A mine intelligent pressure-equalizing ventilation fire prevention and extinguishing method and device

Abstract

The present invention provides a method and device for intelligent pressure-equalizing ventilation and fire prevention in mines, the method comprising: collecting and analyzing ventilation environment parameters, establishing a coal mine ventilation model, planning the location of hardware equipment, establishing a three-dimensional ventilation tunnel model, and adjusting the location of hardware equipment; connecting the control box and base station of the hardware equipment to the industrial ring network; deploying a host computer server, building an intelligent pressure-equalizing control platform, and realizing wind pressure control by controlling the size of the fan frequency and the size of the wind window opening; building a cloud computing intelligent brain analysis platform, optimizing the coal mine ventilation model, establishing a coal mine ventilation data model, setting an early warning threshold, and establishing an early warning data model. The present invention realizes a three-dimensional integrated display of the mine ventilation tunnel diagram through the constructed mine ventilation model, realizes a dynamic model of the mine ventilation condition and wind pressure change according to the adjustment parameters, and at the same time, the set early warning model can realize the early warning of abnormal underground ventilation conditions, timely discover related problems, and eliminate safety hazards.

Description

Technical Field

[0001] The present invention relates to the field of underground safety technology, and in particular to a mine intelligent pressure-equalizing ventilation fire prevention and extinguishing method and device. Background Art

[0002] Some coal mines adopt comprehensive mechanized top coal caving mining. During the mining of the working face, due to the deep burial of coal seams and the large mining height, the goaf collapses and forms an air leakage channel with the surface, which is easy to cause the hidden danger of spontaneous combustion of coal seams in the goaf, seriously affecting the safe production of the working face. The existing traditional solution relies entirely on manual operation inspection and manual adjustment of the ventilation of the working face. When a fault occurs, it is impossible to notify the ground personnel in time, resulting in problems such as high labor consumption, low efficiency, low precision, and frequent pressure adjustment.

[0003] Chinese Patent Name: A Mine Ventilation Intelligent Monitoring and Adjustment Device, Patent Number: CN201320742150.0, provides a technical solution for a mine ventilation intelligent monitoring and adjustment device that can accurately measure ventilation shaft air volume and pressure and a variety of mine air quality parameters, upload data, and support remote inverter control parameter setting. However, it lacks a data processing module and cannot adjust and optimize itself, so it has a low degree of intelligence. In addition, the above device ignores the influence of the tunnel's own factors and has low measurement accuracy.

[0004] The name of the Chinese utility model patent is: A mine ventilation pressure equalization fire prevention and extinguishing system experimental device, patent number: CN201720497913.8. The automatic pressure equalization control system can dynamically monitor and control the leakage air pressure difference, automatically balance the air pressure at both ends of the leakage channel, and solve the problems of manual pressure equalization, but the degree of intelligence and integration is low. Summary of the invention

[0005] In view of the above problems, the present invention provides a method and device for intelligent pressure-equalizing ventilation and fire prevention in mines, which aims at the complexity of spontaneous combustion and fire prevention in goafs by combining high-precision wind pressure and wind speed sensors, remote intelligent pressure-regulating dampers and other underground equipment through automatic data collection and cloud computing intelligent analysis to realize accurate measurement, real-time collection, intelligent analysis and remote intelligent control of ventilation environment data of working faces and goafs, timely adjustment of ventilation conditions of working faces and avoidance of air leakage in goafs, and achieves the purpose of intelligent pressure-equalizing ventilation and fire prevention in goafs.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A mine intelligent pressure-equalizing ventilation fire prevention and extinguishing method comprises the following steps:

[0008] S0, collecting the ventilation environment parameters of the tunnel (tunnel length, tunnel width, tunnel section, wind speed, wind pressure, temperature, humidity) and calculating the wind resistance and friction coefficient of the tunnel according to the resistance law, wind volume balance law, and energy balance law, and classifying and summarizing the characteristic data of the coal mine tunnel (support type, surface roughness, tunnel air intake or return air) and entering them into the MySQL database to establish the ventilation parameter model of the coal mine ventilation tunnel;

[0009] S1. Plan the location of hardware equipment through the ventilation model, establish a three-dimensional ventilation tunnel model, and adjust the location of hardware equipment through the three-dimensional ventilation tunnel model;

[0010] S2, connect the control box and base station of the hardware equipment to the industrial ring network of the coal mine;

[0011] S3, deploy the host computer server for remote control of hardware equipment, building and debugging software platforms, storing data, generating Shape map files and data interaction;

[0012] S4. Build an intelligent pressure-equalizing control platform in the host computer to control the wind pressure by controlling the fan frequency and the wind window opening;

[0013] S5. Build a cloud computing intelligent brain analysis platform in the host computer to optimize the coal mine ventilation model. Combine the collected information (tunnel length, tunnel width, tunnel section, wind speed, wind pressure, temperature, humidity), build a data warehouse through Redis cache, properties configuration files and MySQL data to establish a coal mine ventilation data model, and enter it into the cloud computing intelligent brain analysis platform;

[0014] S6. Set the warning threshold and establish a warning data model. When the threshold is exceeded, the system will automatically issue an alarm.

[0015] Preferably, the ventilation environment parameters in step S0 include: pressure, wind speed, temperature, and humidity; the specific method for obtaining the wind speed data is:

[0016] Get the total pressure P of the lane 全 and the static pressure P of the roadway 静 , the wind speed data of the monitoring point is calculated by the following formula:

[0017] P 全 =P 静 +P 动

[0018] ρ=0.00345×P 静 ×(273.15+t)

[0019]

[0020] Among them, P 动 is the dynamic pressure of the tunnel, ρ is the air density of the tunnel, t is the Celsius temperature of the monitoring point, and V is the wind speed data of the monitoring point.

[0021] The method for calculating the wind speed data also includes:

[0022] The time for the ultrasonic wave to travel from probe A to probe B is t1, and the time for the ultrasonic wave to travel from probe B to probe A is t2. The distance between the two probes is L, the propagation speed of the ultrasonic wave in the air is V0, the wind speed in the tunnel is V, and the wind speed in the tunnel is V1, the component wind speed of the two probes. The specific calculation formula is:

[0023]

[0024] V=kV1

[0025] Among them, k is the adjustment coefficient calculated based on the direct distance between the two probes and the component distance in wind speed;

[0026] tanα=W÷L

[0027] cosα=V1÷V

[0028] V=V1÷cosα

[0029]

[0030] Where W is the distance between the two transducer probes in the direction perpendicular to the roadway wind flow, L is the distance between the two transducer probes, and α is the angle between the two transducer probes and the roadway wind volume direction.

[0031] Furthermore, step S2 connects the hardware equipment to the industrial ring network of the coal mine, specifically: the control box and base station of the hardware equipment convert the electrical signal into AB differential signal through the RS485 module, the differential signal is converted into a network signal through the RS485 network port module, and the network signal enters the industrial ring network of the coal mine through the switch or is converted into an electrical signal through an optoelectronic switch and then connected to the industrial ring network of the coal mine through optical fiber.

[0032] Preferably, in step S4, the intelligent pressure equalization control platform realizes wind pressure control by controlling the size of the fan frequency and the size of the wind window opening, which is specifically manifested as follows:

[0033] Reducing wind pressure specifically includes: reducing the frequency of local fans or increasing the opening of the dampers to ensure the wind volume at the working face while reducing the wind pressure in the goaf to ensure equal pressure with the ground;

[0034] Increasing wind pressure specifically includes: increasing the frequency of local fans and adjusting the damper opening to ensure the air volume at the working face while increasing the wind pressure in the goaf to ensure equal pressure with the ground.

[0035] Preferably, the cloud computing intelligent brain analysis platform in step S5 realizes self-learning and continuous optimization of the model through daily real-time collected data.

[0036] A mine intelligent pressure-equalizing ventilation fire prevention and extinguishing device, comprising:

[0037] The control module, including the host computer server and the control box and base station of the hardware equipment, is used to control the opening of the underground pressure regulating damper and the speed of the local fan, process and store data, generate Shape map files, and build and debug the software platform;

[0038] The data acquisition module includes a high-precision pressure gauge, anemometer, thermometer and humidity meter, ultrasonic probe, and high-precision wind speed sensor, which are used to collect tunnel information, including pressure, wind speed, temperature, and humidity;

[0039] A signal processing module, including a ring network switch and an optical fiber switch, is used to convert electrical signals into differential signals, convert differential signals into network signals, and convert network signals into electrical signals;

[0040] Communication module, used for signal transmission between control module, data acquisition module, signal processing module, hardware equipment, early warning module and user terminal;

[0041] Hardware equipment, including windows, doors, and fans, for ventilation;

[0042] Early warning module: when the set early warning threshold is exceeded, the early warning module will automatically alarm;

[0043] User terminal, the medium for human-computer interaction.

[0044] The beneficial effects of this application are:

[0045] The constructed mine ventilation model is converted into a json data file based on the original 3DMax model, and the mine ventilation tunnel is realized on the browser side through WebGL and WebGIS. Figure 3 It can display the operation data and environmental parameter data of underground equipment in an integrated manner, and store them in Redis cache and MySQL database for historical data recording through data communication protocols such as TCP / HTTP, opc and Modbus. It can also conduct statistical analysis on the recorded operation data, and make comparison and adjustment based on historical parameters and current operation parameters to realize dynamic simulation of mine ventilation conditions and wind pressure changes and prediction of wind pressure change trends. At the same time, the early warning model that is set up can realize early warning statistical analysis of abnormal underground ventilation conditions, timely discover related problems, conduct inspections and check to eliminate safety hazards.

[0046] The upper computer system platform will realize intelligent pressure-equalizing ventilation and fire prevention in the goaf around the working face by automatically remotely controlling the pressure-regulating wind windows and variable frequency fans in the mine based on the real-time collected data and previous model data analysis.

[0047] The intelligent pressure-equalizing ventilation and fire-fighting device solves the problems of the traditional pressure-equalizing process, which is completely dependent on manual operation, has low precision, and frequent pressure adjustment. It achieves the purpose of intelligent pressure-equalizing ventilation and fire-fighting with precise measurement, real-time collection, intelligent analysis, and remote control, and realizes unmanned, automated, and intelligent effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flow chart of a mine intelligent pressure-equalizing ventilation fire prevention and extinguishing method of the present invention;

[0049] Figure 2 A schematic diagram of the structure of an intelligent pressure-equalizing ventilation and fire-fighting device for a mine according to the present invention;

[0050] Figure 3 A schematic diagram of a signal flow in one embodiment of the present invention;

[0051] Figure 4 Schematic diagram of the service architecture of the system of the present invention;

[0052] Figure 5 A schematic diagram of the working principle of the device in one embodiment of the present invention;

[0053] Figure 6 It is a data table for coal mine application data collection and analysis of the present invention;

[0054] Figure 7 This is a data table for analyzing the air volume data of the auxiliary chute of the present invention. DETAILED DESCRIPTION

[0055] The present invention is further described below in conjunction with the accompanying drawings and embodiments: In order to clearly illustrate the technical features of this solution, the present invention is described in detail below through specific implementation methods and in conjunction with its accompanying drawings. The disclosure below provides many different embodiments or examples for realizing different structures of the present invention. In order to simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the accompanying drawings are not necessarily drawn to scale. The present invention omits the description of known components and processing techniques and processes to avoid unnecessary limitations on the present invention.

[0056] The present invention provides a method and device for intelligent pressure-equalizing ventilation and fire prevention in mines. In view of the complexity of spontaneous combustion and fire prevention in goafs, high-precision wind pressure and wind speed sensors, remote intelligent pressure-regulating dampers and other underground equipment are combined to automatically collect data through cloud computing and intelligent analysis to achieve accurate measurement, real-time collection, intelligent analysis, and remote intelligent control of the ventilation environment data of the working face and goaf, so as to timely adjust the ventilation conditions of the working face and avoid air leakage in the goaf, thereby achieving the purpose of intelligent pressure-equalizing ventilation and fire prevention in the goaf.

[0057] like Figure 1 As shown, the method includes:

[0058] S0, collecting the ventilation environment parameters of the tunnel (tunnel length, tunnel width, tunnel section, wind speed, wind pressure, temperature, humidity) and calculating the wind resistance and friction coefficient of the tunnel according to the resistance law, wind volume balance law, and energy balance law, and classifying and summarizing the characteristic data of the coal mine tunnel (support type, surface roughness, tunnel air intake or return air) and entering them into the MySQL database to establish the ventilation parameter model of the coal mine ventilation tunnel;

[0059] S1. Plan the location of hardware equipment through the ventilation model, establish a three-dimensional ventilation tunnel model, and adjust the location of hardware equipment through the three-dimensional ventilation tunnel model;

[0060] S2, connect the control box and base station of the hardware equipment to the industrial ring network of the coal mine;

[0061] S3, deploy the host computer server for remote control of hardware equipment, building and debugging software platforms, storing data, generating Shape map files and data interaction;

[0062] S4. Build an intelligent pressure-equalizing control platform in the host computer to achieve wind pressure control by controlling the fan frequency and the wind window opening;

[0063] S5. Build a cloud computing intelligent brain analysis platform in the host computer to optimize the coal mine ventilation model. Combine the collected information (tunnel length, tunnel width, tunnel section, wind speed, wind pressure, temperature, humidity), build a data warehouse through Redis cache, properties configuration files and MySQL data to establish a coal mine ventilation data model, and enter it into the cloud computing intelligent brain analysis platform;

[0064] S6. Set the warning threshold and establish a warning data model. When the threshold is exceeded, the system will automatically issue an alarm.

[0065] In one embodiment of the present invention, a field investigation is conducted in combination with the on-site conditions of the coal mine, and relevant measuring instruments such as high-precision pressure gauges, anemometers, thermometers and hygrometers are used to measure and record the ventilation environment parameters such as pressure, wind speed, temperature, and humidity. The initial coal mine ventilation model is established based on the measured data, and the locations of hardware equipment such as wind pressure sensors, wind speed sensors, temperature and humidity sensors, variable frequency fans, additional dampers, and pressure regulating dampers are planned through the ventilation model. The rationality of the equipment location planning layout is tested by creating a three-dimensional ventilation tunnel diagram for reverse simulation.

[0066] Get the total pressure P of the lane 全 and the static pressure P of the roadway 静 , the wind speed data of the monitoring point is calculated by the following formula:

[0067] P 全 =P 静 +P 动

[0068] ρ=0.00345×P 静 ×(273.15+t)

[0069]

[0070] Among them, P 动 is the dynamic pressure of the tunnel, ρ is the air density, t is the Celsius temperature of the monitoring point, and V is the wind speed data of the monitoring point.

[0071] The wind resistance of the roadway obtained through wind speed data specifically includes:

[0072]

[0073] Among them, Δh is the pressure difference at both ends of the tunnel, which is measured using a differential pressure meter; V is the wind speed in the tunnel, which is collected by the sensor; S is the cross-sectional area, which is obtained by field measurement.

[0074] By measuring and calculating the tunnel section, wind speed and pressure difference, we can obtain the wind resistance R of the tunnel, which is used to calculate the pressure drop Δh=RQ when adjusting the pressure balance later. 2 Provide basic data support, where R is the tunnel wind resistance; Q is the tunnel air volume, which is obtained by multiplying the wind speed and the tunnel cross-sectional area.

[0075] According to the preliminary planning and layout of the underground equipment location, the corresponding sensors, wind windows, dampers, fans and other equipment will be transported to the designated location and installed on site. In combination with the actual situation of the mine, the required power supply, gas source, optical fiber and other infrastructure will be connected to the equipment at 2-10m.

[0076] The high-precision wind speed sensor uses ultrasonic speed measurement technology to replace the existing mechanical anemometer, which greatly improves the measurement accuracy and measurement range of wind speed. The wind speed in the tunnel is finally calculated by using the different propagation times of the ventilation ultrasonic waves of the sensor in the downwind and headwind. The ultrasonic probes are installed diagonally on both sides of the tunnel to maximize the increase in sampling data.

[0077] In one embodiment of the present invention, it is assumed that the time for the ultrasonic wave to travel from probe A to probe B is t1, the time for the ultrasonic wave to travel from probe B to probe A is t2, the distance between the two probes is L, the propagation speed of the ultrasonic wave in the air is V0, the wind speed in the tunnel is V, and the wind speed in the tunnel is V1, which is the component wind speed of the two probes.

[0078]

[0079] V=kV1

[0080] Among them, k is the adjustment coefficient calculated based on the direct distance between the two probes and the component distance in wind speed. The larger the k value, the greater the tunnel wind speed V. The calculation method of k is:

[0081] tanα=W÷L

[0082] cosα=V1÷V

[0083] V=V1÷cosα

[0084]

[0085] Wherein, W is the distance between the two transducer probes in the direction of vertical tunnel wind flow, L is the distance between the two transducer probes, α is the angle between the two transducer probes and the tunnel wind volume direction, and the value of α should be 0°-90° and include 0° and 90°.

[0086] In one embodiment of the present invention, the control box, base station and other devices of the underground equipment convert the electrical signal into AB differential signal by adding RS485 module, the differential signal is converted into network signal through RS485 network port module, the network signal enters the industrial ring network of the coal mine through the switch or is converted into electrical signal through the photoelectric switch and then connected to the industrial ring network of the coal mine through optical fiber; the corresponding host computer server is installed and deployed in the ground machine room, the software platform environment is built and debugged on the server, the Jdk environment variable is configured, the Jdk virtual machine is installed in the system to ensure that the background system software can be deployed across platforms, the Redis high-speed cache server is used to improve the data reading speed, and the front end uses Nginx The Web service proxy implements the B / S architecture deployment and completes the deployment of one machine for the whole network. The main application business data is stored in the MySQL database to realize the subsequent data traceability and statistical analysis. The CAD file is imported to automatically generate the Shape map file to realize the map access of the mine tunnel map on the browsing end based on WebGIS. The ModBus4j middleware is used to realize the communication and data interaction with the underground equipment through the modbus protocol, and the intelligent pressure equalization control platform and the cloud computing intelligent brain analysis platform are deployed on the server; finally, the normal communication between the underground equipment and the ground server is realized, and the automatic collection and display of the underground environmental data (wind speed, wind pressure, temperature, humidity, etc.) and the working parameters of the ventilation equipment (dampers, wind windows, fans, etc.) are completed.

[0087] The debugging process of the software platform is as follows: by using RedisDesktopManager to configure the parameters of the Redis cache database and initialize the basic data of the database (database id, damper device information, wind window device information, local fan device information), use NetAssit and Modscan plug-in tools to conduct joint debugging tests on the communication status of the underground control box and the message data interaction status, use 360 ​​browser or Google Browser to install the vlc video playback plug-in and perform function display linkage debugging on the Browser side of the software platform system.

[0088] Further optimize and subdivide the coal mine ventilation model established by the previous measurement, establish a coal mine ventilation data model in combination with the collection and analysis of underground data and enter it into the corresponding cloud computing intelligent brain analysis platform, and combine daily real-time data collection to achieve self-learning and continuous optimization of the model; set different warning thresholds according to the different coal mine gas conditions and geological conditions to create a warning data model that conforms to the actual situation of the mine. The host computer compares the collected parameter data with the target values ​​set by the wind speed and pressure parameters of the working face to realize intelligent and automatic remote control of the size of the underground pressure regulating damper and the frequency adjustment of the local fan, and realize intelligent pressure-equalizing ventilation and fire prevention in the goaf around the working face.

[0089] In one embodiment of the present invention, Figure 6The data table of coal mine application data collection and analysis of the present invention is shown, in which the auxiliary transportation chute working condition parameter record (the cross-sectional area of ​​the measuring point is 19.05m 2 ), the auxiliary transport chute air volume data analysis is specifically as follows: the errors of measuring the tunnel air volume and the sensor data collection air volume at the four openings of 100%, 75%, 50%, and 25% are 0.8%, 0%, 3%, and 3.5% respectively, which meets the requirement that the measurement error is less than 5%, so the auxiliary transport chute wind speed sensor meets the measurement accuracy requirements. At the same time, as the air door opening decreases, the absolute atmospheric pressure inside is 91.146kPa, 91.155kPa, 91.172kPa, and 91.183kPa, respectively, gradually increasing, which meets the goal of equalizing the pressure on the working face and balancing the atmospheric pressure difference on the surface.

[0090] In one embodiment of the present invention, Figure 7 The figure shows the data table of the auxiliary transport chute air volume data analysis of the present invention, in which the rubber transport chute working condition parameter records (the cross-sectional area of ​​the measuring point is 22.32m 2 ), the analysis of the air volume data of the rubber transport chute specifically includes: the errors of measuring the air volume in the tunnel and collecting the air volume with sensor data at the four openings of 50Hz, 40Hz, 30Hz and 20Hz are 0.4%, 1.8%, 1.4% and 3% respectively, which meets the requirement of measuring error less than 5%, so the wind speed sensor of the rubber transport chute meets the measurement accuracy requirements. At the same time, with the gradual increase of the frequency of the local fan, the absolute atmospheric pressure inside is: 91.196kPa, 91.201kPa, 91.236kPa, 91.265kPa, which is gradually increasing, meeting the goal of balancing the atmospheric pressure difference on the surface by equalizing the pressure and boosting the working face.

[0091] In one embodiment of the present invention, when the fan operating frequency is 50 Hz and the wind window opening is 100%, the air volume of the rubber transport chute is 19.132 m 3 / s, the absolute atmospheric pressure inside the damper is 19.273 kPa, and the air volume of the auxiliary chute is 19.162 m 3 / s, the absolute atmospheric pressure inside the damper is 19.183 kPa; the device performs a one-button wind control intelligent pressure equalization operation to set the air volume to 15m 3 / s, the fan frequency is adjusted to 39Hz through the intelligent pressure equalization system control adjustment, and the wind window opening is adjusted to 23%. At this time, the air volume of the rubber transport chute collected by the sensor is 15.13m 3 / s, the absolute atmospheric pressure inside the damper is 19.285 kPa, and the air volume data of the auxiliary chute is 15.16 m 3 / sThe absolute atmospheric pressure inside the damper is 192.216kPa; the air volume error of 1.06% meets the measurement adjustment accuracy required by relevant regulations. At the same time, the pressure differences before and after are 0.090kPa and 0.069Kpa respectively. The resistance along the way is reduced due to the reduction of air volume, and finally the pressure difference becomes lower, which is in line with the actual state underground and the purpose of one-button wind control and intelligent pressure equalization.

[0092] The underground pressure-regulating dampers and local fans can be remotely controlled through the host computer, and one-touch wind control and intelligent pressure equalization operations can be performed directly on the intelligent pressure equalization work page. By setting the required air volume on the host computer, the intelligent pressure equalization system calculates and automatically adjusts the underground pressure-regulating dampers and local fans to ultimately achieve precise wind control and intelligent pressure equalization on the working face.

[0093] like Figure 2 As shown, a mine intelligent pressure-equalizing ventilation fire prevention and extinguishing device comprises:

[0094] The control module, including the host computer server and the control box and base station of the hardware equipment, is used to control the opening of the underground pressure regulating damper and the speed of the local fan, process and store data, generate Shape map files, and build and debug the software platform;

[0095] The data acquisition module includes a high-precision pressure gauge, anemometer, thermometer and humidity meter, ultrasonic probe, and high-precision wind speed sensor, which are used to collect tunnel information, including pressure, wind speed, temperature, and humidity;

[0096] A signal processing module, including a ring network switch and an optical fiber switch, is used to convert electrical signals into differential signals, convert differential signals into network signals, and convert network signals into electrical signals;

[0097] Communication module, used for signal transmission between control module, data acquisition module, signal processing module, hardware equipment, early warning module and user terminal;

[0098] Hardware equipment, including windows, doors, and fans, for ventilation;

[0099] Early warning module: when the set early warning threshold is exceeded, the early warning module will automatically alarm;

[0100] User terminal, the medium for human-computer interaction.

[0101] The signal processing module also includes: an RS485 module and an RS485 to network port module, which are used for signal conversion.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A mine intelligent pressure-equalizing ventilation fire prevention and extinguishing method, characterized in that: The steps include: S0, collecting the ventilation environment parameters of the tunnel, and calculating the wind resistance and friction coefficient of the tunnel according to the resistance law, wind volume balance law, and energy balance law, classifying and summarizing the characteristic data of the coal mine tunnel into the MySQL database, and establishing the ventilation parameter model of the coal mine ventilation tunnel; S1. Plan the location of hardware equipment through the ventilation parameter model of the coal mine ventilation tunnel, establish a three-dimensional ventilation tunnel model, and adjust the location of hardware equipment through the three-dimensional ventilation tunnel model; S2, connect the control box and base station of the hardware equipment to the industrial ring network of the coal mine; S3, deploy the host computer server for remote control of hardware equipment, building and debugging software platforms, storing data, generating Shape map files and data interaction; S4. Build an intelligent pressure-equalizing control platform in the host computer to control the wind pressure by controlling the fan frequency and the wind window opening; S5. Build a cloud computing intelligent brain analysis platform in the host computer, optimize the ventilation parameter model of the coal mine ventilation tunnel, combine the collected information, build a data warehouse through Redis cache, properties configuration files and MySQL data to establish a coal mine ventilation data model, and enter it into the cloud computing intelligent brain analysis platform; S6. Set the warning threshold and establish a warning data model. When the threshold is exceeded, the host computer automatically issues an alarm. The ventilation environment parameters in step S0 include: pressure, wind speed, temperature, and humidity; Among the ventilation environment parameters, the specific method for obtaining the wind speed data is as follows: Get the total pressure P of the lane 全 and the static pressure P of the tunnel 静 , the wind speed data of the monitoring point is calculated by the following formula: P 全 =P 静 +P 动 p=0.00345×P 静 ×(273.15+t) Among them, P 动 is the dynamic pressure of the tunnel, P 全 , P 静 , P 动 The unit is kPa; ρ is the air density in the tunnel, the unit is kg / m3; t is the Celsius temperature at the monitoring point, the unit is ℃; V is the wind speed data at the monitoring point, the unit is m / s; The method for calculating the wind speed data also includes: The time for the ultrasonic wave to travel from probe A to probe B is t1, in seconds. The time for the ultrasonic wave to travel from probe B to probe A is t2, in seconds. The distance between the two probes is L, in meters. The propagation speed of the ultrasonic wave in the air is V0, in meters / s. The wind speed in the tunnel is V, in meters / s. The wind speed in the tunnel is the component wind speed of the two probes, V1, in meters / s. The specific calculation formula is: V=kV1 Among them, k is the adjustment coefficient calculated based on the direct distance between the two probes and the component distance in wind speed. The larger k is, the greater the tunnel wind speed V is. The specific calculation method of k is: tanα=W÷L cosα=V1÷V V=V1÷cosα Wherein, W is the distance between the two transducer probes in the direction perpendicular to the roadway wind flow, in m; L is the distance between the two transducer probes, in m; α is the angle between the two transducer probes and the roadway wind volume direction, in degrees.

2. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: Step S2 connects the hardware equipment to the industrial ring network of the coal mine. Specifically, the control box and base station of the hardware equipment convert the electrical signal into AB differential signal through the RS485 module, and the differential signal is converted into a network signal through the RS485 network port module. The network signal enters the industrial ring network of the coal mine through the switch or is converted into an electrical signal through an optoelectronic switch and then connected to the industrial ring network of the coal mine through optical fiber.

3. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: Step S3 specifically includes: configuring the JDK environment variables on the host server and installing the JDK virtual machine in the host computer to ensure that the background system software is deployed across platforms; using the Redis high-speed cache server to improve the data reading speed, using the Nginx Web service proxy on the front end to implement the B / S architecture deployment to complete the one-machine deployment for the entire network, using the MySQL database to store application business data for later data tracing and statistical analysis, importing CAD files to automatically generate Shape map files based on WebGIS to achieve map access to the mine tunnel map on the browsing end, and using ModBus4j middleware to achieve communication and data interaction with underground equipment through the modbus protocol.

4. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: In step S3, a software platform is built and debugged on the host computer server, and the software platform includes: an intelligent voltage-sharing control platform and a cloud computing intelligent brain analysis platform; The debugging process of the software platform by the host computer specifically includes: using RedisDesktopManager to configure the parameters of the Redis cache database and initialize the basic data of the database, and using NetAssit and Modscan plug-in tools to perform joint debugging tests on the communication status of the underground control box and the message data interaction status.

5. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: In step S4, the intelligent pressure equalization control platform realizes wind pressure control by controlling the size of the fan frequency and the size of the wind window opening, which is specifically manifested as follows: Reducing wind pressure specifically includes: reducing the frequency of local fans or increasing the opening of the dampers to ensure the wind volume at the working face while reducing the wind pressure in the goaf to ensure equal pressure with the ground; Increasing wind pressure specifically includes: increasing the frequency of local fans and adjusting the damper opening to ensure the air volume at the working face while increasing the wind pressure in the goaf to ensure equal pressure with the ground.

6. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: The cloud computing intelligent brain analysis platform described in step S5 realizes self-learning and continuous optimization of the model through daily real-time collected data.

7. The intelligent pressure-equalizing ventilation fire prevention and extinguishing method for mines according to claim 1, characterized in that: The mine's intelligent pressure equalization method also includes autonomous adjustment of the software platform, specifically: the host computer compares the collected parameter data with the target values ​​set by the working face wind speed and wind pressure parameters to achieve intelligent and automatic remote control of the size of the underground pressure regulating damper and frequency adjustment of the local fan until the ventilation conditions underground meet the requirements.

8. A mine intelligent pressure-equalizing ventilation fire prevention and extinguishing device, characterized in that: The device is used to implement the method according to claim 1, and the device comprises: The control module, including the host computer server and the control box and base station of the hardware equipment, is used to control the opening of the underground pressure regulating damper and the speed of the local fan, process and store data, generate Shape map files, and build and debug the software platform; The data acquisition module includes a high-precision pressure gauge, anemometer, thermometer and humidity meter, ultrasonic probe, and high-precision wind speed sensor, which are used to collect tunnel information, including pressure, wind speed, temperature, and humidity; A signal processing module, including a ring network switch and an optical fiber switch, is used to convert electrical signals into differential signals, convert differential signals into network signals, and convert network signals into electrical signals; Communication module, used for signal transmission between control module, data acquisition module, signal processing module, hardware equipment, early warning module and user terminal; Hardware equipment, including windows, doors, and fans, for ventilation; Early warning module: when the set early warning threshold is exceeded, the early warning module will automatically alarm; User terminal, the medium for human-computer interaction.

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