Shallow coal seam group coal spontaneous combustion monitoring early warning and pressure equalizing prevention and control system

Abstract

A shallow coal seam group coal spontaneous combustion monitoring early warning and pressure equalizing prevention and control system is provided with a safety monitoring unit, a safety situation early warning unit and a pressure equalizing prevention and control and intelligent scheduling unit, and the safety monitoring unit collects coal mine underground environment index gas concentration and ventilation parameters in real time; monitoring ground atmospheric pressure through an air pressure sensor, and integrating excavation parameters such as excavation working face advancing speed, coal seam thickness and interlayer spacing; the collected parameters are transmitted to a security situation early warning unit through a bus; the safety situation early warning unit establishes a three-area heat flow risk system database, integrates sensor monitoring parameters, and stores data into a ground server according to a coding standard; a deep learning algorithm is combined with a heat flow risk early warning evaluation index system and model to realize risk level dynamic evaluation and alarm; and the voltage-sharing prevention and control and intelligent scheduling unit generates a control strategy according to the early warning level, and remotely controls the ventilation equipment in a linkage manner. According to the utility model, three-area heat flow risk intelligent advanced management and control are realized, and the safety level of a coal mine is improved.

Description

TECHNICAL FIELD

[0001] The utility model relates to a shallow coal seam group coal spontaneous combustion monitoring early warning and equalizing pressure prevention and control system belongs to coal mine safety technical field. BACKGROUND

[0002] Under the influence of multiple strong mining, the goaf, adjacent goaf and overlying goaf of shallow buried close coal seam group are easy to collapse and connect, forming a connected gas leakage channel between the ground, goaf and working face. A large amount of surface gas enters the mined coal rock mass through ground cracks, and the coal-oxygen reaction generates heat and oxidation derivative gas, and low-concentration oxygen transregional overflows to the goaf area of the coal seam with low negative pressure, and finally rushes into the working face, forming the so-called "three-zone" multi-element gas (N2-CO2-CO-O2-CH4) panting-overflow-oxidation heating effect, causing "three-zone" heat-flow disasters such as coal rock mass spontaneous combustion, working face low oxygen and CO overlimit.

[0003] At present, most coal mines adopt equalizing pressure ventilation to control the amount of fissure air leakage, which plays a role in preventing "three-zone" heat-flow disasters to a certain extent, but the existing equalizing pressure ventilation has insufficient intelligence, and there are serious deficiencies in "three-zone" heat-flow risk monitoring and early warning, resulting in inaccurate identification of "three-zone" heat-flow risk and untimely early warning and control, which seriously restricts the safety of shallow buried spontaneous combustion coal seam group mining. SUMMARY

[0004] The utility model discloses a shallow coal seam group coal spontaneous combustion monitoring early warning and equalizing pressure prevention and control system, which can realize intelligent advanced control of heat-flow risk in the three areas of ground, goaf and working face, and ensure the safety of coal mine production.

[0005] In order to realize the above-mentioned purpose, the utility model provides a shallow coal seam group coal spontaneous combustion monitoring early warning and equalizing pressure prevention and control system, which comprises a sensor, an exchange, an analysis host, a ventilation equipment, an industrial ring network, a server and a client, wherein the sensor, the exchange, the analysis host and the ventilation equipment are arranged in the coal mine underground, the industrial ring network, the server and the client are located in the coal mine above ground, and the server is provided with a safety monitoring unit, a safety situation early warning unit and an equalizing pressure prevention and control and intelligent scheduling unit.

[0006] The safety monitoring unit collects the index gas concentration and ventilation parameters of the coal mine underground environment in real time through the sensor, monitors the ground atmospheric pressure through the air pressure sensor, and integrates the mining working face advancing speed, coal seam thickness and interlayer spacing mining parameters, and the safety monitoring unit transmits the collected parameters to the safety situation early warning unit through the bus.

[0007] The safety situation early warning unit is used for establishing a ground-gob-mining face three-area heat-flow risk system database, integrating three-area sensor monitoring parameters, and storing data into an uphole server according to a unified coding standard; a deep learning algorithm based on an AI neural network is combined with a three-area heat-flow risk early warning evaluation index system and model to realize dynamic evaluation of a risk level and voice early warning;

[0008] The uniform pressure prevention and control and intelligent scheduling unit automatically generates a control strategy according to an early warning level, remotely links and controls a ventilation device, and performs prior adjustment and emergency processing;

[0009] The analysis host is used for storing data fed back by the analysis host and the client;

[0010] The exchanger is used for connecting a downhole and an uphole and realizing information transmission through an industrial ring network;

[0011] The client is a man-machine interactive interface and is used for adjusting early warning and control parameters of each system in the server.

[0012] Further, the sensor includes a multi-parameter sensor, an air volume sensor and a differential pressure sensor; real-time collected coal mine downhole environment index gases include O2, CO, CO2, CH4, C2H4, C2H2 and C2H6; ventilation parameters include air speed, differential pressure and air pressure; three-area sensor monitoring parameters integrated by the safety situation early warning unit include ventilation fan operation condition information, O2 concentration, CO concentration, CH4 concentration, C2H4 concentration, C2H2 concentration, C2H6 concentration, temperature and humidity, air speed, differential pressure and air pressure environment parameters; the ventilation device includes a fan, a wind pipe and a damper / window; and the industrial ring network is a wireless WIFI or 5G network.

[0013] Further, a fan, a wind pipe and an air volume sensor one are arranged in an air inlet roadway; a damper / window is arranged in an air return roadway for adjusting a working face air pressure; an air volume sensor two is arranged in the air return roadway, a differential pressure sensor is arranged outside the damper of the air return roadway, one end of the differential pressure sensor is arranged inside two airtight walls of the air return roadway, and the other end of the differential pressure sensor is arranged in a protective pipe communicated with a deep part of a composite gob; a mine intrinsic safety type multi-parameter sensor is arranged at an air return corner; a CO sensor and a methane sensor are arranged in the air return roadway.

[0014] The utility model discloses a safety monitoring unit, safety situation early warning unit, equalizing prevention and control and intelligent scheduling unit are set up in the server, and the safety monitoring unit is through the sensor real -time collection coal mine downhole environment's index gas concentration and ventilation parameter, through barometric pressure sensor monitoring ground atmospheric pressure, and integrated mining working face advancing speed, coal seam thickness, interlayer spacing mining parameter, and the safety monitoring unit will gather the parameter through bus data transmission to safety situation early warning unit, and safety situation early warning unit is used to establish ground -gob -working face three area's heat -flow risk system database, and integrates three area sensor monitoring parameter, and according to unified coding standard, data is stored in the server on the well, and the deep learning algorithm based on AI neural network combines three area heat -flow risk early warning evaluation index system and model, realizes the dynamic evaluation of risk level, and carries out voice early warning, and equalizing prevention and control and intelligent scheduling unit automatically generates control strategy according to early warning level, remote linkage control ventilation equipment, carries out beforehand adjustment emergency handling. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 It is the system structure schematic diagram of the utility model;

[0016] Figure 2 It is the working flow chart of equalizing prevention and control and intelligent scheduling unit of the utility model.

[0017] In the drawing: 1, barometric pressure sensor, 2, multi-parameter sensor, 3, differential pressure sensor, 4, fan, 5, air duct, 6, air door / window, 7, CO sensor, 8, air volume sensor one, 9, air volume sensor two, 10, methane sensor, 11, beam tube monitoring equipment. DETAILED DESCRIPTION

[0018] The utility model will be further described below in connection with the drawings.

[0019] As Figure 1 Indicated, a kind of shallow coal seam group coal spontaneous combustion monitoring and early warning and equalizing prevention and control system, including sensor, switch, analysis host, ventilation equipment, industrial ring network, server and client;Wherein, sensor, switch, analysis host, ventilation equipment are all set in coal mine downhole;Industrial ring network, server and client are all located in coal mine on the well;The server is equipped with safety monitoring unit, safety situation early warning unit, equalizing prevention and control and intelligent scheduling unit;

[0020] The safety monitoring unit collects the index gas concentration and ventilation parameters of the underground environment of the coal mine in real time through sensors; monitors the atmospheric pressure on the ground through the air pressure sensor 1, and integrates the mining parameters of the advancing speed of the mining working face, the thickness of the coal seam, and the interlayer spacing; the safety monitoring unit transmits the collected parameters to the safety situation early warning unit through the bus;

[0021] The safety situation early warning unit is used to establish a ground-gob-working face three-zone heat-flow risk system database, integrate three-zone sensor monitoring parameters, and store data into the surface server according to a unified coding standard; based on the deep learning algorithm of AI neural network, combined with the three-zone heat-flow risk early warning evaluation index system and model, the dynamic evaluation of the risk level is realized, and the voice early warning is carried out;

[0022] The pressure equalization prevention and control and intelligent scheduling unit automatically generates a control strategy according to the early warning level, remotely links and controls the ventilation equipment, and adjusts the emergency treatment in advance;

[0023] The analysis host is used to store the data fed back by the analysis host and the client;

[0024] The exchanger is used to connect the underground and the surface, and realizes information transmission through the industrial ring network;

[0025] The client is a man-machine interactive interface, which is used to adjust the early warning control parameters of each system in the server.

[0026] Further, the sensor includes a multi-parameter sensor 2, an air volume sensor, and a differential pressure sensor 3; the real-time collected index gas of the underground environment of the coal mine includes O2, CO, CO2, CH4, C2H4, C2H2, and C2H6; the ventilation parameters include wind speed, pressure difference, and air pressure; the three-zone sensor monitoring parameters integrated by the safety situation early warning unit include ventilation fan operating condition information, O2 concentration, CO concentration, CH4 concentration, C2H4 concentration, C2H2 concentration, C2H6 concentration, temperature and humidity, wind speed, pressure difference, and air pressure environment parameters; the ventilation equipment includes a fan 4, a wind pipe 5, and a damper / window 6; and the industrial ring network is a wireless WIFI or 5G network.

[0027] As a preferred embodiment, the fan 4, the air duct 5 and the air volume sensor 8 are arranged in the air inlet lane; the fan 4 is the air supply source of the pressure equalization control and intelligent scheduling unit, and the air supply amount is controlled by adjusting the power; the air door / window 6 is arranged in the air return lane to adjust the air pressure of the working face, the air leakage amount is reduced by changing the pressure difference between the goaf and the working face, and parameters are provided for the pressure equalization control; the air volume sensor 8 measures the air inlet amount, and provides parameters for the pressure equalization control and intelligent scheduling unit; the air volume sensor 9 is arranged in the air return lane to measure the air return amount, and the difference between the air return amount and the air inlet amount is the air leakage amount; the differential pressure sensor 3 is arranged outside the air door of the air return lane, one end of the differential pressure sensor 3 is arranged at a position 10 m inside the two closed walls of the air return lane, and the other end is arranged in the protection pipe connected with the deep part of the composite goaf; the differential pressure sensor 3 measures the pressure difference between the air return lane and the deep part of the composite goaf, and controls the pressure difference to be between 30 Pa and 120 Pa; the mine intrinsic safety multi-parameter sensor 2 is arranged at the air return corner to monitor CO, CH4, O2, C2H4, C2H6 and C2H2; the CO sensor 7 is installed in the air return lane, and the CO alarm concentration is 2.4×10 -6 ; the methane sensor 10 is arranged in the air return lane to monitor the CH4 concentration. When the methane concentration in the working face and the air return flow is not less than 0.5%, the methane sensor 10 alarms, and when the methane concentration is not less than 1.5%, the methane sensor 10 is powered off immediately.

[0028] The beam tube monitoring device 11 is laid in the goaf to observe the application effect of the intelligent pressure equalization ventilation technology, monitor the ignition degree of the coal spontaneous combustion in the goaf after pressure regulation, and detect the ignition signs of the coal spontaneous combustion in the composite goaf when the air leakage amount from the working face to the composite goaf is excessive due to the excessively high pressure of the working face.

[0029] The mine pressure equalization ventilation system is equipped with double power supply and double fans, one for use and one for standby, which can ensure the stable and reliable operation of the system within a reasonable range. When the gas sensor data is higher than the locking value, the system main control switch outputs a control signal to control the power feeding switch, realizing the functions of gas electrical locking and air electrical locking. The mine intelligent local ventilation system is connected with the sound and light alarm device to prompt the staff to take corresponding measures to solve the abnormal situation.

[0030] The fan is equipped with a mine explosion-proof and intrinsic safety lithium ion storage battery, which is automatically charged under normal circumstances. When the system is abnormally powered off due to CH4 and CO, the fan automatically starts the lithium ion storage battery to run normally, ensuring the normal ventilation of the working face.

[0031] A control method of a shallow coal seam group coal spontaneous combustion monitoring and early warning and pressure equalization control system, comprising the following steps:

[0032] S1, the safety monitoring unit collects the index gas concentration and ventilation parameters of the underground environment of the coal mine in real time through the mine intrinsically safe wireless sensor, monitors the ground atmospheric pressure through the air pressure sensor 1, and integrates the mining working face advancing speed, coal seam thickness, interlayer spacing mining parameters, and transmits the collected parameters to the safety situation early warning unit through the bus;

[0033] S2, the safety situation early warning unit processes the received data through a multi-element heterogeneous data fusion model, and the specific process is as follows:

[0034] S2.1, the Hampel filter is used to detect and eliminate abnormal values in the data, the median and absolute deviation are used to measure the dispersion degree of the data, so as to judge which data is abnormal value, and then replace the abnormal value with reasonable value. The formula of Hampel filter is as follows:

[0035]

[0036] In the formula, x i is the i-th observation value in the original data, y i is the i-th observation value after filtering, m i is the median of the data in the window centered on x i , and s i is the median of the absolute deviation of the data in the window centered on x i , that is:

[0037] s i =c·median(∣x j -m i ∣)

[0038] j=i-(n-1) / 2,…,i++(n-1) / 2;

[0039] In the formula, n is the window size, c is a constant, and f is a threshold parameter for controlling the sensitivity of abnormal value detection; in this model, c=1.4826 and f=3. The Hampel filter can effectively detect and eliminate spike noise and impulse noise in the data, and maintain the smoothness and shape characteristics of the data.

[0040] S2.2, the Lagrange interpolation method is used to fill in the missing values. For given k+1 points (x0,y0),…,(x k ,y k ), find a polynomial L(x) of degree not more than k, such that L(x i )=y i for all i=0,…,k. The expressions of Lagrange polynomial and basic polynomial are respectively:

[0041]

[0042] At the point x j = 1, and at other points x i = 0, i.e. i≠j;

[0043] S3, the security situation early warning unit adopts a time series prediction algorithm to predict the sensor monitoring parameters in advance, and the specific process is as follows:

[0044] S3.1, the time series prediction algorithm model includes an encoder and a decoder, the input of the encoder is the past time covariate sequence x 1:t-1 = {x1, x2, x3, … x t-1} and the target variable sequence y 1:t-1 = {y1, y2, y3, … y t-1}, where t refers to the time when the prediction starts; the input of the decoder is the future time covariate sequence x t:T = {x t , x t++1 , x t0+2 , … x T}, where T refers to the cutoff time of the prediction; the output of the model is the future time target variable sequence y t:T = {y t , y t++1 , y t++2 , … y T};

[0045] S3.2, the encoder is stacked by N identical layers, each layer contains a multi-head self-attention sublayer and a feedforward neural network sublayer; the output of the multi-head attention sublayer of the Ith layer in the encoder is:

[0046]

[0047] In the formula, W Q , W K and W V are learnable parameter matrices for mapping the vector of each position in the input sequence to Q, K, V, W O is used to splice the output sub-vectors of multiple heads to obtain a complete output vector;

[0048] The feedforward neural network sublayer is used to perform nonlinear transformation on the representation of each position to increase the expression ability of the model. The output of the feedforward neural network sublayer of the Ith layer in the encoder is:

[0049] FFN(x) = max(0, xW1 + b1)W2 + b2;

[0050] where max(0, ) is a ReLU activation function; W1, W2 are learnable parameter matrices; b1, b2 are learnable bias vectors;

[0051] S3.3, the decoder is used to predict the next target sequence according to the output of the encoder and the generated target sequence, the decoder is stacked by N identical layers, each layer contains a multi-head self-attention sublayer, an encoder-decoder attention sublayer and a feedforward neural network sublayer; the multi-head self-attention sublayer of the decoder uses a mask to cover the ungenerated positions, and the calculation formula of the self-attention with the mask is:

[0052]

[0053] The output of the multi-head self-attention sublayer of the Ith layer in the decoder is:

[0054]

[0055] The function of the encoder-decoder attention sublayer is to calculate the correlation between each position in the generated target sequence and each position in the encoder output. The function of the feedforward neural network sublayer in the decoder is the same as that in the encoder.

[0056] S4, the security situation early warning unit sets a hierarchical warning level, according to the importance of the index and the overrun degree of the monitoring data, the warning information is divided into four levels from low to high according to the emergency degree, and the real-time monitoring data is automatically alarmed; the specific process is:

[0057] S4.1, according to the experimental analysis of constant temperature and constant temperature small air volume and variable air volume conditions, the consumption of oxygen by carbon monoxide and carbon dioxide generated by coal oxidation, it is verified that the large amount of carbon monoxide gas is related to the non-linear relationship of coal temperature, and carbon monoxide and oxygen are selected as coal spontaneous combustion early warning indexes;

[0058] S4.2, through the analysis of pyrolysis gas, the corresponding relationship between C2H4 and C2H2 / C2H6 and coal temperature is determined, C2H4, C2H6 and C2H2 are selected as coal spontaneous combustion early warning indexes; six coal spontaneous combustion early warning indexes are selected as CO, O2, CH4, C2H4, C2H6 and C2H2;

[0059] S4.3, combined with the requirements of coal mine safety regulations for CO, CH4 and O2 concentration of dangerous gas in working face, according to the risk coupling mechanism of three zones, the warning levels are set:

[0060] According to the coal spontaneous combustion experiment test and on-site observation, under normal circumstances the CO concentration should be lower than 24ppm. If it exceeds 24ppm, a blue warning will be issued, and the temperature range at this time is 40-60℃; according to the laboratory programmed heating experiment, the temperatures at which C2H4 and C2H6 first appear are both in the range of 70-80℃, and this temperature range is defined as a yellow warning; when the temperature reaches 100-130℃, it is an orange warning, and the concentrations of CO, C2H4 and C2H6 increase significantly, with the CO concentration reaching 500ppm and the C2H4 concentration reaching 2ppm. According to statistics on spontaneous combustion accidents in goafs, the C2H6 concentration generally reaches about 3 times that of C2H4; when the coal temperature reaches 150-180℃, C2H2 will appear, and the CO concentration will increase significantly, which serves as the basis for determining a red warning.

[0061] The corresponding three-zone heat-flow risk warning levels and warning values ​​are as follows:

[0062] Blue alert: T m >40℃; R1={{24ppm<[CO]}∪{0.5%<[CH4]}∪{20%>[O2]}}

[0063] Yellow alert: T m >60℃; R2={{50ppm<[CO]}∩{{[C2H4]>0}∪{[C2H6]>0}}}

[0064] Orange alert: T m >90℃; R3={{500ppm<[CO]}∪{[C2H4]>2ppm}}

[0065] Red Alert: T m >130℃ ； R4={[C2H2]>0};

[0066] S5, the pressure-equalizing control and intelligent dispatching unit automatically provides control strategies according to the system alarm level, realizes one-button start and stop and power adjustment of the pressure-equalizing ventilation equipment, automatically adjusts the operating power according to the monitoring data, and changes the air volume and pressure of the working surface; Figure 2 As shown, the specific process is as follows: S5.1, pressure equalization control Adjust the dampers and fan facilities in the ventilation system according to the specific situation to maintain the wind pressure balance in the goaf, reduce air leakage in the goaf, prevent fresh air from entering the spontaneous combustion area or the goaf, cut off the oxygen supply to the fire source, and achieve suffocation and inerting. Therefore, the purpose of pressure equalization ventilation is to control the air leakage source. According to the ventilation resistance law:

[0067] Δh=RQ e ;

[0068] Wherein, Ah is the pressure difference of the air leakage passage, unit Pa; R is the air resistance of the air leakage passage, unit N·s 2 / m 8 ; Q is the air leakage flow, unit m 3 / s; k is the index of the air leakage flow state, k = 1 ~ 2; here e takes 2;

[0069] That is:

[0070]

[0071] S5.2, real-time monitoring data and prediction data are transmitted to a security situation early warning system, the system issues an early warning according to an early warning threshold, and a pressure regulation and control system automatically adjusts the power of the fan according to the early warning level to reduce the concentration of CO and CH4 dangerous gases in the working face and return air flow, so as to ensure that the O2 content of the working face meets the standard, while the air door and air window are linked to control the pressure difference between 30 Pa and 120 Pa, to reduce the air leakage amount of the three zones and prevent fire, specifically:

[0072] The blue early warning coal is in the oxidation and heating stage, starts to produce CO gas, accompanied by CH4, which reduces the oxygen content of the working face, at this time, the fan power is adjusted to increase the air volume, the CO and CH4 concentrations of the working face are reduced, and the oxygen content of the working face is ensured to meet the standard, while the air door and air window are adjusted to reduce the control pressure difference to less than 50 Pa; thereby reducing the air leakage amount of the three zones so that the residual coal in the goaf stops the oxidation and heating reaction due to lack of oxygen.

[0073] The yellow early warning coal is in the self-heating stage, the oxidation is further intensified, the oxygen consumption rate increases, and the production amount of reaction products CO and CO2 starts to increase, the production amount of CO is increased by more than 3 times compared with the previous stage, and coal spontaneous combustion marker gases C2H4 and C2H6 start to appear, at this time, the pressure difference should be adjusted to less than 20 Pa to prevent coal spontaneous combustion by controlling the air leakage amount under the condition that the dangerous gas of the working face does not exceed the limit and the oxygen content meets the standard;

[0074] The orange early warning coal is in the fission stage, at this time, the concentrations of CO, C2H4 and C2H6 increase significantly, the CO concentration reaches 500 ppm, and the C2H4 concentration reaches 2 ppm, at this time, the air door and air window are adjusted to make the pressure difference close to 0; the air leakage amount of the three zones is inhibited to make the coal spontaneous combustion in the goaf lack of oxygen and suffocate.

[0075] The red early warning coal is in the combustion stage, and coal spontaneous combustion marker gas C2H2 appears, at this time, it is necessary to jointly implement fire extinguishing with the coal mine fire prevention department.

Claims

1. A shallow seam group coal spontaneous combustion monitoring and early warning and pressure equalization prevention and control system, comprising a sensor, a switch, an analysis host, a ventilation device, an industrial ring network, a server and a client; wherein, The sensor, the switch, the analysis host, and the ventilation equipment are arranged in the coal mine underground; the industrial ring network, the server, and the client are located in the coal mine upper; characterized in that, the server is internally provided with a safety monitoring unit, a safety situation early warning unit, and a uniform pressure prevention and control and intelligent scheduling unit; The safety monitoring unit collects the index gas concentration and ventilation parameters of the coal mine underground environment in real time through the sensor; the atmospheric pressure is monitored through the air pressure sensor (1), and the mining parameters such as the advancing speed of the mining face, the coal seam thickness, and the layer spacing are integrated; the safety monitoring unit transmits the collected parameters to the safety situation early warning unit through the bus; The safety situation early warning unit is used for establishing a ground-mining area-working face three-area heat-flow risk system database, integrating the three-area sensor monitoring parameters, and storing the data into the upper server according to the unified coding standard; based on the deep learning algorithm of the AI neural network, the three-area heat-flow risk early warning evaluation index system and model are combined to realize the dynamic evaluation of the risk level and the voice early warning; The uniform pressure prevention and control and intelligent scheduling unit automatically generates a control strategy according to the early warning level, remotely links and controls the ventilation equipment, and adjusts the emergency treatment in advance; The analysis host is used for storing the data fed back by the analysis host and the client; The switch is used for connecting the underground and the upper, and realizing the information transmission through the industrial ring network; The client is a man-machine interactive interface, which is used for adjusting the early warning control parameters of each system in the server.

2. The shallow seam group coal spontaneous combustion monitoring and early warning and pressure equalization prevention and control system according to claim 1, characterized in that, The sensor includes a multi-parameter sensor (2), an air volume sensor, and a differential pressure sensor (3); the real-time collected index gases of the coal mine underground environment include O2, CO, CH4, C2H4, C2H2, and C2H6; the ventilation parameters include the air speed, the differential pressure, and the air pressure; the three-area sensor monitoring parameters integrated by the safety situation early warning unit include the operating condition information of the ventilator (4), the O2 concentration, the CO concentration, the CH4 concentration, the C2H4 concentration, the C2H2 concentration, the C2H6 concentration, the temperature and humidity, the air speed, the differential pressure, and the air pressure environment parameters; the ventilation equipment includes the fan (4), the air duct (5), and the air door / window (6); and the industrial ring network is a wireless WIFI or 5G network.

3. The shallow seam group coal spontaneous combustion monitoring and early warning and pressure equalization prevention and control system according to claim 2, characterized in that, The fan (4), the air duct (5), and the air volume sensor one (8) are arranged in the air inlet lane; the air door / window (6) is arranged in the air return lane for adjusting the air pressure of the working face; the air volume sensor two (9) is arranged in the air return lane, the differential pressure sensor (3) is arranged outside the air door of the air return lane, one end of the differential pressure sensor (3) is arranged inside the two closed walls of the air return lane, and the other end is arranged in the protection pipe connected with the deep part of the composite goaf; the mine intrinsic safety multi-parameter sensor (2) is arranged at the air return corner; the CO sensor (7) and the methane sensor (10) are arranged in the air return lane.

Images