Gas flow field hardware system for highly-intelligent fully-mechanized face and arrangement method

Abstract

The invention discloses a gas flow field hardware system for a high-intelligence fully-mechanized face and an arrangement method, and relates to the technical field of coal mine safety monitoring, and the technical scheme is characterized in that the gas flow field hardware system comprises a high-precision sensor array which is used for monitoring ventilation, gas concentration and gas extraction measurement around a working face in real time; the data acquisition and transmission network realizes real-time transmission of monitoring data; the server and the client computer are used for receiving and processing the monitoring data; the gas flow field and gas abnormity early warning model is used for constructing and analyzing gas flow field distribution and abnormity early warning based on monitoring data; and the early warning information system integrates an early warning model and realizes online monitoring, intelligent analysis and real-time early warning. The system realizes comprehensive monitoring and intelligent analysis of gas abnormity in areas such as a working face, a goaf, an upper corner and the like by visualizing a gas flow field around the working face, remarkably improves the gas abnormity monitoring and early warning capability, effectively prevents gas accidents, guarantees the safety of miners and improves the safe operation level of a mine.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine safety monitoring and surveillance, and more specifically, to a gas flow field hardware system and a layout method for a high-intelligent fully mechanized mining face. Background Art

[0002] As an important part of the safety guarantee of intelligent working faces, gas prevention and control must be further strengthened and implemented. With the advancement of intelligent construction, the production conditions of mines will undergo profound changes, resulting in more complex and changeable gas outbursts, gas flows, mine pressure manifestations, and gas flow fields in goafs. It is increasingly difficult to perceive gas risks in advance and predict trends, and gas prevention and control at working faces will face unprecedented challenges.

[0003] Although the gas prevention and control and safe and efficient production of Shihe Mine are in a state of balance at a relatively high level, with the steady advancement of intelligent construction, the production conditions of the mine will undergo profound changes, resulting in more complex and changeable gas outbursts, gas flows, mine pressure manifestations, and gas flow fields in goafs at the working face, making it increasingly difficult to perceive gas risks in advance and predict trends. Existing technologies must be further strengthened and implemented under intelligent production conditions, especially in the face of challenges in gas risk prevention and control such as excessive gas in the upper corner and gas backflow in goafs. Existing gas monitoring technologies have monitoring blind spots and difficulties, and cannot achieve full coverage of gas monitoring at intelligent working faces, making it difficult to provide scientific and reliable gas prevention and control guarantees for intelligent working faces.

[0004] Therefore, it is necessary and of great significance to study the abnormal gas warning system of the intelligent working face of Sihe Mine, monitor the gas flow field of the working face, upper corner and goaf in real time, and dynamically identify the gas risk of the working face to ensure the safety of intelligent working face operations. Summary of the invention

[0005] The purpose of the present invention is to provide a gas flow field hardware system and layout method for high-intelligence fully mechanized mining faces, so as to solve the problems in the prior art that the working face cannot be fully covered and the gas risk management under complex and changeable production conditions.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: A gas flow field hardware system for high-intelligent fully mechanized mining face, comprising:

[0007] High-precision sensor array for monitoring ventilation around the working face, gas concentration and gas extraction metering;

[0008] A data acquisition and transmission network, connected to the sensor array, for real-time transmission of monitoring data;

[0009] Server and client computers for receiving and processing the transmitted monitoring data;

[0010] A gas flow field and gas anomaly warning model is constructed based on the monitoring data and is used to analyze the gas flow field distribution and anomaly warning;

[0011] The early warning information system integrates the gas flow field and gas anomaly early warning models to achieve online monitoring, intelligent analysis and real-time early warning.

[0012] The present invention is further configured as follows: the high-precision sensor array comprises:

[0013] Wind speed and direction sensors are arranged in the air inlet and return tunnels and brackets of the working face;

[0014] Environmental laser methane sensors and pipeline laser methane sensors are used to monitor the concentration of environmental gas and pipeline gas;

[0015] Distributed optical fiber methane detector, used for multi-point synchronous detection of methane gas concentration;

[0016] Mine gas extraction multi-parameter sensor monitors flow, negative pressure and temperature parameters.

[0017] The present invention is further configured as follows: the data acquisition and transmission network includes a network system based on an underground industrial ring network and a ground office network, and hardware equipment for data acquisition, storage, analysis and information release.

[0018] The present invention is further configured as follows: the gas flow field and gas abnormality early warning model includes the following models:

[0019] Gas emission characteristic analysis model for working face;

[0020] Upper corner gas distribution characteristics and abnormal warning model;

[0021] Working face flow field characteristics and influencing factors analysis model;

[0022] Analysis model of mine pressure monitoring characteristics and its relationship with gas monitoring data;

[0023] Working face gas abnormality early warning model;

[0024] Numerical simulation of flow field in goaf area and analysis model of distribution law;

[0025] High and low borehole gas extraction data analysis model.

[0026] The present invention is further configured as follows: the early warning information system comprises:

[0027] Data acquisition interface, used to realize real-time collection and storage of data such as gas monitoring, mine pressure monitoring, extraction monitoring, ventilation monitoring, etc.;

[0028] Early warning analysis and result release module, used to predict the trend of abnormal gas phenomena and provide real-time early warning;

[0029] The gas abnormality warning SMS platform is used to notify the designated responsible personnel of gas abnormality information in real time.

[0030] The present invention is further configured as follows: the system also includes a peep instrument and a goaf area bundle pipe monitoring sensor for auxiliary monitoring of the goaf area edge collapse state and gas environment.

[0031] Another object of the present invention is to provide a method for arranging a gas flow field hardware system for a high-intelligent fully mechanized mining face, the method comprising the following steps:

[0032] a. Arrange wind speed and direction sensors in the air inlet and return tunnels and brackets of the working face;

[0033] b. Arrange environmental laser methane sensors and pipeline laser methane sensors on the working surface, upper and lower corners, air inlet and return tunnels, and inside the closed wall;

[0034] c. Arrange a distributed optical fiber methane detector in the upper corner triangle area, and arrange multiple probes along the upper corner triangle area;

[0035] d. Arrange laser methane sensors for pipelines in the extraction pipes in the goaf area and in the extraction pipes at high and low positions of the boreholes;

[0036] e. Methane sensors are installed on the PE380 extraction main pipe in the return air lane at the tail lane and the return air closed wall as well as in the high and low position boreholes;

[0037] f. Arrange a mining intrinsically safe gas sampler at the first horizontal river near the working face in the goaf. The main unit is arranged outside the closed wall, and the bundle tube is pushed to the inside of the closed wall at a position 10m away from the goaf;

[0038] g. Pre-install a PE pipe on the bottom plate of the closed front tunnel of the return air tunnel to use the peep instrument to observe the collapse status of the edge of the goaf;

[0039] h. Connecting the sensor array through a data acquisition and transmission network to achieve real-time transmission of monitoring data;

[0040] i. Receive and process the transmitted monitoring data using server and client computers;

[0041] j. Construct gas flow field and gas abnormality warning model based on monitoring data and conduct intelligent analysis;

[0042] k. Integrate the gas flow field and gas anomaly warning model into the warning information system to achieve online monitoring, intelligent analysis and real-time warning.

[0043] By adopting the above technical solution, the present invention can fully cover the ventilation, gas concentration and gas extraction metering around the working face by deploying a high-precision sensor array, ensuring the comprehensiveness and real-time nature of the monitoring data. This comprehensive coverage and real-time transmission capability enables the system to capture precursor information of gas risks in a timely manner, providing a solid data foundation for the prediction and early warning of gas risks. At the same time, through the data acquisition and transmission network, the real-time collection and storage of monitoring data, as well as the trend prediction and real-time early warning of gas anomalies are realized, ensuring that timely measures can be taken when gas anomalies occur to ensure the safety of miners.

[0044] The server and client computers of the present invention receive and process the transmitted monitoring data, and use the gas flow field and gas abnormality warning model for intelligent analysis. This intelligent processing method greatly improves the efficiency and accuracy of data processing, making the gas abnormality warning more scientific and reliable. The integration of the early warning information system, especially the development of the gas abnormality warning SMS platform, enables the gas abnormality information to notify the designated responsible personnel in real time, improving the speed and efficiency of emergency response.

[0045] The system of the present invention has constructed multiple models including the working face gas outburst characteristic analysis model, the upper corner gas distribution characteristic and abnormal warning model. The comprehensive application of these models enables the system to conduct in-depth analysis of the gas flow field from different angles and levels, thereby improving the accuracy and effectiveness of the gas abnormality warning. In addition, by integrating multiple monitoring models and early warning information systems, the present invention not only improves the efficiency of data processing, but also enhances the ability to predict gas risk trends, thereby optimizing the gas control plan and improving the scientific management level and production efficiency of the mine. Through the implementation of these technical solutions, the present invention significantly improves the gas abnormality monitoring and early warning capabilities, effectively prevents gas accidents, ensures the safety of miners, and improves the safety level of mine operations.

[0046] In summary, the present invention has the following beneficial effects:

[0047] 1. The present invention significantly improves the monitoring and early warning capabilities of gas anomalies by comprehensively monitoring the ventilation, gas concentration and gas extraction metering around the working face, combined with real-time data transmission and intelligent analysis. This real-time monitoring and rapid response mechanism can effectively prevent the occurrence of gas accidents, ensure the safety of miners, and improve the safety level of mine operations.

[0048] 2. The system design of the present invention realizes dynamic monitoring and intelligent analysis of gas flow fields, making gas management more scientific and accurate. By integrating multiple monitoring models and early warning information systems, the present invention not only improves the efficiency of data processing, but also enhances the ability to predict gas risk trends, thereby optimizing gas control plans and improving the scientific management level and production efficiency of mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a structural diagram of a working face gas anomaly monitoring and early warning system in an embodiment of the present invention;

[0050] Figure 2 is a schematic diagram of a ventilation sensor arrangement scheme in an embodiment of the present invention;

[0051] Figure 3 Schematic diagram of the arrangement of gas sensors in an embodiment of the present invention;

[0052] Figure 4 is a schematic diagram of the arrangement of extraction sensors in an embodiment of the present invention;

[0053] Figure 5 is a schematic diagram of a bundle tube monitoring arrangement scheme in an embodiment of the present invention;

[0054] Figure 6 This is a schematic diagram of observation of a peep device in an embodiment of the present invention;

[0055] Figure 7 This is an example diagram of the expected effect of the early warning information system in the embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the embodiments of the present invention and the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0057] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. In addition, the experimental methods in the following embodiments are conventional methods unless otherwise specified. Figure 1-6 The present invention is described in further detail.

[0058] Embodiment: A gas flow field hardware system for a highly intelligent fully mechanized mining face includes a high-precision sensor array for monitoring ventilation around the working face, gas concentration, and gas extraction metering;

[0059] 1. Ventilation sensor layout

[0060] In order to estimate the wind volume entering the goaf, a total of 8 wind speed and direction sensors were arranged at the 5313 working face, such as Figure 1 As shown, the specific installation positions are as follows: Arrange one wind speed and direction sensor in each of the inlet and return air lanes of the working face ( Figure 1, 1, 6, 7, 8 positions), and arrange one wind speed and direction sensor at each of the 60# and 120# brackets in the middle of the working face ( Figure 1 , 3, 4 positions), and arrange a wind speed and direction sensor at each of the upper and lower corners ( Figure 1 , 2, 5 positions).

[0061] 2. Gas sensor layout

[0062] Gas sensors can be divided into environmental gas sensors and pipeline gas sensors according to different application scenarios. The present invention adopts the new GJG100J environmental laser methane sensor and the GJG100J (B) pipeline laser methane sensor. The two types of sensors have the same measurement principle and both adopt the independently patented "self-calibration" technology, which can realize automatic linear correction of the sensor. The stable operation time is greater than 60 days, and the sensor has its own sealed standard gas sample inside, which can ensure the monitoring accuracy by "dual optical path" measurement. In addition, in order to realize the effective monitoring of spatial gas distribution, the present invention adopts the YJG100X (8) distributed optical fiber methane measuring instrument. The instrument adopts laser absorption spectrum detection combined with optical wave multi-point multiplexing technology. It can monitor the methane gas concentration of up to 8 measuring points at the same time. It has the advantages of multi-point real-time synchronous detection, high measurement accuracy, long adjustment cycle, good repeatability, wide measurement range, long service life, and no influence from other gases in the environment. The specific layout of the gas sensor is as follows: Figure 2 shown.

[0063] 2.1 Ambient gas sensor layout

[0064] Environmental gas sensors are mainly used to monitor the gas concentration in the working face, upper and lower corners, air inlet and return tunnels, and inside the closed wall. Figure 2 The specific sensor selection and installation method are as follows: GJG100J environmental laser methane sensors are used at positions 1 to 7; YJG100X(8) distributed optical fiber methane measuring instruments are used at positions 8 to 11, and 4 to 8 probes are arranged along the upper corner triangle area at position 8.

[0065] 2.2 Pipeline gas sensor layout

[0066] Pipeline gas sensors are mainly used to monitor gas concentration in extraction pipes in goaf areas and high and low-level borehole extraction pipes. GJG100J (B) type pipeline laser methane sensors are used. Figure 2 , 17 to 21 positions) and return air ( Figure 2 , 12 to 16 positions) The methane sensor at the closed wall is installed on the PE380 pipeline outside the closed wall, and high and low holes are drilled ( Figure 2, 22 to 26 positions) methane sensors are installed on the PE380 extraction main pipe in the return air lane. It should be noted that if the working face is mined for more than 200m, the tail lane sensor ( Figure 2 , positions 17 to 21) do not need to be installed.

[0067] 3. Extraction sensor layout

[0068] The extraction sensor mainly monitors three parameters: flow, negative pressure and temperature. The GD3(B) type mine gas extraction multi-parameter sensor is used. Figure 3 , 17 to 21 positions) and return air ( Figure 3 , 12 to 16 positions) The methane sensor at the closed wall is installed on the PE380 pipeline outside the closed wall, and high and low holes are drilled ( Figure 3 , 22 to 26 positions) methane sensors are installed on the PE380 extraction main pipe in the return air lane. It should be noted that if the working face is mined for more than 200m, the tail lane sensor ( Figure 3 , positions 17 to 21) do not need to be installed.

[0069] 4. Arrangement of sensors for monitoring the bundled tube in the goaf area

[0070] In order to fully understand the gas environment in the goaf, the present invention introduces a new CQB1 type mine intrinsically safe gas sampler (beam tube monitoring). The system can realize "three on-site" measurements (on-site sampling, on-site measurement, on-site display and transmission), and the measurement data can be directly connected to the safety monitoring system. This system is only used as an auxiliary system for gas flow field modeling. It is planned to deploy one set, which will be arranged in the first horizontal river near the working face in the goaf, such as Figure 4 As shown in the figure, the main machine is arranged outside the closed wall, and the bundle tube is pushed into the closed wall at a position 10m away from the goaf. The instrument is installed before the Yokogawa closed.

[0071] 5. Peeping Device Arrangement

[0072] The present invention uses a peep instrument to observe the collapse state of the edge of the goaf, and the observation method is designed as follows: Figure 5 As shown: a PE pipe is pre-installed on the bottom plate of the closed front tunnel of the return air lane. The front end of the PE pipe is kept at a safe distance of about 10m from the goaf, and a valve is installed at the tail end. When observation is required, the valve is opened and the peephole camera is sent along the PE pipe to a suitable position for observation by a guide rod. The observation results are stored in the form of video.

[0073] A data acquisition and transmission network, connected to the sensor array, for real-time transmission of monitoring data; a server and client computer, for receiving and processing the transmitted monitoring data; a gas flow field and gas abnormality early warning model, constructed based on the monitoring data, for analyzing gas flow field distribution and abnormality early warning;

[0074] According to the monitoring data of ventilation, gas, extraction and other key nodes, data mining, mathematical statistics, numerical simulation and field experiments are used to effectively integrate the multivariate monitoring and simulation data, realize the visualization of the gas flow field in the working face, upper corner and goaf based on big data, and build an intelligent comprehensive mining working face gas abnormality early warning model on this basis.

[0075] Analysis of gas emission characteristics of working face: Gas sensors are arranged at key nodes of the working face to conduct comprehensive monitoring of the working face environmental gas. Factors such as coal seam gas content and gas extraction are comprehensively considered to construct a gas emission characteristic model.

[0076] Gas distribution characteristics in the upper corner and construction of abnormal warning model: Multiple measuring points are arranged in the "triangle area" of the upper corner with distributed laser methane sensors. Big data analysis methods are used to analyze the gas accumulation and flow direction in the upper corner, and the changing relationship between the gas in the upper corner and the goaf is studied to establish an abnormal gas warning model in the upper corner.

[0077] Analysis of working face flow field characteristics and influencing factors: According to the actual situation of Sihe Mine, a sensor layout plan was designed, and wind speed, gas, temperature and other sensors were arranged at the key nodes of the three tunnels of "two inlets and one return". A large amount of monitoring data was deeply mined, and combined with numerical simulation methods, the working face wind flow field was analyzed, the air volume entering the goaf and its changing law were estimated, and its correlation with the degree of gas accumulation in the goaf was studied.

[0078] On the basis of comprehensive monitoring of working face ventilation and gas parameters, the changes in working face flow field under typical conditions such as direct roof collapse, periodic pressure from old roof, over-structure, coal quality changes and operating procedure changes are analyzed to understand the main influencing factors of working face flow field changes.

[0079] Analysis of mine pressure monitoring characteristics and their relationship with gas monitoring data: The characteristics of mine pressure monitoring and gas monitoring data were extracted respectively, and the correlation between the two was analyzed to study the impact of mine pressure on gas outburst and gas flow field in the high-height fully-mechanized mining face of Sihe Mine.

[0080] Construction of working face gas abnormality warning model: By monitoring the gas, wind speed and direction, temperature and other information around the working face, combined with the gas flow field in the goaf, establish working face gas abnormality warning indicators and rules (including automatic noise filtering method for gas monitoring data), real-time analysis of the current status and trend of gas inrush in the working face, and dynamic and advance identification of working face gas abnormalities.

[0081] Numerical simulation of flow field in goaf and analysis of distribution law: Based on the geological and production conditions of Sihe Mine and the detection results of goaf peep instruments, the distribution state of pores and cracks in goaf after the collapse of goaf roof is simulated, and then the gas flow field in goaf is simulated in combination with sensor monitoring data.

[0082] Analysis of gas extraction data from high and low-level boreholes: Install sensors on the gas extraction pipelines of high and low-level boreholes, the closed wall of the return air lane, and the closed wall of the shunting lane (tail lane). Based on the monitoring data of each group of sensors, big data analysis technology is used in combination with numerical simulation methods to analyze the change law of gas extraction data, realize abnormal gas extraction warning, and invert the gas outburst characteristics of the goaf to support the construction of the gas flow field in the goaf.

[0083] Early warning information system integrates gas flow field and gas abnormality early warning model to achieve online monitoring, intelligent analysis and real-time early warning;

[0084] Develop a dedicated data acquisition interface, build a professional early warning information database, realize the real-time collection and storage of gas monitoring, mine pressure monitoring, extraction monitoring, ventilation monitoring and other data, as well as the storage of early warning analysis data; develop an early warning information system based on big data, integrate the working face and surrounding gas flow field and gas abnormality early warning model, and realize the trend prediction and real-time early warning of the working face, upper corner, goaf gas flow field and gas abnormality phenomenon; develop a gas abnormality early warning SMS platform, which can notify the designated responsible personnel of gas abnormality information in real time. The expected effects of the early warning information system are as follows: Figure 6 shown.

[0085] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A gas flow field hardware system for high-intelligent fully mechanized mining face, characterized by: include: High-precision sensor array for monitoring ventilation around the working face, gas concentration and gas extraction metering; A data acquisition and transmission network, connected to the sensor array, for real-time transmission of monitoring data; Server and client computers for receiving and processing the transmitted monitoring data; A gas flow field and gas anomaly warning model is constructed based on the monitoring data and is used to analyze the gas flow field distribution and anomaly warning; The early warning information system integrates the gas flow field and gas anomaly early warning models to achieve online monitoring, intelligent analysis and real-time early warning.

2. The system according to claim 1, characterized in that: The high-precision sensor array comprises: Wind speed and direction sensors are arranged in the air inlet and return tunnels and brackets of the working face; Environmental laser methane sensors and pipeline laser methane sensors are used to monitor the concentration of environmental gas and pipeline gas; Distributed optical fiber methane detector, used for multi-point synchronous detection of methane gas concentration; Mine gas extraction multi-parameter sensor monitors flow, negative pressure and temperature parameters.

3. The system according to claim 1, characterized in that: The data collection and transmission network includes a network system based on an underground industrial ring network and a ground office network, as well as hardware equipment for data collection, storage, analysis and information release.

4. The system according to claim 1, characterized in that: The gas flow field and gas anomaly early warning model includes the following models: Gas emission characteristic analysis model for working face; Upper corner gas distribution characteristics and abnormal warning model; Working face flow field characteristics and influencing factors analysis model; Analysis model of mine pressure monitoring characteristics and its relationship with gas monitoring data; Working face gas abnormality early warning model; Numerical simulation of flow field in goaf area and analysis model of distribution law; High and low borehole gas extraction data analysis model.

5. The system according to claim 1, characterized in that: The early warning information system comprises: Data acquisition interface, used to realize real-time collection and storage of data such as gas monitoring, mine pressure monitoring, extraction monitoring, ventilation monitoring, etc.; Early warning analysis and result release module, used to predict the trend of abnormal gas phenomena and provide real-time early warning; The gas abnormality warning SMS platform is used to notify the designated responsible personnel of gas abnormality information in real time.

6. The system according to claim 1, characterized in that: The system also includes a peep instrument and a goaf bundle pipe monitoring sensor for auxiliary monitoring of the goaf edge collapse state and gas environment.

7. A method for arranging a gas flow field hardware system for a high-intelligent fully mechanized mining face, characterized in that: The arrangement method comprises the following steps: a. Arrange wind speed and direction sensors in the air inlet and return tunnels and brackets of the working face; b. Arrange environmental laser methane sensors and pipeline laser methane sensors on the working surface, upper and lower corners, air inlet and return tunnels, and inside the closed wall; c. Arrange a distributed optical fiber methane detector in the upper corner triangle area, and arrange multiple probes along the upper corner triangle area; d. Arrange laser methane sensors for pipelines in the extraction pipes in the goaf area and in the extraction pipes at high and low positions of the boreholes; e. Methane sensors are installed on the PE380 extraction main pipe in the return air lane at the tail lane and the return air closed wall as well as in the high and low position boreholes; f. Arrange a mining intrinsically safe gas sampler at the first horizontal river near the working face in the goaf. The main unit is arranged outside the closed wall, and the bundle tube is pushed to the inside of the closed wall at a position 10m away from the goaf; g. Pre-install a PE pipe on the bottom plate of the closed front tunnel of the return air tunnel to use the peep instrument to observe the collapse status of the edge of the goaf; h. Connecting the sensor array through a data acquisition and transmission network to achieve real-time transmission of monitoring data; i. Receive and process the transmitted monitoring data using server and client computers; j. Construct gas flow field and gas abnormality warning model based on monitoring data and conduct intelligent analysis; k. Integrate the gas flow field and gas anomaly warning model into the warning information system to achieve online monitoring, intelligent analysis and real-time warning.

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