0012] As a specific solution to the technical solution of this application, the step of obtaining the gas leakage potential value based on the gas diffusion dynamic index and the structural integrity coefficient includes: Analyze the matching relationship between the gas diffusion dynamic index D and the structural integrity coefficient S at the same spatial location. When D ≥ the preset dynamic threshold and S ≤ the preset integrity threshold, it is determined that there is leakage potential at that location. Based on the leakage potential assessment, and combined with the vertical distance L between the location and the sealing layer, the leakage path resistance coefficient R is obtained; the greater the distance, the greater the resistance coefficient. The gas leakage potential value is calculated using the following formula:

[0013] Where Q is the gas leakage potential value, and R is the leakage path resistance coefficient, which is positively correlated with the vertical distance L.

[0014] As a specific solution to the technical solution of this application, the step of combining the gas concentration data at the corresponding location with the gas leakage potential value to obtain the initial risk value of gas leakage includes: Based on the gas concentration at different spatial locations within each gas monitoring unit, the degree of concentration exceeding the standard C is obtained, which is the ratio of the actual concentration to the safe concentration threshold. The concentration exceedance level C at each spatial location is matched with the gas leakage potential value Q according to spatial coordinates to construct a risk assessment matrix; Based on the risk assessment matrix, the initial risk value R0 of gas leakage is obtained through normalization. The calculation formula is as follows:

[0015] Where norm() is a normalization function that normalizes the parameter to the interval [0,1], λ and u are the weighting coefficients of the concentration exceeding the standard and the leakage potential value, respectively, and λ+u=1.

[0016] As a specific solution to the technical solution of this application, the step of obtaining the influence correction coefficient corresponding to each gas monitoring unit based on the initial risk value of gas leakage at different spatial locations includes: Based on the spatial distribution of each gas monitoring unit, the target monitoring unit is obtained; the target monitoring unit is any unit among the gas monitoring units for which the influence correction coefficient has not been obtained; Based on the target monitoring unit, associated monitoring units are obtained; the associated monitoring units are gas monitoring units that are adjacent to the target monitoring unit and have communication with rock fissures. Obtain the crack connectivity K and spatial distance d between the target monitoring unit and the associated monitoring unit, and calculate the initial risk value difference ΔR0 between the two units within the same time period. Based on the fracture connectivity K, spatial distance d, and risk value difference ΔR0, the domain influence I is obtained using the following formula:

[0017] Based on the domain influence degree I of all associated monitoring units of the target monitoring unit, the average value is taken as the influence correction coefficient η of the target monitoring unit.

[0018] As a specific solution to the technical solution of this application, the step of obtaining the corrected leakage risk value of each gas monitoring unit based on the influence correction coefficient and the initial risk value of gas leakage, and activating the corresponding level of gas disaster prevention and control measures, includes: The corrected leakage risk value R is calculated using the following formula:

[0019] Where R is the corrected leakage risk value, R0 is the initial risk value of gas leakage, and η is the influence correction coefficient; Three risk thresholds are preset: low risk threshold R1, medium risk threshold R2, and high risk threshold R3, with R1... <R2<R3; When R ≤ R1, initiate primary prevention and control, strengthen the monitoring frequency in this area, and keep the ventilation system operating normally; When R1 < R ≤ R2, initiate secondary prevention and control. On the basis of primary prevention and control, conduct airtightness detection on the sealing structure, and supplement grouting to reinforce weak areas; When R > R3, initiate tertiary prevention and control, immediately block this area, start the emergency drainage system, evacuate the surrounding personnel and set up a warning area.

[0020] As a specific solution of the technical scheme of this application, it further includes a step of feedback on the effect of prevention and control measures: After initiating the prevention and control measures, continuously monitor the multi-dimensional data of the corresponding gas monitoring unit, and calculate the risk reduction rate after prevention and control ; If ΔR% ≥ the preset effect threshold, maintain the current prevention and control measures. If ΔR% < the preset effect threshold, adjust the weight distribution of the influence correction coefficient η, recalculate the corrected leakage risk value, and optimize the prevention and control measures.

[0021] A closed coal mine gas leakage monitoring and disaster prevention and control system includes: A data acquisition module, including fixed sensing nodes and mobile monitoring devices. The fixed sensing nodes are arranged around the sealed area and at key positions in the roadway to collect gas concentration, air pressure, and temperature data; the mobile monitoring device is equipped with an infrared gas detection unit and a vibration sensor to supplement the collection of rock layer vibration and gas data in hidden areas. The data acquisition module realizes data transmission through industrial Ethernet; A risk assessment module, connected to the data acquisition module, for receiving multi-dimensional monitoring data, and calculating the gas diffusion power index, structural integrity coefficient, and initial gas leakage risk value based on a preset algorithm; A correction calculation module, connected to the risk assessment module, for obtaining the initial risk value of each monitoring unit, calculating the field influence degree and the influence correction coefficient, and then obtaining the corrected leakage risk value; A prevention and control execution module, connected to the correction calculation module, includes a ventilation control unit, a grouting reinforcement unit, an emergency drainage unit, and an acoustic-optical warning unit, for initiating corresponding-level prevention and control measures according to the corrected risk value; A visualization monitoring module, connected to the data acquisition module, the risk assessment module, and the prevention and control execution module respectively, and based on the three-dimensional geological model of the closed coal mine, it can display the risk status of each monitoring unit and the implementation of prevention and control measures in real time, and trigger a hierarchical warning pop-up window and voice prompt when the risk value exceeds the standard.

[0022] Compared with the prior art, the beneficial effects of this invention are: This application overcomes the limitations of traditional single-parameter monitoring by integrating multi-dimensional data such as gas concentration, gas pressure, temperature, and rock vibration. By combining the quantitative assessment of gas diffusion dynamic index and structural integrity coefficient, it achieves accurate characterization of gas leakage risk and improves the basis of initial risk assessment. By introducing the influence correction coefficient and the leakage correlation effect of adjacent monitoring units, and through the quantitative analysis of fracture connectivity and spatial distance, the risk value is dynamically corrected, solving the problem of assessment bias caused by neglecting regional correlation in traditional methods.

[0023] Meanwhile, based on the corrected risk value, tiered prevention and control measures were initiated, and the plan was dynamically optimized through effect feedback to achieve precise matching and real-time adjustment of prevention and control measures, effectively improving the prevention and control capabilities of coal mine gas disasters and reducing the risk of leakage accidents. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the method for monitoring and preventing coal mine gas leaks proposed in this application. Figure 2 This is a schematic diagram of the structure of the coal mine gas leakage monitoring and disaster prevention system proposed in this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0026] The terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. For example, the first cluster and the second cluster mentioned below belong to different clusters. It should be understood that such names can be used interchangeably where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules in the embodiments of this application is merely a logical division. In actual applications, there may be other division methods. For example, multiple modules may be combined into or integrated into another system, or some features may be ignored or not performed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms. None of these are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0027] To address the technical problems mentioned in the background, this application proposes an embodiment of a method and system for monitoring and preventing gas leaks in closed coal mines. This method, through the construction of a multi-dimensional monitoring system, a quantitative risk assessment model, and a dynamic correction mechanism, achieves accurate identification and graded prevention and control of gas leak risks in closed coal mines. Figure 1 As shown, the method for monitoring and preventing coal mine gas leaks includes steps S100 to S500: Step S100: Obtain multi-dimensional monitoring data from each gas monitoring unit in the closed coal mine. The core objective of this step is to construct a three-dimensional monitoring network covering the entire area of ​​a closed coal mine, acquiring fundamental data that comprehensively reflects the potential risks of gas leakage. This multi-dimensional monitoring data includes at least gas concentration, gas pressure, temperature, and rock vibration parameters at different locations within each gas monitoring unit, collectively forming the core indicator system for gas leakage risk assessment.

[0028] In the embodiments of this application, a hybrid data acquisition mode combining historical data reuse and real-time data supplementation can be adopted to improve data acquisition efficiency and reduce monitoring costs. For example, if a well-established monitoring system has been established before the closure of a coal mine, its historical monitoring data (such as annual changes in gas concentration in different areas, rock stratum stability data, etc.) are stored in the coal mine safety monitoring server according to the classification rules of monitoring unit, spatial coordinates, and monitoring time. This data can be directly retrieved through professional data management software (such as the KJ90X coal mine safety monitoring system data terminal, SQL Server database query tools, etc.). For subfolders stored in the "2024 Pre-closure Monitoring Data" directory on the server, the corresponding gas concentration curves and rock stratum vibration records can be quickly located by using spatial representations such as the 100m horizontal east wing, without the need for repeated monitoring of the data completion area.

[0029] To address the challenges of large, closed coal mines with extensive monitoring areas and complex geological conditions, a "Gas Monitoring Data Index Library" can be established on the server. This library can be used to label the storage path of each monitoring unit's data (e.g., "Server IP: 192.168.1.100\Gas Monitoring\Second Mining Area\202503-Hidden Area-Vibration Data.csv"), data type (e.g., gas concentration, rock vibration), monitoring accuracy, and validity period. During data retrieval, the index library enables second-level location of target data. Simultaneously, it allows for comparative queries of historical data from adjacent units, aiding in data consistency verification and preventing interference from abnormal data caused by sensor malfunctions.

[0030] To achieve the collection and management of monitoring data, step S100 also includes steps S110 to S140: Step S110: Divide the coal mine into multiple first gas monitoring units based on the geological characteristics of the closed coal mine. This step requires combining the distribution of mine shafts and tunnels, the extent of sealed areas, and the characteristics of rock fissures in closed coal mines to construct a monitoring unit system using a differentiated division strategy. This ensures that each unit has a unified geological background and risk characteristics, specifically including: Shaft and tunnel guidance division: For closed coal mines with complete shaft and tunnel systems, the mine is divided into multiple independent units, with the main roadways and connecting roadways as boundaries. Each unit corresponds to the original production mining area or tunneling face. For example, a closed coal mine containing 3 production mining areas, 2 tunneling faces, and 1 important chamber can be divided into 6 first gas monitoring units. Each unit is bounded by the outline of the original production area's shaft and tunnel, ensuring that the monitoring range matches the geological structure unit.

[0031] Sealed Area Division: For areas that have been sealed, each sealed area and its surrounding 50m radius are divided into independent monitoring units, with the sealing wall as the core boundary. For double-sealed structures in high-gas areas, the area between the inner and outer sealing walls can be separately divided into monitoring units, focusing on monitoring the leakage status of the sealing structure. For example, a coal mine has 8 permanent sealing walls, 3 of which are double-sealed in high-gas areas. Based on this, it can be divided into 11 first-level gas monitoring units to achieve precise coverage of the sealed areas.

[0032] Risk gradient classification: Based on geological exploration data, high-risk areas such as areas with dense rock fractures and fault fracture zones are classified using a denser grid method. For example, within the fault influence zone, the area is divided into 20m×20m grid units, while areas with intact rock strata are divided into 50m×50m units, forming a differentiated monitoring unit layout of "dense grid in high-risk areas and extensive grid in stable areas," which ensures monitoring accuracy while controlling monitoring costs.

[0033] Step S120: Screening the second gas monitoring unit based on data integrity The second gas monitoring unit is any area within the first gas monitoring units that has not completed multidimensional data acquisition or exhibits abnormal data. Its identification requires a dual mechanism of "historical data verification + on-site inspection and verification." Specifically, the data management system assesses the integrity of historical data from each first monitoring unit. If a unit has more than 30% of its monitoring parameters missing or its data fluctuation exceeds twice the normal range, it is initially identified as a data anomaly area. Subsequently, on-site inspections are conducted to check the sensor deployment and the integrity of the sealing structure to ultimately determine the scope of the second gas monitoring unit.

[0034] For example, if the historical data of a certain first monitoring unit shows a missing gas concentration parameter for three consecutive months, and on-site inspection reveals that the original sensor is damaged, this unit will be designated as the second gas monitoring unit, requiring targeted supplementary data collection. It should be noted that the multidimensional data acquisition methods for each first gas monitoring unit are the same as those for the second gas monitoring unit, ensuring consistency in data acquisition standards.

[0035] Step S130: Construct a fixed + mobile monitoring network to collect real-time data Based on the spatial distribution characteristics of the second gas monitoring unit, a hybrid monitoring mode combining a fixed sensor node network and mobile monitoring equipment prediction is adopted to achieve comprehensive acquisition of multi-dimensional data, specifically including: Fixed sensor node deployment: Fixed sensor nodes are deployed at key locations such as the perimeter of the sealed area, tunnel intersections, and areas with developed rock fissures. Each node integrates a gas concentration sensor (measurement range 0-100% CH4, accuracy ±0.1%), a pressure sensor (measurement range 80-120 kPa, accuracy ±0.5 kPa), a temperature sensor (measurement range -20℃-80℃, accuracy ±0.2℃), and a vibration sensor (measurement range 0-100 Hz, accuracy ±0.1 Hz). The sensor nodes are connected to the monitoring system via industrial Ethernet, with a data transmission interval of 10 seconds to ensure real-time performance.

[0036] Mobile monitoring equipment supplementation: For concealed areas (such as deep within abandoned alleyways or behind sealed walls), mobile monitoring robots equipped with infrared gas detection units and high-precision vibration sensors are used for inspection. The mobile robots can travel along preset tracks or be remotely controlled, collecting data every 5 meters, focusing on supplementing monitoring data in areas not covered by fixed nodes. For areas with excessive concentrations of harmful and toxic gases, drones equipped with gas sampling devices are used for remote data collection, avoiding the risk of personnel exposure.

[0037] Step S140: Data preprocessing to obtain effective multidimensional monitoring data The collected real-time data undergoes noise reduction and outlier removal to ensure data validity. The specific processing flow includes: Wavelet transform algorithm was used to denoise the rock vibration data and filter environmental interference signals. Outliers (data exceeding the mean ± 3 standard deviations) in parameters such as gas concentration and air pressure were removed using the 3σ criterion. Missing data were supplemented using linear interpolation between adjacent time points. The processed multidimensional monitoring data must meet the following requirements: data integrity ≥ 95% and outlier rate ≤ 1%, ensuring a reliable data foundation for subsequent risk assessment.

[0038] Step S200: Obtain the initial risk value of gas leakage based on multi-dimensional monitoring data. This step constructs a multi-dimensional coupled risk assessment model to transform multi-dimensional monitoring data into a quantified initial risk value for gas leakage. This risk value at least characterizes the likelihood of gas breaching the sealing structure at the corresponding location. Existing methods often assess risk based solely on the single parameter of gas concentration, neglecting key influencing factors such as diffusion dynamics and structural stability, leading to significant risk assessment bias. This application achieves accurate risk quantification through a coupled model of dynamics, structure, and concentration, specifically including steps S210 to S240.

[0039] Step S210: Obtain the gas diffusion dynamic index based on air pressure and temperature parameters The gas diffusion dynamics index is used to characterize the dynamic force of gas flow in rock fissures. Its acquisition requires combining the ideal gas law with field parameter deviation analysis, specifically including the following steps: A three-dimensional correlation model was established: Based on the ideal gas law PV=nRT, a three-dimensional correlation model of gas pressure P, temperature T, and gas concentration C was established in conjunction with the gas concentration parameter. The calculation model of the theoretical gas diffusion rate v was obtained by fitting the model using a multiple linear regression algorithm.

[0040] Wherein, K is a geological coefficient, determined based on the permeability of coal mine strata (range 0.8-1.2). By substituting the air pressure and temperature data from different spatial locations into the model, the theoretical gas diffusion rate at each point can be obtained.

[0041] Calculate the parameter deviation values: Select standard state parameters (standard air pressure P0 = 101.3 kPa, standard temperature T0 = 25℃) under the same geological conditions in a closed coal mine, and calculate the deviation values ​​ΔP = Pactual - P0 and ΔT = Tactual - T0 between the actual monitored parameters and the standard parameters. The deviation values ​​reflect the degree of difference between the on-site environment and the standard conditions, and directly affect the gas diffusion dynamics.

[0042] Weighted calculation of the dynamic index: The weights of each parameter are determined by expert scoring (rate weight α=0.5, pressure deviation weight β=0.3, temperature deviation weight γ=0.2, satisfying α+β+γ=1), and the gas diffusion dynamic index is calculated using the following formula:

[0043] Wherein, D is the gas diffusion dynamic index, with a value range of [0, 1]. The larger the D value, the stronger the gas diffusion dynamic and the higher the risk of leakage.

[0044] Step S220: Obtain the structural integrity coefficient based on rock vibration parameters The structural integrity coefficient is used to characterize the leakage resistance of the surrounding sealing structure and rock strata at a given location. It is quantified through the variability characteristics of vibration data and the analysis of dominant frequency shifts, specifically including: Extracting vibration characteristic data: For any spatial location within the same gas monitoring unit, extract the rock strata vibration acceleration and frequency data for a continuous 30 minutes at that location. The sampling frequency is set to 100Hz to ensure that the data can reflect the complete characteristics of structural vibration.

[0045] Calculate vibration characteristic parameters: Calculate the coefficient of variation C of vibration amplitude based on vibration data. v and the main frequency offset Δf. Where C v The ratio of the standard deviation to the mean of the vibration amplitude reflects the stability of the vibration (C). vThe larger the value, the more unstable the vibration; Δf is the difference between the actual main frequency and the main frequency when the structure is sealed (the stable main frequency is determined by monitoring data in the early stage of pit closure). The larger the absolute value of Δf, the worse the surface structure integrity.

[0046] Calculate the structural integrity coefficient: Set the baseline coefficient of variation C for structural integrity. v 0=0.2 and reference main frequency offset Δ f 0 = 5Hz, the structural integrity coefficient is calculated using the following formula:

[0047] Where S is the structural integrity coefficient, with a value range of [0,1], and δ=0.6 and ε=0.4 are the weighting coefficients of the coefficient of variation and the dominant frequency offset, respectively (satisfying δ+ε=1). When S≤0, the structure is determined to have failed, and emergency measures must be initiated immediately.

[0048] Step S230: Obtain the gas leakage potential value based on the dynamic index and integrity coefficient. The gas leakage potential value characterizes the inherent possibility of gas leakage in a single space and requires comprehensive calculation based on structural diffusion dynamics, structural resistance, and leakage path characteristics. Leakage potential determination: Analyze the matching relationship between the gas diffusion dynamic index D and the structural integrity coefficient S at the same spatial location. When D≥0.5 (preset dynamic threshold) and S≤0.6 (preset integrity threshold), the location is determined to have leakage potential; otherwise, it is determined to have no obvious leakage potential.

[0049] Determine the leakage path resistance: Based on the leakage potential assessment, and combined with the vertical distance L between the location and the sealing layer, obtain the leakage path resistance coefficient R. The relationship between R and L is then fitted through field tests.

[0050] The greater the distance, the greater the drag coefficient, and the more difficult it is to leak.

[0051] Calculate the leakage potential value: The gas leakage potential value is calculated using the following formula:

[0052] Where Q is the gas leakage potential value, which ranges from [0,1]. The larger the Q value, the higher the inherent possibility of gas leakage at that location.

[0053] Step S240: Obtain the initial risk value of gas leakage based on gas concentration. The initial risk value of gas leakage is a comprehensive reflection of both intrinsic potential and extrinsic concentration, and is positively correlated with both gas concentration and leakage potential. The calculation process is as follows: Calculate the degree of concentration exceeding the standard: Based on the gas concentration at different spatial locations within each gas monitoring unit, obtain the degree of concentration exceeding the standard C, which is the ratio of the actual concentration to the safe concentration threshold. When Pactual ≤ Psafe, C = 1; when Pactual > Psafe, C is calculated based on the actual ratio.

[0054] Construct a risk assessment matrix: Match the concentration exceedance level C and the gas leakage potential value Q at each spatial location according to spatial coordinates to construct a two-dimensional risk assessment matrix of concentration and potential. Each element in the matrix represents the risk combination characteristics for a specific spatial location.

[0055] Calculate the initial risk value: The influence of dimensions is eliminated through normalization, and the initial gas leakage value R0 is obtained by weighted summation.

[0056] Where norm() is a normalization function that normalizes the parameter to the range of [0,1]. λ=0.6 and u=0.4 are the weighting coefficients for the degree of concentration exceeding the standard and the leakage potential value, respectively, satisfying λ+u=1. R0 takes the value range of [0,1]. The larger R0 is, the higher the initial leakage risk.

[0057] Step S300: Obtain the impact correction coefficient for each monitoring unit based on the initial risk value. The influence correction coefficient is used to characterize the degree to which the leakage risk of a corresponding gas monitoring unit is correlated with the leakage status of its adjacent gas monitoring units. In a closed coal mine, the monitoring units are interconnected through rock fissures; the leakage risk of a single unit is significantly affected by the leakage risk of its neighboring units. Existing methods ignore this spatial correlation, leading to limitations in risk assessment. This step, specifically steps S310 to S350, refines the risk assessment by quantifying the mutual influence between units.

[0058] Step S310: Determine the target monitoring unit The target monitoring unit is any unit in each gas monitoring unit that has not yet had its influence correction coefficient obtained. To ensure the comprehensiveness of the correction coefficient calculation, a unit-by-unit, sequential approach is adopted, gradually expanding from the coal mine boundary unit to the central unit to avoid duplicate calculations or omissions.

[0059] Step S320: Identify associated monitoring units A related monitoring unit is a gas monitoring unit that is adjacent to the target monitoring unit and connected by rock fissures. The connectivity between units is determined using ground-penetrating radar. If a connecting fissure with a width ≥ 0.1 mm exists between two units and the distance is ≤ 50 m, it is determined to be a related monitoring unit. For example, if the target monitoring unit is the eastern wing unit of a mining operation, and its adjacent central unit of a mining operation and western wing unit of a mining operation both have connecting fissures, then these two units are both related monitoring units.

[0060] Step S330: Obtain inter-unit correlation parameters Three key parameters were collected between the target monitoring unit and the associated monitoring units: The fracture connectivity K is calculated by multiplying the fracture width and length, K=w×L (w is the average fracture width, L is the connectivity length), and after normalization, the value range is [0,1]. Spatial distance d is the straight-line distance between the centers of the two units (in meters). The initial risk value difference ΔR0 is the absolute value of the difference between the initial risk values ​​of the two units within the same time period, ΔR0 = |R0 target - R0 association|.

[0061] Step S340: Calculate the domain influence Domain Influence I characterizes the degree of risk impact that associated monitoring units have on the target monitoring unit. The calculation formula is as follows:

[0062] The value of region I ranges from [0,1]. A larger I value indicates a stronger risk impact of the surface-associated unit on the target unit. For example, if K=0.8, ΔR0=0.3, and d=30m, then... The surface shows that the influence of the associated unit on the target unit is relatively weak.

[0063] Step S350: Calculate the influence correction factor Based on the domain influence degree I of all associated monitoring units of the target monitoring unit, the average value is taken as the influence correction coefficient η of the target monitoring unit, i.e. (n is the number of associated monitoring units). The value of η ranges from [0,1]. The larger the value of η, the stronger the risk impact of the target unit on the adjacent units, and the more significant the correction of the initial risk value is required.

[0064] Step S400: Obtain the corrected leakage risk value for each monitoring unit. The corrected leakage risk value is a comprehensive reflection of the chef's risk value and its spatial correlation, and can more accurately reflect the actual leakage risk of the monitoring unit. The corrected leakage risk value R is calculated using the following formula:

[0065] Among them, R is the corrected leakage risk value, and its value range is [0, 2]. The physical meaning of this formula is: when the risk of the associated unit is relatively high (η is relatively large), the actual risk of the target unit will increase based on the initial risk, so as to achieve accurate risk quantification. For example, if R0 = 0.6 and η = 0.2, then R = 0.6×(1 + 0.2) = 0.72, indicating that the risk of the target unit has increased after considering the influence of adjacent units.

[0066] Step S500: Start the hierarchical prevention and control measures based on the corrected risk value and adjust dynamically In this step, a dynamic prevention and control mechanism for risk grading, measure matching, and effect feedback is established to ensure the pertinence and effectiveness of the prevention and control measures. It specifically includes three links: risk grading determination, implementation of prevention and control measures, and optimization of effect feedback.

[0067] Risk grading determination: Preset three-level risk thresholds, which are determined in combination with the actual risk tolerance of the closed coal mine. The low-risk threshold R1 = 0.5, the medium-risk threshold R2 = 1.0, and the high-risk threshold R3 = 1.5, and R1 < R2 < R3 is satisfied. According to the size of the corrected leakage risk value R, each monitoring unit is divided into three risk levels: low, medium, and high.

[0068] Implementation of hierarchical prevention and control measures: Level 1 prevention and control (R ≤ R1): Applicable to low-risk areas. Start the basic prevention and control measures, including strengthening the monitoring frequency in this area (shortening the data collection interval from 10 seconds to 5 seconds), keeping the ventilation system running normally, conducting an external inspection of the sealing structure every week, and ensuring the stable operation of the monitoring equipment.

[0069] Level 2 prevention and control (R1 < R ≤ R2): Applicable to medium-risk areas. On the basis of Level 1 prevention and control, add targeted measures, conduct airtightness detection of the sealing structure (using the pressure decay method), inject polyurethane to plug the leakage points found in the detection, add 2 - 3 mobile monitoring points in the monitoring unit to achieve accurate risk tracking, conduct on-site inspections every 3 days, and record the risk change situation.

[0070] Level 3 prevention and control (R > R3): Applicable to high-risk areas. Immediately start the emergency prevention and control measures, block the area, set a warning range (radius ≥ 100m), evacuate the surrounding personnel, start the emergency gas drainage system, control the gas concentration within a safe range, conduct comprehensive reinforcement of the sealing structure, adopt double protection measures of grouting + steel plate plugging, and monitor the change of gas concentration in real time until the risk drops to a medium-low level. [[ID=2i]]

[0071] Optimization of effect feedback of prevention and control measures: To achieve dynamic adjustment of prevention and control measures, establish an effect feedback mechanism. After starting the prevention and control measures, continuously monitor the multi-dimensional data of the corresponding gas monitoring unit, and calculate the risk reduction rate after prevention and control , where R before is the corrected risk value before prevention and control, and R after is the corrected risk value in the stable state after prevention and control.

[0072] The preset effect threshold is 50%. If ΔR% ≥ 50%, it indicates that the prevention and control measures are effective and the current prevention and control measures should be maintained. If ΔR% < 50%, it indicates that the prevention and control measures are not targeted enough and the weight allocation of the influence correction coefficient η needs to be adjusted (such as increasing the weight of high-risk associated units), the corrected leakage risk value should be recalculated, and the prevention and control measures should be optimized (such as replacing the sealing material, increasing the extraction intensity, etc.).

[0073] After introducing the methods for monitoring and preventing gas leaks in closed coal mines, the following section details an embodiment of a gas leak monitoring and disaster prevention system for closed coal mines proposed in this application. This system, through the collaborative operation of multiple modules, achieves full-process monitoring, accurate assessment, and efficient prevention and control of gas leaks in closed coal mines, effectively solving technical problems such as incomplete coverage, inaccurate risk assessment, and delayed prevention and control response in traditional monitoring methods. Figure 2 As shown, the coal mine gas leak monitoring and disaster prevention system 200 includes: Data acquisition module 201 includes fixed sensing nodes and mobile monitoring devices for collecting multi-dimensional safety data from closed areas. The fixed sensing nodes are deployed around the sealed area and at key locations in the shaft, primarily collecting data on gas concentration, gas pressure, and temperature. The mobile monitoring devices are equipped with an infrared gas monitoring unit and a vibration sensor to supplement the collection of rock vibration and gas data from concealed areas. The data acquisition module achieves real-time transmission of the collected data via industrial Ethernet, ensuring the stability and timeliness of data transmission.

[0074] The risk assessment module 202, connected to the data acquisition module 201, is used to receive the multidimensional monitoring data, perform fusion analysis on the multidimensional monitoring data based on a preset algorithm, calculate the gas diffusion dynamic index and structural integrity coefficient, and obtain the initial risk value of gas leakage based on the gas diffusion dynamic index and structural integrity coefficient. The initial risk value of gas leakage is used to characterize at least the probability and basic hazard level of gas leakage in the closed coal mine.

[0075] The correction calculation module 203, connected to the risk assessment module 202, is used to obtain the initial risk value of gas leakage for each monitoring unit, calculate the domain influence degree based on the spatial location relationship and data correlation of each monitoring unit, obtain the influence correction coefficient based on the domain influence degree, and calibrate the initial risk value of gas leakage based on the influence correction coefficient to obtain the corrected leakage risk value. The corrected leakage risk value is used to more accurately reflect the actual distribution and diffusion trend of gas leakage risk.

[0076] The prevention and control execution module 204, connected to the correction calculation module 203, includes a ventilation control unit, a grouting reinforcement unit, an emergency extraction unit, and an audible and visual early warning unit. It is used to receive the corrected leakage risk value and activate corresponding prevention and control measures according to the magnitude of the corrected risk value. The activation level of the prevention and control measures is positively correlated with the corrected risk value, ensuring the rational allocation of prevention and control resources and the targeted nature of prevention and control actions.

[0077] The visualization monitoring module 205 is connected to the data acquisition module 201, the risk assessment module 202, and the prevention and control execution module 204 respectively. Based on the closed three-dimensional geological model of the coal mine, it integrates and displays the original monitoring data, risk status, and implementation status of prevention and control measures of each monitoring unit in real time. When the corrected risk value of any area exceeds the preset threshold, it triggers a graded early warning pop-up window and voice prompt. The graded early warning pop-up window at least includes the specific location of the area with the risk exceeding the standard, the risk level, and the suggested handling measures.

[0078] As a specific solution in the technical solution of this application, the risk assessment module 202 is also used to construct a multi-dimensional assessment matrix based on the rate of change of gas concentration data, pressure gradient and temperature fluctuation amplitude; Furthermore, the multidimensional monitoring data is substituted into the multidimensional evaluation matrix, and the weight coefficients of each parameter are determined by the analytic hierarchy process. Furthermore, the initial risk value of gas leakage is obtained by weighting the gas diffusion dynamics index and the structural integrity coefficient in combination with the weighting coefficient.

[0079] As a specific solution in the technical solution of this application, the correction calculation module 203 is also used to obtain historical risk data and fault records of each monitoring unit; And, based on the historical risk data, calculate the probability density of the risk occurrence; Furthermore, the influence correction coefficient is dynamically adjusted based on the probability density and the equipment operating status of the monitoring unit; Furthermore, the initial risk value of gas leakage is corrected using the adjusted impact correction factor, thereby further improving the accuracy of risk assessment.

[0080] As a specific solution in this application, the prevention and control execution module 204 is also used to preset multi-level risk thresholds. The risk thresholds include at least Level I, Level II, and Level III thresholds, corresponding to general risk, significant risk, and major risk, respectively. When the corrected repair risk value is lower than the Level I threshold, only the audible and visual warning unit is activated for routine alerts. When the corrected leakage risk is between the Level I and Level II thresholds, the ventilation control unit and the audible and visual warning unit are activated to dilute the gas concentration by strengthening ventilation. When the corrected leakage risk value is between the Level II and Level III thresholds, the emergency extraction unit, the ventilation control unit, and the audible and visual warning unit are activated to achieve active extraction and emission of gas. When the corrected leakage risk value is higher than the Level III threshold, the grouting reinforcement unit, the emergency extraction unit, the ventilation control unit, and the audible and visual warning unit are activated simultaneously to control the risk through a combination of grouting to seal the leakage channel, extraction to reduce the gas concentration, and ventilation to optimize airflow organization.

[0081] As a specific solution in the technical solution of this application, the data acquisition module 201 is also used to preprocess the acquired multidimensional monitoring data, the preprocessing including outlier removal, data smoothing and format standardization; In addition, data from fixed sensor nodes and mobile monitoring devices are synchronized via timestamps; In addition, a data quality assessment mechanism is established so that when the data transmission of a certain monitoring unit is interrupted or the proportion of abnormal data exceeds a preset ratio, an equipment fault alarm is triggered and the system automatically switches to a backup monitoring unit.

[0082] As a specific solution in the technical solution of this application, the visualization monitoring module 205 is also used to support the functions of historical data backtracking and risk trend prediction. Based on the historical monitoring data and risk assessment results of each monitoring unit, a time series analysis model is used to predict the risk change trend within a future preset time period. Furthermore, the prediction results will be overlaid in the form of curves in a three-dimensional geological model to provide data support for the early deployment of prevention and control measures.

[0083] As a specific solution in the technical solution of this application, the correction calculation module 203 is also used to obtain the geological structural parameters of the closed coal mine, including the rock stratum porosity, fault distribution and coal seam burial depth; Furthermore, a gas diffusion simulation model is constructed based on the geological structural parameters, and the corrected leakage risk value is substituted into the gas diffusion simulation model to predict the diffusion path and impact range of the gas leakage, and the diffusion path and impact range are synchronized to the visualization monitoring 205 for display.

[0084] As a specific solution in the technical solution of this application, the prevention and control execution module 204 is also used to establish a feedback mechanism for the effect of prevention and control measures, and to receive monitoring data such as gas concentration and air pressure fed back by the data acquisition module 201 in real time after the prevention and control measures are started; Furthermore, based on the feedback data, the effectiveness of the prevention and control measures is evaluated. When the rate of decrease in gas concentration is lower than the preset standard, the operating parameters of the prevention and control measures are automatically adjusted, such as increasing the extraction power of the emergency extraction unit and optimizing the air volume distribution of the ventilation control unit.

[0085] The embodiment of the closed coal mine gas leakage monitoring and disaster prevention system proposed in this application achieves comprehensive coverage of detection data through fixed and mobile structure acquisition methods. Accurate risk values ​​are obtained through risk assessment and correction calculations, and differentiated prevention and control measures are initiated based on the risk level. The entire process is monitored through a visualization module. This system effectively solves the technical problems of traditional closed coal mine gas monitoring, such as numerous blind spots, coarse risk assessment, and untimely response. It can accurately identify hidden gas leakage risks through multi-dimensional data fusion, achieve intelligent scheduling of prevention and control measures based on dynamic assessment, and improve risk handling efficiency through visualization and early warning mechanisms. It provides comprehensive technical support for the safety management of closed coal mines, preventing major safety accidents such as explosions and asphyxiation caused by gas leaks.

[0086] 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 embodiments and their equivalents.

Claims

1. A method for monitoring and preventing coal mine gas leaks, characterized in that, include: Acquire multi-dimensional monitoring data from each gas monitoring unit in the closed coal mine; The multidimensional monitoring data includes at least the gas concentration, gas pressure, temperature, and rock vibration parameters at different spatial locations within each gas monitoring unit; Based on monitoring data from various dimensions, initial risk values ​​for gas leakage at different spatial locations are obtained; these initial risk values ​​are used to characterize the likelihood of gas breaching the sealing structure at the corresponding location. Based on the initial risk value of gas leakage at different spatial locations, the influence correction coefficient corresponding to each gas monitoring unit is obtained; the influence correction coefficient is at least used to characterize the degree of correlation between the leakage risk of the corresponding gas monitoring unit and the leakage status of its adjacent gas monitoring units; Based on the aforementioned impact correction coefficient and the initial risk value of gas leakage, the corrected leakage risk value of each gas monitoring unit is obtained; Based on the revised leakage risk value, corresponding level of external leakage disaster prevention and control measures are initiated and dynamically adjusted.

2. The method for monitoring and preventing coal mine gas leaks according to claim 1, characterized in that, The acquisition of multi-dimensional monitoring data within each gas monitoring unit of the closed coal mine includes: Based on the distribution of shafts and tunnels, sealed areas, and rock fracture characteristics of the closed coal mine, the closed coal mine is divided into multiple first gas monitoring units; Based on the integrity of historical monitoring data and geological stability of each first gas monitoring unit, a second gas monitoring unit is obtained; the second gas monitoring unit is any area in each first gas monitoring unit where multidimensional data acquisition has not been completed or where data is abnormal; Based on the spatial distribution of the second gas monitoring unit, a monitoring network consisting of mobile monitoring equipment and fixed sensor nodes is deployed to collect real-time monitoring data at different spatial locations. The collected real-time monitoring data is processed for noise reduction and outlier removal to obtain multi-dimensional monitoring data of the second gas monitoring unit.

3. The method for monitoring and preventing coal mine gas leaks according to claim 2, characterized in that, The method of obtaining initial risk values ​​for gas leakage at different spatial locations based on monitoring data from various dimensions includes: Based on the air pressure and temperature parameters at different spatial locations, a gas diffusion dynamic index is obtained; the gas diffusion dynamic index is used to characterize at least the magnitude of the dynamic force of gas flow in rock fissures; Based on the vibration parameters of the rock strata at different spatial locations, a structural integrity coefficient is obtained; the structural integrity coefficient is used at least to characterize the leakage resistance of the surrounding sealing structure and the rock strata at that location. Based on the gas diffusion dynamics index and the structural integrity coefficient, a gas leakage potential value is obtained; the gas leakage potential value is used to characterize at least the inherent probability of gas leakage at a single spatial location; By combining the gas concentration data and gas leakage potential value at the corresponding location, the initial risk value of gas leakage is obtained; the initial risk value of gas leakage is positively correlated with the gas concentration and leakage potential value.

4. The method for monitoring and preventing coal mine gas leaks according to claim 1, characterized in that, The method for obtaining the gas diffusion dynamic index based on air pressure and temperature parameters at different spatial locations includes: Based on the ideal gas law, a three-dimensional correlation model of gas pressure, temperature and gas concentration is established. Gas pressure and temperature data at different spatial locations are substituted into the model to obtain the theoretical gas diffusion rate. Select standard state parameters under the same geological conditions as the closed coal mine, namely standard air pressure P0 and standard temperature T0, and calculate the deviation values ​​ΔP and ΔT between the actual monitoring parameters and the standard parameters; Based on the theoretical gas diffusion rate and the deviation values ​​ΔP and ΔT, the gas diffusion dynamic index is obtained through weighted calculation, and the calculation formula is as follows: ； Where D is the gas diffusion dynamic index, v is the theoretical gas diffusion rate, α, β, and γ are the weighting coefficients of rate, pressure deviation, and temperature deviation, respectively, and α+β+γ=1; ΔP is the difference between actual gas pressure and standard gas pressure, ΔT is the difference between actual temperature and standard temperature, P0 is the standard gas pressure, and T0 is the standard temperature.

5. The method for monitoring and preventing coal mine gas leaks according to claim 4, characterized in that, The method of obtaining the structural integrity coefficient based on the rock strata vibration coefficient at different spatial locations includes: For any spatial location within the same gas monitoring unit, extract the frequency data of the rock strata vibration accelerometer within a continuous preset time period at that location; Based on vibration data, obtain the vibration amplitude variation coefficient C. v and the dominant frequency offset Δf; the vibration amplitude variation coefficient C v The ratio of the standard deviation to the mean of the vibration amplitude is given by Δf, and the main frequency offset Δf is the difference between the actual main frequency and the main frequency when the sealed structure is stable. Set the baseline coefficient of variation C for structural integrity. v The structural integrity coefficient is calculated using the following formula, taking 0 and the reference fundamental frequency offset Δf0 as the reference: ； Where S is the structural integrity coefficient, with a value range of [0, 1]; δ and ε are the weighting coefficients of the coefficient of variation and the main frequency offset, respectively, and δ+ε=1; when S≤0, the structure is judged to have failed.

6. The method for monitoring and preventing coal mine gas leaks according to claim 5, characterized in that, The process of obtaining the gas leakage potential value based on the gas diffusion dynamics index and the structural integrity coefficient includes: Analyze the matching relationship between the gas diffusion dynamic index D and the structural integrity coefficient S at the same spatial location. When D ≥ the preset dynamic threshold and S ≤ the preset integrity threshold, it is determined that there is leakage potential at that location. Based on the leakage potential assessment, and combined with the vertical distance L between the location and the sealing layer, the leakage path resistance coefficient R is obtained; the greater the distance, the greater the resistance coefficient. The gas leakage potential value is calculated using the following formula: ； Where Q is the gas leakage potential value, and R is the leakage path resistance coefficient, which is positively correlated with the vertical distance L.

7. The method for monitoring and preventing coal mine gas leaks according to claim 3, characterized in that, The process of combining gas concentration data at the corresponding location with gas leakage potential values ​​to obtain the initial risk value of gas leakage includes: Based on the gas concentration at different spatial locations within each gas monitoring unit, the degree of concentration exceeding the standard C is obtained, which is the ratio of the actual concentration to the safe concentration threshold. The concentration exceedance level C at each spatial location is matched with the gas leakage potential value Q according to spatial coordinates to construct a risk assessment matrix; Based on the risk assessment matrix, the initial risk value R0 of gas leakage is obtained through normalization. The calculation formula is as follows: ； Where norm() is a normalization function that normalizes the parameter to the interval [0,1], λ and u are the weighting coefficients of the concentration exceeding the standard and the leakage potential value, respectively, and λ+u=1.

8. The method for monitoring and preventing coal mine gas leaks according to claim 1, characterized in that, The initial risk value of gas leakage based on different spatial locations is used to obtain the impact correction coefficient corresponding to each gas monitoring unit, including: Based on the spatial distribution of each gas monitoring unit, the target monitoring unit is obtained; the target monitoring unit is any unit among the gas monitoring units for which the influence correction coefficient has not been obtained; Based on the target monitoring unit, associated monitoring units are obtained; the associated monitoring units are gas monitoring units that are adjacent to the target monitoring unit and have communication with rock fissures. Obtain the crack connectivity K and spatial distance d between the target monitoring unit and the associated monitoring unit, and calculate the initial risk value difference ΔR0 between the two units within the same time period. Based on the fracture connectivity K, spatial distance d, and risk value difference ΔR0, the domain influence I is obtained using the following formula: ； Based on the field influence degree I of all associated monitoring units of the target monitoring unit, the average value is taken as the influence correction coefficient η of the target monitoring unit.

9. A method for monitoring and preventing coal mine gas leaks according to claim 8, characterized in that, Based on the influence correction coefficient and the initial risk value of gas leakage, obtain the corrected leakage risk value of each gas monitoring unit, and initiate gas disaster prevention and control measures of corresponding levels, including: Calculate the corrected leakage risk value R through the following formula: ； Where, R is the corrected leakage risk value, R0 is the initial risk value of gas leakage, and η is the influence correction coefficient; Preset three-level risk thresholds, a low-risk threshold R1, a medium-risk threshold R2, and a high-risk threshold R3, and R1 < R2 < R3; When R ≤ R1, initiate first-level prevention and control, strengthen the monitoring frequency of this area, and keep the ventilation system operating normally; When R1 < R ≤ R2, initiate second-level prevention and control. On the basis of the first-level prevention and control, conduct airtightness detection on the sealing structure and supplement grouting to reinforce weak areas; When R > R3, initiate third-level prevention and control, immediately block this area, initiate the emergency drainage system, evacuate the surrounding personnel and set up a warning area.

10. A method for monitoring and preventing coal mine gas leaks according to claim 9, characterized in that, It also includes the feedback step of the prevention and control measure effect: After initiating prevention and control measures, continuous monitoring of multidimensional data from the corresponding gas monitoring units was conducted to calculate the risk reduction rate after prevention and control. ; If ΔR% ≥ the preset effect threshold, maintain the current prevention and control measures. If ΔR% < the preset effect threshold, adjust the weight distribution of the influence correction coefficient η, recalculate the corrected leakage risk value and optimize the prevention and control measures.

11. A system for monitoring and preventing coal mine gas leaks, characterized in that, Including: The data acquisition module, including fixed sensing nodes and mobile monitoring devices. The fixed sensing nodes are arranged around the sealed area and at key positions in the roadway, and are used to collect gas concentration, air pressure, and temperature data; the mobile monitoring device is equipped with an infrared gas detection unit and a vibration sensor, and is used to supplement the collection of rock formation vibration and gas data in hidden areas. The data acquisition module realizes data transmission through industrial Ethernet; The risk assessment module, connected to the data acquisition module, is used to receive multi-dimensional monitoring data and calculate the gas diffusion power index, the structural integrity coefficient, and the initial risk value of gas leakage based on a preset algorithm; The correction calculation module, connected to the risk assessment module, is used to obtain the initial risk value of each monitoring unit, calculate the field influence degree and the influence correction coefficient, and then obtain the corrected leakage risk value; The prevention and control execution module, connected to the correction calculation module, includes a ventilation control unit, a grouting reinforcement unit, an emergency drainage unit, and an audible and visual warning unit, and is used to initiate prevention and control measures of corresponding levels according to the corrected risk value; The visual monitoring module, connected to the data acquisition module, the risk assessment module, and the prevention and control execution module respectively, based on the closed three-dimensional geological model of the coal mine, displays the risk status of each monitoring unit and the implementation of prevention and control measures in real time, and triggers a hierarchical warning pop-up window and voice prompt when the risk value exceeds the standard.

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