Intelligent mine gas monitoring system and gas safety risk identification and evaluation method

Abstract

The invention discloses an intelligent mine gas monitoring system and a gas safety risk identification and evaluation method. The system adopts a three-layer framework; the sensing layer is integrated with fixed monitoring equipment, mobile inspection equipment and methane emission detection equipment, and global data acquisition is realized through a multi-parameter sensor, an accurate positioning module and a gas emission calculation model; the transmission layer realizes underground data transmission through a wired-wireless hybrid network; and the application layer performs data fusion based on a digital twin mine model, and provides intelligent analysis, visual display and report generation functions. The risk assessment method comprises the following steps: collecting multi-source data in real time and carrying out space-time alignment and Kriging interpolation fusion; dynamically extracting four types of risk factors; identifying an abnormal aggregation area, and associating an equipment state traceability risk; and calculating a risk value through a weighting model, dividing four levels of risks, and triggering a grading response. According to the invention, gas risk dynamic identification, accurate traceability and automatic closed-loop control are realized, and the mine gas safety prevention and control capability is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of coal mine gas safety monitoring, and particularly relates to a mine intelligent gas monitoring system and a gas safety risk identification and evaluation method. BACKGROUND

[0002] At present, a large number of gas monitoring sensors are laid in coal mines, but gas inspection work still needs to be carried out. Coal mine gas inspection mainly detects concentration parameters such as methane, oxygen and carbon monoxide by a gas inspector carrying portable optical methane detectors and portable methane detection alarm instruments, and then the inspection results are manually recorded on a gas inspection shift report manual and a record card at the inspection site, and then manually compared with the monitoring data on the ground and the monitoring system. The current method has the following disadvantages: (1) low information release level, mainly manifested in serious information lag, lack of real-time monitoring and early warning, and difficult information sharing; (2) low efficiency, large workload of gas inspectors, and high labor intensity; (3) human errors such as reading errors, recording errors and point omission exist in manual inspection. The current coal mine gas inspection mode is a traditional way highly dependent on manual work, with complicated process and lagging information transmission. With the advancement of mine intelligence, intelligent inspection is upgrading towards intelligence, informatization and automation, and gradually realizes the replacement of "inspection" with "monitoring". In order to achieve this purpose, it is necessary to realize automatic data acquisition and transmission, application of intelligent terminals and self-calibration of sensors, automatic comparison and early warning. SUMMARY

[0003] The application provides a mine intelligent gas monitoring system and a gas safety risk identification and evaluation method.

[0004] Technical scheme: The application discloses a mine intelligent gas monitoring system, which comprises a perception layer, a transmission layer and an application layer.

[0005] The perception layer is used for collecting gas data and environmental data; the perception layer comprises fixed monitoring equipment, mobile inspection equipment and methane emission detection equipment.

[0006] The fixed monitoring equipment comprises a mine multi-parameter sensor and is arranged at a fixed position; the fixed monitoring equipment comprises a self-checking optical gas concentration detection sensor; the self-checking optical gas concentration detection sensor comprises a self-checking methane concentration detection sensor; the self-checking methane concentration detection sensor comprises a reference gas chamber and a self-checking module; the reference gas chamber stores standard concentration methane gas and nitrogen standard gas; the self-checking module is used for automatically inputting nitrogen standard gas to perform zero point calibration and inputting methane standard gas to perform range calibration according to a set period.

[0007] The mobile inspection equipment is used for collecting gas data and environmental data in the mine in real time according to an inspection path;

[0008] The methane emission detection equipment is used for calculating a roadway methane emission amount based on a roadway methane concentration and a wind speed.

[0009] The transmission layer is used for transmitting data acquired by the perception layer to an application layer in the mine or on the well through a hybrid network architecture combining wired and wireless transmission.

[0010] The application layer is used for processing the received data, including data storage management, intelligent analysis and early warning decision, visual human-computer interaction, control instruction issuing and system management, and forming a mine gas monitoring report; the visual human-computer interaction adopts a digital twin mine model based on a GIS roadway three-dimensional map to display the positions of each sensor, the mobile inspection equipment, a methane concentration gradient map, and data collected by each sensor in real time.

[0011] Further, the positions of the fixed monitoring equipment include upper and lower corner angles of a coal mining face, a return airway, a coal mining face, a heading face, and a mechanical and electrical chamber; a self-checking process of a self-checking methane concentration detection sensor includes: starting at a fixed time every day, passing nitrogen standard gas for x seconds to check whether zero point calibration is passed, if yes, passing y methane standard gas for calibration to check whether a range error is ≤±0.1%, if yes, the calibration is successful; if not, the calibration fails, and a device fault alarm is triggered, wherein x and y are preset values.

[0012] Further, the mobile inspection equipment includes a portable detector carried by a person, an inspection robot, and a positioning module, a vehicle-mounted detector, a wireless transmission module, a path planning module, a temperature and humidity sensor, and a methane detection module carried on the inspection robot; the path planning module dynamically generates a gas inspection path based on UWB positioning and a roadway three-dimensional map; the positioning module realizes real-time positioning of the inspection robot by fusing UWB and inertial navigation data; the methane detection module monitors methane concentration in real time; and the wireless transmission module supports multi-network adaptive switching to upload positioning data, methane concentration, and data detected by the vehicle-mounted detector to the transmission layer.

[0013] Further, the methane emission detection equipment includes a laser methane remote detector and a wind speed sensor; and the methane emission detection equipment calculates a roadway methane emission amount Q according to the following formula:

[0014] Q=C×V×S×k

[0015] Wherein, C is an average methane concentration acquired by the laser methane remote detector, V is a wind speed measured by the wind speed sensor, S is a roadway cross-sectional area, and k is a turbulent flow correction coefficient.

[0016] Further, the transmission layer includes an uphole network switch, a plurality of downhole network switches, a protocol converter, a wireless router, a mine 4G / 5G base station, a fiber transceiver, and a repeater; the uphole network switch and the plurality of downhole network switches are used to build a wired backbone network, provide port connection and network management, and establish communication connection between the uphole and the downhole; the protocol converter is used to connect different networks and realize protocol conversion; the different networks include wired to wireless and fieldbus to Ethernet; the wireless router is used to provide Wi-Fi coverage; the mine 4G / 5G base station is used to provide cellular network coverage and access; the fiber transceiver is used for fiber link transmission; and the repeater is used to extend the transmission distance of wireless or wired signals.

[0017] Further, after the application layer receives the data collected by the sensor, the data needs to be preprocessed, specifically: the data is subjected to moving average filtering to eliminate jump abnormal values.

[0018] The gas safety risk identification and evaluation method specifically includes the following steps:

[0019] Step 1: Time-space alignment and data fusion are performed in the digital twin mine model to generate a full-mine methane concentration field;

[0020] Step 2: Dynamic extraction of risk factors, including: methane concentration exceeding index C, methane concentration change gradient AG, high concentration aggregation risk A, and emission flux E;

[0021] Step 3: If the methane concentration exceeds the preset threshold, a DBSCA spatial clustering algorithm is used to automatically identify abnormal aggregation areas;

[0022] Step 4: Calculate the real-time risk value Risk_Score through a weighted scoring model:

[0023] Risk_Score=α·C+β·ΔG+γ·A+δ·E

[0024] Wherein, alpha, beta, gamma and delta are weights;

[0025] Step 5: Based on the risk value, determine the risk level, trigger the corresponding response measures and automatically issue control instructions.

[0026] Further, step 1 maps the precise positioning data of the mobile inspection equipment and the location of the fixed monitoring equipment to the same three-dimensional coordinate system, and generates a full-mine methane concentration field through a Kriging interpolation algorithm.

[0027] Further, the emission flux E is the ratio of the roadway methane emission amount to the preset safety threshold.

[0028] Further, four intervals with sequentially increasing ranges are set, if the calculated risk value belongs to the first interval, it is determined as low risk; if the risk value belongs to the second interval, it is determined as medium risk, and the inspection frequency of the mobile inspection device is automatically increased; if the risk value belongs to the third interval, it is determined as high risk, the corresponding ventilation equipment of the risk source is started, personnel are notified to evacuate, and the nearest inspection device is dispatched to the abnormal point to review along the shortest path; if the risk value belongs to the fourth interval, it is determined as critical, the whole area is powered off, and the emergency broadcasting system is triggered.

[0029] Advantages:

[0030] (1) The present application realizes real-time sensing and cooperation of all factors. The fixed monitoring device, mobile inspection terminal and methane emission detection device are integrated to construct a "point-line-surface" three-dimensional monitoring network, realizing millisecond-level full-time domain coverage of parameters such as underground methane concentration, oxygen, carbon monoxide and wind speed, and completely eliminating the monitoring blind area.

[0031] (2) The inspection efficiency is revolutionarily improved. Through the functions of autonomous path planning of the inspection robot, automatic data return of the portable terminal, self-checking of the sensor, etc., the artificial inspection intensity is reduced, the professional personnel are liberated to focus on risk judgment, and at the same time, the detection points are covered as much as possible.

[0032] (3) The data reliability and decision intelligence are greatly improved. Through the cross verification mechanism of multiple sources, the device anomaly is effectively identified; the self-checking optical sensor is used to eliminate false alarms caused by zero drift, ensuring the accuracy of long-term measurement, automatically correcting the influence of environmental factors such as temperature and humidity on the detection results, reducing false alarms or omissions, and the self-checking function greatly reduces the maintenance frequency and labor cost; the intelligent analysis engine is used to automatically generate decision suggestions such as gas concentration warning and emission exceeding, and the accident response speed is improved to seconds.

[0033] (4) The present application improves the comprehensiveness of risk perception. By fusing real-time data of fixed monitoring devices, mobile inspection devices and methane emission detection devices, and combining with the Kriging interpolation algorithm to generate a methane concentration field of the whole mine, three-dimensional dynamic coverage of underground gas risk is realized, and the artificial inspection blind area is completely eliminated.

[0034] (5) The accuracy of risk assessment is enhanced. Four-dimensional dynamic risk factors of concentration exceeding index C, concentration change gradient AG, high concentration aggregation risk A and emission flux E are proposed; the DBSCAN spatial clustering algorithm is used to automatically identify abnormal aggregation areas with methane concentration >1%; the risk value is dynamically calculated by a weighted scoring model, and the weight coefficient is adaptively adjusted according to the geological conditions, and the quantization error is reduced by more than 40%.

[0035] (6) Realize minute-level risk early warning. The concentration change gradient (AG>0.1% / min triggers a transient alarm) is captured by using a 5-minute sliding time window, compared with the traditional manual inspection cycle, and the time efficiency of major risk discovery is improved.

[0036] (7) Establish a closed-loop control mechanism. According to the low, medium, high and critical four-level risk grades, automatic triggering of graded response is realized, medium risk: automatically increase the frequency of inspection robots; high risk: linkage start local ventilation equipment and issue personnel evacuation instructions; critical: trigger the whole area power failure and emergency broadcast system, and the emergency response speed is compressed to a few seconds.

[0037] (8) Promote the digital transformation of safety management, the present application generates a gas risk thermal map in real time through a digital twin mine model, and pushes it to the associated terminal; automatically records the risk judgment, response and disposal of the whole process data. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 The system block diagram of the mine intelligent gas monitoring system of the present application;

[0039] Figure 2 The mine gas safety risk identification and evaluation method block diagram of the present application;

[0040] Figure 3 The core module block diagram of the application layer of the present application;

[0041] Figure 4 The flowchart of the self-checking of the methane sensor self-checking module. DETAILED DESCRIPTION

[0042] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application, and are incorporated in and constitute a part of this application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application.

[0043] As shown in Figure 1 The present application proposes a mine intelligent gas monitoring system, which is divided into three layers: perception layer, transmission layer and application layer. The perception layer is responsible for collecting gas and environmental data, and the perception layer device includes:

[0044] Fixed monitoring equipment, the fixed monitoring equipment includes a mine multi-parameter sensor, which is deployed in the upper and lower corner of the coal mining face, the return airway, the coal mining face, the heading face and the mechanical chamber.

[0045] Mobile inspection equipment, the mobile inspection equipment includes a portable detector carried by personnel, a vehicle-mounted detector of mine mobile equipment and an inspection robot, and the mobile inspection equipment is equipped with a methane detection module, a precise positioning module and a wireless transmission module.

[0046] The methane emission detection device comprises a laser methane remote sensor and a wind speed sensor, and calculates the roadway gas emission based on the roadway methane concentration and the wind speed.

[0047] The methane emission detection device calculates the roadway methane emission Q according to the following formula:

[0048] Q=C*V*S*k

[0049] Wherein, C is the average methane concentration obtained by the laser methane remote sensor, V is the wind speed measured by the wind speed sensor, S is the roadway cross-sectional area, and k is the turbulence correction coefficient.

[0050] The transmission layer is responsible for transmitting the key gas and environmental data obtained by the downhole sensing layer to the application in the mine or on the well through a hybrid network architecture combining wired and wireless; the network transmission equipment of the transmission layer comprises: an uphole network switch and a plurality of downhole network switches, which are used to build a wired backbone network, provide port connection and network management, and establish communication connection between the uphole and the downhole.

[0051] The application layer is responsible for data processing and analysis decision, realizes data access and preprocessing, data storage management, intelligent analysis and early warning decision engine, control instruction issuing, system management, and visual human-computer interaction platform, forms a mine gas monitoring report and a digital twin mine model.

[0052] As shown in Figure 2 , 3 The application also provides a mine gas safety risk identification and evaluation method based on the mine intelligent gas monitoring system, comprising the following steps:

[0053] (a) Real-time collection of downhole multi-position methane concentration, environmental parameters, device positioning and gas emission flux data through the fixed monitoring equipment, mobile inspection equipment and methane emission detection equipment of the sensing layer;

[0054] (b) Data uploading to the application layer through the wired-wireless hybrid network of the transmission layer, and spatio-temporal alignment and data fusion in the digital twin mine model;

[0055] (c) The application layer is divided into an application layer core module response and a visualization module, and dynamic extraction of risk factors, including: concentration exceeding index C, concentration change gradient AG, high concentration aggregation risk A, and emission flux E;

[0056] (d) Identification of dynamic risk sources based on a spatial clustering algorithm, and determination of risk inducements by correlating device operating states;

[0057] (e) Real-time risk value calculation through a weighted scoring model:

[0058] Risk_Score = a*C + b*AG + g*A + d*E,

[0059] wherein the weight coefficients a, b, g and d are dynamically adjusted according to the geological conditions;

[0060] (f) According to the risk value interval, low, medium, high and critical four levels of risk grade are divided, and the hierarchical response measures are triggered and the control instructions are automatically issued.

[0061] The present application sets four intervals with increasing ranges, if the calculated risk value belongs to the first interval, it is identified as low risk; if the risk value belongs to the second interval, it is identified as medium risk, and the inspection frequency of the mobile inspection device is automatically increased; if the risk value belongs to the third interval, it is identified as high risk, the corresponding ventilation equipment of the risk source is started, the personnel are notified to evacuate, and the nearest inspection device is dispatched to the abnormal point to review in the shortest path; if the risk value belongs to the fourth interval, it is identified as critical, and the whole area power failure and emergency broadcasting system are triggered.

[0062] The present embodiment adopts a three-layer architecture deployment, the perception layer is composed of three types of devices, fixed monitoring devices, mobile inspection devices and methane emission detection devices. The fixed monitoring device: the mine multi-parameter sensor is deployed at the key positions of the upper and lower corner of the coal mining face, the head of the return-to-entry working face, the electromechanical chamber, etc., to continuously monitor the parameters such as methane concentration (0-100% CH4), oxygen (0-25% O2), carbon monoxide (0-1000 ppm CO), and wind speed (0-15 m / s). The mobile inspection device includes: a personnel portable detector, which adopts a GJC4 methane detector and is equipped with a UWB positioning module (accuracy ± 30 cm) and a 4G / Wi-Fi dual-mode transmission; an explosion-proof rubber-tyred vehicle-mounted detector integrates a methane sensor and an inertial navigation unit; a patrol robot carries a laser methane detector (range 0-5% CH4), a temperature and humidity sensor, and a 360° panoramic camera, and realizes centimeter-level positioning through a UWB base station (deployment interval ≤ 50 m). The methane emission detection device: a set of laser methane remote detector (range 0-100% CH4) is arranged in the return airway every 200 meters, cooperating with an ultrasonic wind speed sensor (range 0-20 m / s).

[0063] Transmission layer networking implementation

[0064] Backbone network: industrial-grade gigabit optical ring network is adopted, and the core switch on the surface is connected with the underground substation switch (such as product model KJJ12) through mine flame-retardant optical cable;

[0065] Wireless coverage: a mine intrinsic safety type Wi-Fi6 access point (KXY12) is deployed in the main roadway every 300 meters, and a 4G base station is used to realize cellular network coverage;

[0066] Protocol conversion: install multi-protocol converters in the sensor cluster area to support RS485 / Can to Ethernet conversion.

[0067] Layer function implementation

[0068] Data preprocessing: perform sliding average filtering (window size 5 seconds) on sensor raw data to eliminate jump outliers; Digital twin platform: based on Unity3D engine, import the roadway three-dimensional model (accuracy ±0.1 m), and render the methane concentration thermal map in real time (color spectrum range: blue 0%→red ≥1.5%).

[0069] Among them, the flow of methane sensor self-checking is as shown in Figure 4 . Starting at 2:00 every day, pass through 10 seconds of nitrogen standard gas, check if the zero point calibration is passed, if yes, pass in 1.5% methane standard gas calibration, check if the range error is ≤±0.1%, if yes, the verification is successful; if not, the verification fails, and a device fault alarm is triggered.

[0070] The return airway cross section of this embodiment is A=12 m 2 , the average concentration of laser remote sensing is C=0.82%, the wind speed is V=2.3 m / s, and the turbulence coefficient k is 1.12, then:

[0071] Q=0.82%×2.3×12×1.12=0.253 m 3 / s=15.18 m 3 / min

[0072] In order to better illustrate the mine gas safety risk identification and evaluation process, taking the actual situation of a mine as an example, the specific steps are introduced:

[0073] Step 1: Data fusion and concentration field construction.

[0074] The mobile device reports the methane concentration of 0.95% to the system through UWB positioning; the application layer calls the Kriging interpolation algorithm, taking the fixed monitoring point as the reference point (weight 0.6) and the mobile point as the floating point (weight 0.4) to generate the full-mine concentration field grid (resolution 1 m×1 m);

[0075] Step 2: Dynamic risk factor extraction.

[0076] Concentration exceeding index C: the sensor on a coal mining face detects a value of ≥1.2% for 3 consecutive minutes (over-limit threshold 1.0%), calculate C=1.2;

[0077] Concentration change gradient ΔG: the concentration of the sensor on the heading face rises from 0.4% to 0.92% during t=14:05-14:10, then:

[0078] AG = (0.92-0.4) / 5 = 0.104% / min > 0.1% / min threshold -> trigger transient alarm;

[0079] High concentration aggregation risk A: DBSCAN algorithm scan finds 3 abnormal clusters (e = 10m, minPts = 3):

[0080] Cluster 1: coordinates (210.5, 87.3, -422.1) 5 points around the concentration > 1.1% -> A = 1.8 (A is the maximum, minimum or average of all abnormal clusters with concentration greater than the preset threshold of the surrounding points).

[0081] Emission flux E: return airway emission Q = 28.6m 3 / min (safety threshold 25m 3 / min) -> E = 1.14

[0082] Step 3: Risk value calculation and response.

[0083] The weight setting of this real-time fact (geological conditions of this mine area): a = 0.4, b = 0.3, g = 0.2, d = 0.1;

[0084] Risk value calculation:

[0085] Risk_Score = 0.4 x 1.2 + 0.3 x 1.04 + 0.2 x 1.8 + 0.1 x 1.14 = 1.326

[0086] Classification response:

[0087] Risk value 1.326 ∈ [1.2, 1.5], belongs to high risk level.

[0088] And trigger the following automatic execution: (1) start the local fan of coal mining face #203 to the maximum air volume; (2) send evacuation instructions (vibration + red light warning) to personnel portable terminal within a radius of 50m; (3) dispatch the nearest inspection robot to the abnormal point for review.

[0089] Step 4: Risk visualization and record.

[0090] The digital twin platform marks the high-risk area as an orange flashing polygon; automatically generates an event report: including risk source positioning map, disposal time axis, and operation record of responsible personnel.

[0091] In addition, it should be noted that various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, various possible combinations are not described again by the present application.

Claims

1. The intelligent mine gas monitoring system is characterized by: Includes perception layer, transport layer and application layer; The perception layer is used to collect gas data and environmental data; the perception layer includes fixed monitoring equipment, mobile inspection equipment and methane emission detection equipment; The fixed monitoring device includes a mining multi-parameter sensor, which is set at a fixed position; the fixed monitoring device includes a self-calibrating optical gas concentration detection sensor, which includes a self-calibrating methane concentration detection sensor, and the self-calibrating methane concentration detection sensor includes a reference gas chamber and a self-calibration module, wherein the reference gas chamber stores standard concentration methane gas and nitrogen standard gas; the self-calibration module is used to automatically introduce nitrogen standard gas to perform zero point calibration and introduce methane standard gas to perform range calibration according to a set period; The mobile inspection equipment is used to collect gas data and environmental data in the mine in real time according to the inspection route; The methane emission detection equipment is used to calculate the methane emission in the roadway based on the methane concentration and wind speed in the roadway; The transmission layer is used to transmit the data acquired by the perception layer to the application layer in or above the mine through a hybrid network architecture combining wired and wireless networks; The application layer is used to process the received data, including data storage management, intelligent analysis and early warning decision-making, visual human-computer interaction, control instruction issuance and system management, and the formation of mine gas monitoring reports; the visual human-computer interaction uses a digital twin mine model based on a GIS-based three-dimensional tunnel map to display the location of each sensor, the location of mobile inspection equipment, the methane concentration gradient map, and the data collected by each sensor in real time.

2. The intelligent mine gas monitoring system according to claim 1, characterized in that: The locations where the fixed monitoring equipment is set up include: the upper and lower corners of the coal mining face, the return air lane, the coal mining face, the head of the excavation face and the electromechanical chamber; the self-calibration process of the self-calibration methane concentration detection sensor is: start at a scheduled time every day, pass nitrogen standard gas for x seconds, check whether the zero point calibration passes, if passed, pass y methane standard gas for calibration, check whether the range error is ≤±0.1%, if so, the calibration is successful; if not, the calibration fails, and the equipment fault alarm is triggered, where x and y are both preset values.

3. The intelligent mine gas monitoring system according to claim 1, characterized in that: The mobile inspection equipment includes a portable detector carried by personnel, an inspection robot, a positioning module mounted on the inspection robot, a vehicle-mounted detector, a wireless transmission module, a path planning module, a temperature and humidity sensor, and a methane detection module. The path planning module dynamically generates a gas inspection route based on UWB positioning and a three-dimensional map of the roadway. The positioning module integrates UWB and inertial navigation data to achieve real-time positioning of the inspection robot. The methane detection module monitors the methane concentration in real time. The wireless transmission module supports multi-network adaptive switching and uploads positioning data, methane concentration and data detected by the on-board detector to the transmission layer.

4. The intelligent mine gas monitoring system according to claim 1, characterized in that: The methane emission detection equipment includes a laser methane telemeter and a wind speed sensor; the methane emission detection equipment calculates the methane emission Q of the roadway according to the following formula: Q=C×V×S×k Where C is the average methane concentration obtained by the laser methane telemeter, V is the wind speed measured by the wind speed sensor, S is the cross-sectional area of ​​the tunnel, and k is the turbulence correction coefficient.

5. The intelligent mine gas monitoring system according to claim 1, characterized in that: The transmission layer includes an above-ground network switch, multiple underground network switches, a protocol converter, a wireless router, a 4G / 5G base station for mining, an optical fiber transceiver and a repeater; the above-ground network switch and multiple underground network switches are used to build a wired backbone network, provide port connection and network management, and establish communication connections between the above-ground and underground areas; the protocol converter is used to connect different networks and realize protocol conversion; the different networks include wired to wireless, field bus to Ethernet; the wireless router is used to provide Wi-Fi coverage; the mining 4G / 5G base station is used to provide cellular network coverage and access; the optical fiber transceiver is used for the transmission of optical fiber links; the repeater is used to extend the transmission distance of wireless or wired signals.

6. The intelligent mine gas monitoring system according to claim 1, characterized in that: After the application layer receives the data collected by the sensor, it needs to preprocess the data. Specifically, the data needs to be filtered by sliding average to remove abnormal jump values.

7. The gas safety risk identification and assessment method based on the mine intelligent gas monitoring system according to claim 1 is characterized in that: The specific steps include: Step 1: Perform spatiotemporal alignment and data fusion in the digital twin mine model to generate the methane concentration field for the entire mine; Step 2: Dynamically extract risk factors, including: methane concentration exceedance index C, methane concentration change gradient ΔG, high concentration accumulation risk A, and emission flux E; Step 3: If the methane concentration exceeds the preset threshold, the DBSCA spatial clustering algorithm is used to automatically identify abnormal cluster areas; Step 4: Calculate the real-time risk value Risk_Score through the weighted scoring model: Risk_Score=α·C+β·ΔG+γ·A+δ·E Among them, α, β, γ and δ are weights; Step 5: Based on the risk value, determine the risk level, trigger corresponding response measures and automatically issue control instructions.

8. The gas safety risk identification and assessment method according to claim 7, characterized in that: The step 1 maps the precise positioning data of the mobile inspection equipment and the location of the fixed monitoring equipment to the same three-dimensional coordinate system, and generates the methane concentration field of the entire mine through the Kriging interpolation algorithm.

9. The gas safety risk identification and assessment method according to claim 7, characterized in that: The emission flux E is the ratio of the tunnel methane emission to the preset safety threshold.

10. The gas safety risk identification and assessment method according to claim 7, characterized in that: Set four intervals with increasing ranges. If the calculated risk value falls within the first interval, it is considered low risk. If the risk value falls within the second interval, it is considered medium risk and the inspection frequency of mobile inspection equipment is automatically increased. If the risk value falls into the third interval, it is considered high risk, the ventilation equipment corresponding to the risk source is started, personnel are notified to evacuate, and the nearest inspection equipment is dispatched to the abnormal point for re-examination via the shortest path; if the risk value falls into the fourth interval, it is considered critical, triggering a power outage in the entire area and the emergency broadcast system.

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