Coal mine goaf gas extraction system and method

Abstract

The invention discloses a coal mine goaf gas extraction system and method, and relates to the technical field of gas extraction, and the system comprises a data collection unit which is used for collecting gas related data of a coal mine goaf in real time; the data transmission unit is used for transmitting gas related data to the background processing unit in real time; the background processing unit is used for generating safety constraint conditions based on the gas parameter threshold value and historical extraction monitoring data, judging whether the goaf environment meets the extraction requirement or not and outputting a control instruction; and the gas extraction execution unit is used for executing extraction starting, continuous extraction or extraction stopping operation according to the control instruction. Environmental data are collected in real time through the data collection unit, the background processing unit generates safety constraint conditions based on a machine learning algorithm and automatically judges extraction feasibility, extraction starting, continuing and stopping operation can be completed without manual intervention, dependence of traditional extraction on manual experience is eliminated, subjectivity of manual judgment is avoided, and the extraction efficiency is improved. And the extraction accuracy is further improved.

Description

Technical Field

[0001] This invention relates to the field of gas extraction technology, specifically a gas extraction system and method for goaf areas in coal mines. Background Technology

[0002] Most coal seams require gas drainage before mining to reduce the gas content and gas emission during mining, in order to achieve safe mining under low gas conditions and prevent accidents such as gas poisoning.

[0003] With the scientific development of coal mining technology, current coal mine gas drainage mainly relies on surface fixed gas drainage systems. These systems control parameters such as gas drainage pressure, temperature, and concentration within safe ranges to ensure safe gas drainage. However, existing gas drainage systems largely rely on manual experience for control, which has some shortcomings: 1. Manual control relies on the experience and judgment of operators, which is highly subjective and makes it difficult to adjust parameters according to real-time environmental changes in the goaf. This can easily lead to incomplete or excessive extraction, posing serious safety hazards. 2. Manual monitoring and control have response delays and cannot capture the dynamic fluctuations of parameters such as gas concentration and pressure in the goaf in real time. When environmental parameters change abruptly, it is difficult to take timely shutdown measures. Summary of the Invention

[0004] The purpose of this invention is to provide a gas extraction system and method for coal mine goaf areas, so as to solve the problem that the existing gas extraction system relies heavily on manual experience, which makes it impossible to accurately judge the degree of extraction and the timing of extraction shutdown.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A coal mine goaf gas extraction system includes a data acquisition unit, a data transmission unit, a background processing unit, and a gas extraction execution unit that communicate with each other via a network. The data acquisition unit is deployed at several monitoring points in the coal mine goaf and is equipped with several sensors to collect gas-related data in the coal mine goaf in real time. The gas-related data includes non-extraction monitoring data in the non-extraction state and extraction monitoring data in the extraction state. The data transmission unit is used to transmit gas-related data to the background processing unit in real time. The background processing unit has built-in analysis software and a database. The database stores gas parameter thresholds and historical extraction monitoring data. The analysis software is used to generate safety constraints based on gas parameter thresholds and historical extraction monitoring data, and to determine whether the goaf environment meets the extraction requirements by combining gas-related data, and output control commands. The gas extraction execution unit is electrically connected to the background processing unit and is used to execute extraction start, continuous extraction or extraction stop operations according to control commands.

[0006] Furthermore, the data acquisition unit includes several sets of sensor components, each set of sensor components integrating at least a gas concentration sensor, a carbon dioxide concentration sensor, a methane concentration sensor, an oxygen concentration sensor, a temperature sensor, and a pressure sensor. The monitoring points include at least the air intake side boundary, the return air side boundary, the core area of ​​the caving zone, and the area with delamination fractures in the coal mine goaf. The data acquisition unit has a non-extraction state acquisition mode and an extraction state acquisition mode. In the non-extraction state acquisition mode, the data acquisition unit collects non-extraction monitoring data in the non-extraction state through several sensors. In the extraction state acquisition mode, the data acquisition unit collects extraction monitoring data in the extraction state through several sensors.

[0007] Furthermore, the analysis software includes a data preprocessing module, a constraint generation module, an environment judgment module, and an instruction output module. The data preprocessing module is used to perform noise reduction, outlier removal, and standardization on the gas-related data. The constraint generation module is used to construct a safety constraint model based on gas parameter thresholds and historical extraction monitoring data in the database, and output real-time safety constraints. The environment judgment module is used to compare the preprocessed gas-related data with the real-time safety constraints and output the environment judgment result. The instruction output module is used to generate control instructions for the gas extraction execution unit based on the environment judgment result. The control instructions include extraction start instructions, continuous extraction instructions, and extraction stop instructions.

[0008] Furthermore, the database includes a basic parameter database, a monitoring database, and a parameter threshold database. The basic parameter database is used to store geological condition parameters and sensor-related parameters of the coal mine goaf. The monitoring database is used to store the full process data of each extraction and the real-time gas-related data. The parameter threshold database is used to store parameter thresholds under different geological conditions.

[0009] Furthermore, the gas extraction execution unit includes an extraction pump set, a multi-channel extraction pipeline, an electrically controlled valve, and a flow regulating device. The inlet end of the multi-channel extraction pipeline is equipped with several branch nozzles, which are correspondingly arranged in different gas-rich areas of the coal mine goaf. The outlet end of the multi-channel extraction pipeline is connected to the extraction pump set. The electrically controlled valve and the flow regulating device cooperate with each other to realize the functions of opening and closing the extraction channels and regulating the extraction flow according to the control commands, and are all installed on the multi-channel extraction pipeline. The extraction pump set, the electrically controlled valve, and the flow regulating device are all electrically connected to the background processing unit.

[0010] A method for gas extraction in coal mine goaf, applied to a coal mine goaf gas extraction system, specifically includes the following steps: Step S1: The data acquisition unit is in the non-extraction state acquisition mode, collecting non-extraction monitoring data of the coal mine goaf in the non-extraction state in real time, and transmitting it to the background processing unit through the data transmission unit. Step S2: The analysis software of the background processing unit calls the gas parameter threshold and historical extraction monitoring data in the database to generate real-time safety constraints. Step S3: After processing the unextracted monitoring data, the analysis software compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for starting extraction. If it does not meet the requirements, it returns to step S1 to continue collecting unextracted monitoring data and repeating the comparison and judgment operation. If it meets the requirements, it executes step S4. Step S4: The background processing unit sends a gas extraction start command to the gas extraction execution unit to perform the gas extraction operation. At the same time, the data acquisition unit switches to the extraction status acquisition mode to collect extraction monitoring data in real time and transmit it to the background processing unit. Step S5: After processing the real-time collected gas extraction monitoring data, the analysis software compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for continuous extraction. If it does, a continuous extraction command is sent to maintain the gas extraction operation and continue to execute step S4. If it does not meet the requirements, step S6 is executed. Step S6: The background processing unit sends a stop extraction command to the gas extraction execution unit to stop the gas extraction operation. Then the data acquisition unit switches back to the non-extraction state acquisition mode and returns to step S1 to repeat the above process.

[0011] Furthermore, the specific operation of generating real-time safety constraints in step S2 includes: the constraint generation module extracts historical extraction monitoring data within 3 months and the geological condition parameters of the corresponding coal mine goaf from the database, combines the current gas parameter threshold and historical extraction monitoring data, trains a safety constraint model through a machine learning algorithm, takes the geological condition parameters of the corresponding coal mine goaf as input, and outputs real-time safety constraints including the upper limit of gas concentration, the upper limit of methane concentration, the safe range of oxygen concentration, the upper limit of carbon dioxide concentration, the ambient temperature threshold, the pressure threshold, and the safe range of gas component proportion. The machine learning algorithm adopts the random forest algorithm.

[0012] Furthermore, the specific operation in step S3 to determine whether the current coal mine goaf environment meets the requirements for starting extraction includes: extracting multi-dimensional monitoring parameters from the pre-processed non-extraction monitoring data, including the gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure and gas component ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints output by the constraint generation module one by one. If all multi-dimensional monitoring parameters at all key points meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for starting extraction. If any monitoring parameter does not meet the requirements or the continuous stable time does not meet the requirements, then the extraction start-up requirements are not met.

[0013] Furthermore, the specific operation in step S5 to determine whether the current coal mine goaf environment meets the requirements for continuous extraction includes: extracting multi-dimensional monitoring parameters from the pre-processed extraction monitoring data, including the real-time values ​​of gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure, and gas composition ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints one by one; If all monitoring parameters meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for continuous extraction. If any monitoring parameter does not meet the requirements or a parameter change occurs, then it is determined that the requirements for continuous extraction are not met.

[0014] Furthermore, it also includes a data update step: the background processing unit records the unextracted monitoring data, extracted monitoring data, geological condition parameters, environmental judgment results, and control instructions in each extraction process to the database to form new historical extraction monitoring data. The constraint generation module periodically calls the updated historical extraction monitoring data to train and optimize the safety constraint model.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention collects environmental data in real time through a data acquisition unit, and the back-end processing unit generates safety constraints based on machine learning algorithms and automatically judges the feasibility of gas extraction. It can complete the entire process control of gas extraction start-up, continuity, and stop without human intervention, eliminating the reliance on human experience in traditional gas extraction and avoiding the subjectivity and delay of human judgment, thereby improving the accuracy of gas extraction. In addition, through real-time safety constraint comparison, this invention can quickly respond to parameter changes and trigger stop extraction commands in a timely manner, effectively avoiding safety accidents such as explosions and poisoning caused by gas leaks and accumulation, and improving the safety of gas extraction. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system structure of the present invention.

[0017] Figure 2 This is a schematic diagram of the backend processing unit of the present invention.

[0018] Figure 3 This is a schematic diagram of the structure of the gas extraction execution unit of the present invention.

[0019] Figure 4 This is a schematic diagram of the method steps of the present invention.

[0020] Figure label annotations: Data acquisition unit 10, data transmission unit 20, background processing unit 30, data preprocessing module 31, constraint generation module 32, environmental judgment module 33, instruction output module 34, basic parameter library 35, monitoring database 36, parameter threshold library 37, gas extraction execution unit 40, extraction pump group 41, multi-channel extraction pipeline 42, electric control valve 43, flow regulating device 44, branch suction nozzle 45. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0022] Example 1 In this embodiment, as Figures 1-3 As shown, a coal mine goaf gas extraction system includes a data acquisition unit 10, a data transmission unit 20, a background processing unit 30, and a gas extraction execution unit 40 that communicate with each other via a network. The data acquisition unit 10 is deployed at several monitoring points in the coal mine goaf and is equipped with several sensors to collect gas-related data in the coal mine goaf in real time. The gas-related data includes non-extraction monitoring data in the non-extraction state and extraction monitoring data in the extraction state. Data transmission unit 20 is used to transmit gas-related data to background processing unit 30 in real time; The background processing unit 30 has built-in analysis software and database. The database stores gas parameter thresholds and historical drainage monitoring data. The analysis software is used to generate safety constraints based on gas parameter thresholds and historical drainage monitoring data, and to determine whether the goaf environment meets the drainage requirements by combining gas-related data, and output control commands. The gas extraction execution unit 40 is electrically connected to the background processing unit 30 and is used to execute extraction start, continuous extraction or extraction stop operations according to control commands.

[0023] In this embodiment, wherein, as Figure 1 and Figure 3As shown, the data acquisition unit 10 includes several sets of sensor components. Each set of sensor components integrates at least a gas concentration sensor, a carbon dioxide concentration sensor, a methane concentration sensor, an oxygen concentration sensor, a temperature sensor, and a pressure sensor. It also includes a flow meter for collecting pipeline flow data and a wind speed sensor for collecting gas flow velocity data inside the goaf. The sensors adopt sensor structures adapted to the harsh environmental conditions of the coal mine goaf, such as dampness, dust, and impact. All are intrinsically safe designs for mining use. The monitoring points include at least the intake air boundary, return air boundary, core area of ​​the caving zone, and areas with delamination fractures in the coal mine goaf. The monitoring points are deployed according to the principle of full coverage and no blind spots. The spacing between adjacent monitoring points can be adjusted according to actual environmental needs, such as setting the spacing to 8-10m. In addition to the above monitoring points, it also includes the return air corner of the working face and the post-mining area. The closed tail tunnel of the stone gate, the area affected by high-level drilling, and the area where boreholes are arranged along the bedding plane ensure coverage of key areas rich in gas. The data acquisition unit 10 has a non-drainage state acquisition mode and a drainage state acquisition mode. In the non-drainage state acquisition mode, the data acquisition unit 10 collects non-drainage monitoring data through several sensors. In the drainage state acquisition mode, the data acquisition unit 10 collects drainage monitoring data through several sensors. The acquisition mode of the data acquisition unit 10 is remotely controlled by the background processing unit 30. The acquisition frequency is different in the two acquisition modes. For example, in the non-drainage state, the sensor components collect data at a frequency of 10 seconds / time. In the drainage state, the acquisition frequency is increased to 5 seconds / time to ensure real-time capture of the dynamic changes of environmental parameters during the drainage process. In the non-drainage state, local sensors such as flow meters are in a dormant state.

[0024] In this embodiment, wherein, as Figure 2As shown, the analysis software includes a data preprocessing module 31, a constraint generation module 32, an environmental judgment module 33, and an instruction output module 34. The data preprocessing module 31 is used to perform noise reduction, outlier removal, and standardization on gas-related data. The processing flow of the data preprocessing module 31 is as follows: First, the wavelet transform algorithm is used to denoise the data to remove noise caused by environmental vibration and electromagnetic interference. Then, outliers (i.e., data exceeding the mean ± 3 times the standard deviation) are removed using the 3σ criterion. Finally, parameters of different dimensions are converted into standardized data in the [0,1] interval for easy comparison and analysis. The preprocessing operation is based on existing technologies and methods. The constraint generation module 32 is used to construct a safety constraint model based on gas parameter thresholds and historical extraction monitoring data in the database using machine learning algorithms, and output real-time safety constraint conditions. The inputs of the safety constraint model include geological condition parameters of the coal mine goaf, Historical gas extraction monitoring data, including but not limited to coal seam thickness, dip angle, burial depth, and roof and floor lithology, as well as gas concentration, pressure, and temperature, are used to output real-time safety constraints for the current operating conditions. The model is iteratively updated every 24 hours using newly added historical gas extraction monitoring data to improve the adaptability of the constraints. The environmental judgment module 33 compares the preprocessed gas-related data with the real-time safety constraints and outputs the environmental judgment result. The instruction output module 34 generates control instructions for the gas extraction execution unit 40 based on the environmental judgment result. The control instructions include extraction start instructions, continuous extraction instructions, and extraction stop instructions. The instruction output module 34 generates control instructions based on the environmental judgment result and waits for feedback signals from the gas extraction execution unit 40 after the control instructions are transmitted. If no feedback is received, the instructions are resent to ensure that the instructions are executed properly.

[0025] Among them, such as Figure 2 As shown, the database includes a basic parameter library 35, a monitoring database 36, and a parameter threshold library 37. The basic parameter library 35 stores geological condition parameters and sensor-related parameters of the coal mine goaf. The monitoring database 36 stores the full-process data of each extraction and the real-time gas-related data. The parameter threshold library 37 stores parameter thresholds under different geological conditions. The geological condition parameters stored in the basic parameter library 35 are imported from the geological exploration report. The sensor-related parameters (model, range, accuracy, calibration date, etc.) are updated regularly. The monitoring database 36 adopts a partitioned storage strategy. The real-time gas-related data is stored in the memory database, and the full-process data of each extraction is stored in the hard disk. The parameter threshold library 37 stores the default thresholds under different geological conditions, which can be manually adjusted by the operator according to the actual situation on site.

[0026] Among them, such as Figure 1 and Figure 3As shown, the gas extraction execution unit 40 includes an extraction pump set 41, a multi-channel extraction pipeline 42, an electric control valve 43, and a flow regulating device 44. Pressure sensors are installed at the inlet and outlet ports of the extraction pump set 41 to provide real-time feedback on the extraction negative pressure, meeting the requirements for pre-extraction of coal seam gas. The air inlet end of the multi-channel extraction pipeline 42 is equipped with several branch suction nozzles 45, which are correspondingly arranged in different gas-rich areas of the coal mine goaf. The number of branch suction nozzles 45 is greater than the number of gas-rich areas. The air outlet end of the multi-channel extraction pipeline 42 is connected to the input end of the extraction pump set 41. The electric control valve 43 and the flow regulating device 44 cooperate to realize the extraction according to the control command. The extraction passage opening and closing function and the extraction flow rate adjustment function are all installed on the multi-pass extraction pipeline 42. The extraction pump set 41, the electric control valve 43 and the flow adjustment device 44 are all electrically connected to the background processing unit 30. When the gas extraction execution unit 40 receives the extraction start command from the background processing unit 30, the electric control valve 43 acts first to open the corresponding extraction passage, and then the extraction pump set 41 starts. The flow adjustment device 44 adjusts the extraction flow rate according to the command. During the extraction process, the valve status and flow data are fed back to the background processing unit 30 in real time for real-time monitoring. The output end of the extraction pump set 41 is connected to the gas storage device for temporary gas storage.

[0027] Specifically, the main extraction pipeline of the multi-path extraction pipeline 42 adopts a Φ300mm extraction pipe, and the branch pipelines use Φ150mm iron pipes with a perforated pipe design at the end and wrapped with mesh. The external connection is a Φ150mm spring hose, and the end of the hose is connected to the main extraction pipeline. In the high-level drilling area, the branch suction nozzles 45 are arranged corresponding to the drilling end position. In the layer drilling area, the branch suction nozzles 45 are set synchronously according to the drilling spacing to ensure that each gas enrichment area has a corresponding extraction path. Orifice plate flow meters are installed on the main extraction pipeline and the branch pipelines to monitor the extraction flow of each branch in real time. The electric control valve 43 is linked with the flow adjustment device 44. Different flow adjustment ranges are preset for different processes such as high-level drilling extraction and buried pipe extraction, and are dynamically adjusted according to the instructions of the background processing unit 30.

[0028] Example 2 In this embodiment, as Figure 4 As shown, the present invention also provides a method for gas extraction in coal mine goaf areas, applied to a coal mine goaf gas extraction system, specifically including the following steps: Step S1: The data acquisition unit 10 is in the non-extraction state acquisition mode, collecting non-extraction monitoring data of the coal mine goaf in the non-extraction state in real time, and transmitting it to the background processing unit 30 through the data transmission unit 20. Step S2: The analysis software of the background processing unit 30 calls the gas parameter threshold and historical extraction monitoring data in the database to generate real-time safety constraints. Step S3: After the analysis software processes the unextracted monitoring data, it compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for starting extraction. If it does not meet the requirements, it returns to step S1 to continue collecting unextracted monitoring data and repeating the comparison and judgment operation. If it meets the requirements, it executes step S4. When judging the extraction start-up requirements, it also includes a verification step of the extraction pipeline status to confirm whether the pipeline joints are tight and leak-free, and whether components such as orifice plate flow meters, electric control valves 43 and flow regulating devices 44 are installed in place. If there are any verification failures, an early warning command is output, and the judgment process is restarted after the on-site rectification is completed. Step S4: The background processing unit 30 sends a gas extraction start command to the gas extraction execution unit 40 to perform the gas extraction operation. At the same time, the data acquisition unit 10 switches to the extraction status acquisition mode to collect extraction monitoring data in real time and transmit it to the background processing unit 30. Step S5: After the analysis software processes the real-time collected gas extraction monitoring data, it compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for continuous extraction. If it does, a continuous extraction command is sent to maintain the gas extraction operation and continue to execute step S4. If it does not meet the requirements, step S6 is executed. Step S6: The background processing unit 30 sends a stop extraction command to the gas extraction execution unit 40 to stop the gas extraction operation. Then the data acquisition unit 10 switches back to the non-extraction state acquisition mode and returns to step S1 to repeat the above process.

[0029] Among them, such as Figure 4As shown, the specific operations for generating real-time safety constraints in step S2 include: the constraint generation module 32 extracts historical extraction monitoring data and corresponding geological condition parameters of the coal mine goaf from the database within the past three months. Using the historical extraction monitoring data from the past three months as a training set, and combining the current gas parameter threshold and historical extraction monitoring data, a safety constraint model is trained using a machine learning algorithm. The input is the geological condition parameters of the corresponding coal mine goaf, labeled "whether extraction is permitted." The output is a real-time safety constraint including the upper limit of gas concentration, the upper limit of methane concentration, the safe range of oxygen concentration, the upper limit of carbon dioxide concentration, the ambient temperature threshold, the pressure threshold, and the safe range of gas component proportion. The safe range of gas component proportion refers to... The safe threshold ranges for the volume concentration of each component in the gas in the goaf are as follows: the safe range for methane (CH4) is usually ≥40%. A value lower than this may indicate that the gas concentration is too low or that air is mixed in, affecting extraction efficiency and safety. The safe range for carbon dioxide (CO2) is usually ≤30%. A value higher than this may indicate the risk of spontaneous combustion of coal or abnormal gas outburst. The safe range for oxygen (O2) is between 18% and 22%. A value lower than 18% may lead to the risk of asphyxiation, while a value higher than 22% may increase the risk of gas explosion. The above ranges can be dynamically adjusted according to different coal seam conditions, goaf structure, and historical extraction data, and are an important part of real-time safety constraints, participating in the judgment of extraction start and stop.

[0030] In this embodiment, the machine learning algorithm preferably adopts the random forest algorithm. The random forest algorithm can effectively process high-dimensional data and determine whether it belongs to the "sampling" or "non-sampling" category. It supports incremental learning and rapid model updates, which makes it convenient for the system to periodically use newly added historical sampling monitoring data to iteratively optimize the model.

[0031] Among them, such as Figure 4 As shown, the specific operation in step S3 to determine whether the current coal mine goaf environment meets the requirements for starting extraction includes: extracting multi-dimensional monitoring parameters from the pre-processed non-extraction monitoring data, including the gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure and gas component ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints output by the constraint generation module 32 one by one.

[0032] In this embodiment, real-time safety constraints refer to a set of dynamic thresholds output by the constraint generation module 32 to determine whether the current goaf environment allows extraction. These thresholds include, but are not limited to: upper limit of gas concentration (e.g., ≤30%), upper limit of methane concentration (e.g., ≤15%), safe range of oxygen concentration (e.g., 18%~22%), upper limit of carbon dioxide concentration (e.g., ≤5%), ambient temperature threshold (e.g., ≤40%), pressure threshold (e.g., ≤105kPa), and safe range of gas component proportion (e.g., methane proportion ≥40%, carbon dioxide proportion ≤30%). If the monitored parameters remain below the parameter thresholds for 10 minutes, extraction is allowed to start. If the monitored parameters at any monitoring point, such as oxygen concentration, are below 18% or above 22%, extraction is immediately stopped. The real-time safety constraints are dynamically adjusted according to the current geological conditions, historical extraction data, and environmental changes to ensure the real-time nature and safety of extraction decisions.

[0033] If all multi-dimensional monitoring parameters at all key points meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for starting extraction. If any monitoring parameter does not meet the requirements or the continuous stable time does not meet the requirements, then the extraction start-up requirements are not met.

[0034] In this embodiment, the specific operation of determining whether the current coal mine goaf environment meets the requirements for continuous extraction in step S5 includes: extracting multi-dimensional monitoring parameters from the pre-processed extraction monitoring data, including the real-time values ​​of gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure and gas composition ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints one by one.

[0035] If all monitoring parameters meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for continuous extraction. If any monitoring parameter does not meet the requirements or a parameter change occurs, then it is determined that the requirements for continuous extraction are not met.

[0036] Specifically, the data preprocessing module 31 of the analysis software first verifies the real-time sampling monitoring data transmitted by the data acquisition unit 10, removes extreme data caused by instantaneous sensor failures, fills in missing values ​​caused by data transmission packet loss, and compares the same parameters collected by different sensors in the same monitoring area. If the deviation exceeds 15%, a second acquisition verification is initiated to eliminate the risk of misjudgment caused by a single sensor failure. The preset time threshold is 10 minutes, and a comprehensive judgment is made in combination with the environmental judgment results. Level 1 judgment: If any of the multi-dimensional monitoring parameters does not meet the threshold requirement or the continuous stable time does not meet the preset time threshold, it is directly judged as "not meeting the continuous sampling requirements" and a stop sampling command is immediately triggered. Secondary judgment: If the multi-dimensional monitoring parameters and continuous stable time are all met, it is judged as "meeting the requirements for continuous sampling", the current sampling operation is maintained and the next round of real-time data collection and judgment cycle is entered.

[0037] In this embodiment, a data update step is also included: the background processing unit 30 records the non-extraction monitoring data, extraction monitoring data, geological condition parameters, environmental judgment results, and control instructions in each extraction process to the database to form new historical extraction monitoring data. The constraint condition generation module 32 periodically calls the updated historical extraction monitoring data to train and optimize the safety constraint model. The data update cycle can be set to 24 hours, and this time can be adjusted according to actual needs.

[0038] In this embodiment, an emergency response step is also included: when the sensor detects a sharp increase in gas concentration or a sudden change in parameters, the background processing unit 30 sends a stop extraction command to the gas extraction execution unit 40, cuts off the power supply to the threatened area through remote control, sends emergency warning information to the dispatch center, including data such as abnormal area, real-time gas concentration, and geological conditions, and simultaneously starts sensor positioning and tracking to continuously collect data of the abnormal area and push it to on-site personnel through communication equipment.

[0039] In summary, this invention constructs a coal mine goaf gas extraction system through the coordinated cooperation of various units and proposes a corresponding extraction method. This system and method solve the problem that the existing gas extraction system relies heavily on manual experience, which makes it impossible to accurately judge the extraction degree and the timing of extraction shutdown. Through real-time data acquisition, safety constraint generation, comparison and judgment, and execution of command operations, the overall gas extraction operation process is realized, and it has good application prospects.

[0040] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A coal mine goaf gas extraction system, characterized in that, It includes a data acquisition unit (10), a data transmission unit (20), a background processing unit (30), and a gas extraction execution unit (40) that communicate with each other via a network. The data acquisition unit (10) is set up at several monitoring points in the coal mine goaf and is equipped with several sensors for real-time collection of gas-related data in the coal mine goaf. The gas-related data includes non-extraction monitoring data in the non-extraction state and extraction monitoring data in the extraction state. The data transmission unit (20) is used to transmit gas-related data to the background processing unit (30) in real time. The background processing unit (30) has built-in analysis software and database. The database stores gas parameter thresholds and historical extraction monitoring data. The analysis software is used to generate safety constraints based on gas parameter thresholds and historical extraction monitoring data, and to determine whether the goaf environment meets the extraction requirements in combination with gas-related data, and output control commands. The gas extraction execution unit (40) is electrically connected to the background processing unit (30) and is used to execute extraction start, continuous extraction or extraction stop operations according to control instructions.

2. A coal mine goaf gas extraction system according to claim 1, characterized in that, The data acquisition unit (10) includes several sets of sensor components. Each set of sensor components integrates at least a gas concentration sensor, a carbon dioxide concentration sensor, a methane concentration sensor, an oxygen concentration sensor, a temperature sensor, and a pressure sensor. The monitoring points include at least the air intake side boundary, the return air side boundary, the core area of ​​the caving zone, and the area with delamination fracture development in the coal mine goaf. The data acquisition unit (10) is equipped with a non-extraction state acquisition mode and an extraction state acquisition mode. In the non-extraction state acquisition mode, the data acquisition unit (10) collects non-extraction monitoring data in the non-extraction state through several sensors. In the extraction state acquisition mode, the data acquisition unit (10) collects extraction monitoring data in the extraction state through several sensors.

3. A coal mine goaf gas extraction system according to claim 1, characterized in that, The analysis software includes a data preprocessing module (31), a constraint generation module (32), an environment judgment module (33), and an instruction output module (34). The data preprocessing module (31) is used to perform noise reduction, outlier removal, and standardization on the gas-related data. The constraint generation module (32) is used to construct a safety constraint model based on the gas parameter thresholds and historical extraction monitoring data in the database, and output real-time safety constraint conditions. The environment judgment module (33) is used to compare the preprocessed gas-related data with the real-time safety constraint conditions and output the environment judgment result. The instruction output module (34) is used to generate control instructions for the gas extraction execution unit (40) based on the environment judgment result. The control instructions include extraction start instructions, continuous extraction instructions, and extraction stop instructions.

4. A coal mine goaf gas extraction system according to claim 1, characterized in that, The database includes a basic parameter database (35), a monitoring database (36), and a parameter threshold database (37). The basic parameter database (35) is used to store geological condition parameters and sensor-related parameters of the coal mine goaf. The monitoring database (36) is used to store the full process data of each extraction and the real-time gas-related data. The parameter threshold database (37) is used to store parameter thresholds under different geological conditions.

5. A coal mine goaf gas extraction system according to claim 1, characterized in that, The gas extraction execution unit (40) includes an extraction pump group (41), a multi-channel extraction pipeline (42), an electric control valve (43), and a flow regulating device (44). The air inlet end of the multi-channel extraction pipeline (42) is provided with several branch suction nozzles (45). The branch suction nozzles (45) are arranged in different gas-rich areas in the goaf of the coal mine. The air outlet end of the multi-channel extraction pipeline (42) is connected to the extraction pump group (41). The electric control valve (43) and the flow regulating device (44) cooperate with each other to realize the opening and closing of the extraction channel and the adjustment of the extraction flow according to the control command. They are all installed on the multi-channel extraction pipeline (42). The extraction pump group (41), the electric control valve (43), and the flow regulating device (44) are all electrically connected to the background processing unit (30).

6. A method for gas extraction from goaf areas in coal mines, applied to a gas extraction system for goaf areas in coal mines as described in any one of claims 1-5, characterized in that, Specifically, the following steps are included: Step S1: The data acquisition unit (10) is in the non-extraction state acquisition mode, and collects the non-extraction monitoring data of the coal mine goaf in the non-extraction state in real time, and transmits it to the background processing unit (30) through the data transmission unit (20). Step S2: The analysis software of the background processing unit (30) calls the gas parameter threshold and historical extraction monitoring data in the database to generate real-time safety constraints. Step S3: After processing the unextracted monitoring data, the analysis software compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for starting extraction. If it does not meet the requirements, it returns to step S1 to continue collecting unextracted monitoring data and repeating the comparison and judgment operation. If it meets the requirements, it executes step S4. Step S4: The background processing unit (30) sends a gas extraction start command to the gas extraction execution unit (40) to perform gas extraction operation. At the same time, the data acquisition unit (10) switches to the extraction status acquisition mode to collect extraction monitoring data in real time and transmit it to the background processing unit (30). Step S5: After processing the real-time collected gas extraction monitoring data, the analysis software compares it with the real-time safety constraints to determine whether the current coal mine goaf environment meets the requirements for continuous extraction. If it does, a continuous extraction command is sent to maintain the gas extraction operation and continue to execute step S4. If it does not meet the requirements, step S6 is executed. Step S6: The background processing unit (30) sends a stop extraction command to the gas extraction execution unit (40) to stop the gas extraction operation. Then the data acquisition unit (10) switches back to the non-extraction state acquisition mode and returns to step S1 to repeat the above process.

7. A method for gas extraction from goaf areas in coal mines according to claim 6, characterized in that, The specific operation of generating real-time safety constraints in step S2 includes: the constraint generation module (32) extracts historical mining monitoring data within 3 months and geological condition parameters of the corresponding coal mine goaf from the database, combines the current gas parameter threshold and historical mining monitoring data, trains a safety constraint model through a machine learning algorithm, inputs the geological condition parameters of the corresponding coal mine goaf, and outputs real-time safety constraints including the upper limit of gas concentration, the upper limit of methane concentration, the safe range of oxygen concentration, the upper limit of carbon dioxide concentration, the environmental temperature threshold, the pressure threshold and the safe range of gas component proportion. The machine learning algorithm adopts the random forest algorithm.

8. A method for gas extraction from goaf areas in coal mines according to claim 7, characterized in that, The specific operation of determining whether the current coal mine goaf environment meets the requirements for starting extraction in step S3 includes: extracting multi-dimensional monitoring parameters from the pre-processed non-extraction monitoring data, including the gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure and gas component ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints output by the constraint generation module (32) one by one. If all multi-dimensional monitoring parameters at all key points meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for starting extraction. If any monitoring parameter does not meet the requirements or the continuous stable time does not meet the requirements, then the extraction start-up requirements are not met.

9. A method for gas extraction from goaf areas in coal mines according to claim 8, characterized in that, The specific operation in step S5 to determine whether the current coal mine goaf environment meets the requirements for continuous extraction includes: extracting multi-dimensional monitoring parameters from the pre-processed extraction monitoring data, including real-time values ​​of gas concentration, methane concentration, oxygen concentration, ambient temperature, gas pressure, and gas composition ratio at each key point, and comparing the multi-dimensional monitoring parameters with the real-time safety constraints one by one. If all monitoring parameters meet the real-time safety constraints and the continuous stable time meets the preset time threshold, then the current coal mine goaf environment is determined to meet the requirements for continuous extraction. If any monitoring parameter does not meet the requirements or a parameter change occurs, then it is determined that the requirements for continuous extraction are not met.

10. A method for gas extraction from a coal mine goaf according to claim 7, characterized in that, It also includes a data update step: the background processing unit (30) records the unextracted monitoring data, extraction monitoring data, geological condition parameters, environmental judgment results and control instructions in each extraction process to the database to form new historical extraction monitoring data. The constraint generation module (32) periodically calls the updated historical extraction monitoring data to train and optimize the safety constraint model.

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