Drainage and drainage system and method based on multi-dimensional linkage intelligent monitoring in underground mines

Abstract

A multi-dimensional, intelligent monitoring system and method for drainage and flood control in underground mines is disclosed. The system comprises: an atmospheric precipitation monitoring module installed at the mine surface; a surface water monitoring module installed at the mine surface and in subsidence areas; a groundwater monitoring module installed in mined-out areas and karst caves; a water inflow monitoring module installed at known water inflow points within the mine; a water level monitoring module installed in the water reservoir; an environmental monitoring module installed at the mine surface; an automated control module connected to each drainage pump group; and an intelligent analysis and decision-making module connected to the atmospheric precipitation monitoring module, surface water monitoring module, groundwater monitoring module, water inflow monitoring module, water level monitoring module, environmental monitoring module, automated control module, and early warning module. The method involves establishing a dynamic risk assessment model and obtaining dynamic risk levels; and formulating drainage strategies. This system and method enable drainage process control based on a multi-dimensional, intelligent control approach.

Description

Technical Field

[0001] This invention belongs to the field of smart mine safety and disaster prevention technology, specifically a drainage system and method based on multi-dimensional linkage intelligent monitoring in underground mines. Background Technology

[0002] Mine water inrush is a significant factor jeopardizing mine safety. Once underground water seepage or flooding occurs, it not only disrupts normal production but also seriously endangers the lives of miners. The main factors influencing mine water inrush include atmospheric precipitation, surface water, and groundwater. In the event of a mine water inrush, the water must be promptly drained to the surface through the mine drainage system. Real-time intelligent monitoring and analysis of the dynamic correlation between underground water inrush and atmospheric precipitation, surface water, and groundwater is of paramount importance. This monitoring and analysis process can provide reliable support and guidance for digital monitoring and prevention of mine water pollution, as well as automated and intelligent drainage of water storage facilities. It is of utmost significance for strengthening mine water control, preventing water-related accidents, and building smart mines.

[0003] Currently, most mines in China lack systematic intelligent monitoring systems and methods for water prevention and control. Water discharge from mine sump is currently carried out solely based on worker experience, without automation. This results in low automation and accuracy, making it difficult to pinpoint the precise timing of sump discharge. This can easily lead to water-related accidents when mine water inflow is high. While some mines have installed automated drainage systems, these systems merely interlock the mine sump water level with the pump's operation, only automating the "discharge" process. They fail to systematically consider the dynamic correlation between atmospheric rainfall, surface water, and groundwater on underground water inflow, thus failing to provide effective "prevention" and hindering integrated control of mine water prevention and drainage. Therefore, there is an urgent need for a multi-dimensional, interconnected, intelligent monitoring system and method for water prevention and drainage. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a multi-dimensional, intelligent monitoring system and method for mine drainage and flood control in underground mines. This system boasts a high degree of intelligence and automation, possessing proactive prevention and control capabilities. It enables dynamic monitoring and intelligent management of mine water inflow, significantly improving the intelligence level, control and management capabilities, and drainage efficiency of coal mine drainage systems. This effectively reduces the risk of mine water hazards and significantly reduces the labor intensity and monitoring difficulty for workers. The method also features a high degree of intelligence, enabling highly intelligent management and control of dynamic monitoring and drainage operations for mine water inflow. It can perform intelligent, tiered, and dynamic drainage operations when water inflow occurs, and simultaneously provide linked early warning and alert actions, effectively reducing the risk of mine water hazards and significantly improving the safety of mine production.

[0005] To achieve the above objectives, the present invention provides a multi-dimensional linkage intelligent monitoring system for drainage in underground mines, including a water tank, several drainage pumps, an atmospheric rainfall monitoring module, a surface water monitoring module, a groundwater monitoring module, a water inflow monitoring module, a water tank level monitoring module, an environmental monitoring module, an automated control module, an early warning module, and an intelligent analysis and decision-making module.

[0006] The drainage pumps are divided into three groups: a surface water drainage pump group, a groundwater drainage pump group, and a water tank drainage pump group; the surface water drainage pump group consists of multiple surface water pumps; the groundwater drainage pump group consists of multiple groundwater pumps; and the water tank drainage pump group consists of multiple water tank pumps.

[0007] The atmospheric precipitation monitoring module is installed at the surface of the mining area; the surface water monitoring module is installed at the surface of the mining area and in the subsidence area; the groundwater monitoring module is installed in the mined-out area and karst caves of the mining area; the water inflow monitoring module is installed at known water inflow points in the mining area; the water level monitoring module is installed in the water tank; the environmental monitoring module is installed at the surface of the mining area; the automatic control module is connected to the surface water drainage pump group, the groundwater drainage pump group, and the water tank drainage pump group respectively.

[0008] The intelligent analysis and decision-making module is connected to the atmospheric rainfall monitoring module, surface water monitoring module, groundwater monitoring module, water inflow monitoring module, water reservoir level monitoring module, environmental monitoring module, automated control module, and early warning module, respectively.

[0009] Preferably, the atmospheric precipitation monitoring module is a high-precision rain gauge. The environmental monitoring module includes a temperature sensor, a humidity sensor, and a wind speed sensor.

[0010] As a preferred embodiment, the surface water monitoring module comprises a surface water level sensor and a millimeter-wave radar level gauge. The surface water level sensor is installed on the surface of the mining area to monitor the surface water accumulation signal, and the millimeter-wave radar level gauge is installed in the subsidence area of ​​the mining area to monitor the water accumulation signal in the subsidence area.

[0011] As a preferred embodiment, the groundwater monitoring module comprises a goaf water level sensor and a karst cave water level sensor. The goaf water level sensor is installed in the goaf to monitor the goaf water level signal, and the karst cave water level sensor is installed in the karst cave to monitor the karst cave water level signal.

[0012] As a preferred embodiment, the water flow monitoring module includes a flow rate meter.

[0013] As a preferred embodiment, the water tank level monitoring module includes a water tank level sensor.

[0014] As a preferred embodiment, the system also includes a power supply module, a communication module, and a remote monitoring terminal. The power supply module is connected to the intelligent analysis and decision-making module for supplying power, and the communication module is connected to the intelligent analysis and decision-making module to establish communication connections between the intelligent analysis and decision-making module and external devices. This facilitates unattended operation and remote management, further improving the mine's production efficiency and water hazard prevention capabilities.

[0015] In this invention, an atmospheric precipitation monitoring module is deployed at the surface of the mining area to facilitate real-time monitoring of atmospheric precipitation signals; a surface water monitoring module is deployed at the surface of the mining area and in the subsidence area to facilitate real-time monitoring of surface water accumulation signals and subsidence area water accumulation signals; a groundwater monitoring module is deployed in the goaf and karst caves of the mining area to facilitate real-time monitoring of goaf and karst cave water level signals; a water inflow monitoring module is deployed at known water inflow points in the mining area to facilitate real-time monitoring of water inflow signals; a water level monitoring module is deployed in the water tank to facilitate real-time monitoring of water tank water level signals; and an environmental monitoring module is set up to facilitate real-time monitoring of environmental temperature, humidity, and wind speed signals. By configuring the intelligent analysis and decision-making module, it can not only obtain data on atmospheric rainfall, surface water accumulation, subsidence area water accumulation, goaf water level, karst cave water level, water inflow, water reservoir water level, temperature, humidity, and wind speed in the mining area, but also integrate real-time monitoring data through the built-in dynamic risk assessment module to determine the dynamic risk level, thereby quantifying the mine water inflow risk level. Furthermore, the intelligent analysis and decision-making module can also determine the impact of current rainfall on water reservoir capacity, thus generating control commands for water reservoir drainage in advance, optimizing water reservoir capacity management, and ensuring the efficient and smooth drainage of surface and groundwater. By configuring the automated control module, multi-dimensional intelligent control can be implemented for underground drainage pump sets, surface water drainage pump sets, and water tank pump sets. This further enhances the system's intelligence level and allows for dynamic adjustment of the control input signals of each drainage pump, which is beneficial for optimizing drainage strategies. While improving drainage efficiency, it also significantly reduces energy consumption, achieving energy-saving management. Therefore, this system encompasses multi-dimensional online monitoring of atmospheric precipitation, surface water, and groundwater, and can combine dynamic risk assessment with multi-dimensional linkage control to achieve integrated intelligent management of flood prevention and drainage. This enables high-precision prevention and control of mine water hazards, significantly improving the proactive prevention and control capabilities of mine water hazards.

[0016] This system boasts a high degree of intelligence and automation. Through a multi-dimensional monitoring architecture and intelligent control system, it achieves informatization and digitization of the monitoring process and possesses proactive prevention and control capabilities. It enables dynamic monitoring and intelligent management of mine water inflow, significantly improving the intelligence level, control and prevention capabilities, and drainage efficiency of coal mine drainage systems. This effectively reduces the risk of mine water hazards and significantly reduces the labor intensity and monitoring difficulty for workers. It solves the problems of low automation and lack of multi-dimensional linkage control in existing underground mine drainage systems, effectively ensuring the safety of coal mine production.

[0017] This invention also provides a drainage and flood control method based on multi-dimensional linkage intelligent monitoring in underground mines, employing a drainage and flood control system based on multi-dimensional linkage intelligent monitoring in underground mines, comprising the following steps:

[0018] Step 1: Collect historical atmospheric rainfall data for the mining area and establish a rainfall prediction model for the mining area based on the historical atmospheric rainfall data;

[0019] Step Two: Utilize high-precision rain gauges installed on the mine surface to monitor atmospheric rainfall signals in real time and send them to the intelligent analysis and decision-making module; utilize surface water level sensors installed on the mine surface to monitor surface water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize millimeter-wave radar level gauges installed in the mine subsidence area to monitor subsidence area water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize goaf water level sensors installed in the goaf area to monitor goaf water level signals in real time and send them to the intelligent analysis and decision-making module. The module includes: a cave water level sensor installed in the cave to monitor the cave water level signal in real time and send it to the intelligent analysis and decision-making module; a water inflow monitoring module installed at known water inflow points to monitor the water inflow signal in real time and send it to the intelligent analysis and decision-making module; a water tank water level sensor installed in the water tank to monitor the water tank water level signal in real time and send it to the intelligent analysis and decision-making module; and temperature, humidity, and wind speed sensors installed in the mining area to monitor the temperature, humidity, and wind speed signals in real time and send them to the intelligent analysis and decision-making module.

[0020] Step 3: The intelligent analysis and decision-making module obtains atmospheric rainfall data Q1 in the mining area based on atmospheric rainfall signals; it obtains surface water accumulation data Q21 based on surface water volume signals in the mining area, and subsidence area water accumulation data Q22 based on subsidence area water accumulation signals. The total surface water accumulation Q2 is obtained by summing surface water accumulation data Q21 and subsidence area water accumulation data Q22; it obtains subsidence area water accumulation data Q31 based on goaf water level signals, and karst cave water accumulation data Q32 based on karst cave water level signals. The total underground water accumulation Q3 is obtained by summing subsidence area water accumulation data Q31 and karst cave water accumulation data Q32; it obtains total mine water inflow Q4 based on monitored water inflow signals; it obtains water accumulation in water sump Q51 based on water sump water level signals; and it obtains temperature data, humidity data, and wind speed data based on temperature signals, humidity signals, and wind speed signals.

[0021] Simultaneously, the atmospheric rainfall data Q1, current temperature data, humidity data, and wind speed data of the mining area are input into the mining area rainfall prediction model. The model is then used to predict future rainfall, yielding the future rainfall prediction data Q1. 预测 (t);

[0022] Step 4: Establish a dynamic risk assessment model based on formula (1) and obtain the dynamic risk level R(t);

[0023]

[0024] In the formula, Q1(t) represents real-time atmospheric rainfall data in the mining area; Q2(t) represents real-time total surface water accumulation; Q3(t) represents real-time total groundwater accumulation; Q4(t) represents real-time total mine water inflow; Q5 represents the total capacity of the water reservoir; Q1 警 This indicates the preset warning threshold for atmospheric rainfall in the mining area; Q2 警 The preset warning threshold for total surface water accumulation; Q3 警 Q1 represents the preset warning threshold for the total groundwater accumulation; 极 β represents the historical extreme values ​​of atmospheric rainfall data in the mining area; β represents the prediction adjustment coefficient of the rainfall prediction model in the mining area, with a value range of 0.1 to 0.3, which is used to adjust the impact of future rainfall on current risks.

[0025] Step 5: Develop a drainage strategy based on the dynamic risk level R(t). When R(t) < 0.5, it is determined to be a low-risk level L1. Maintain the current normal drainage status, generate a low-risk early warning command, and send it to the early warning module.

[0026] When 0.5≤R(t)<1.0, it is judged as a medium risk level L2. A control command is generated to start some of the surface water drainage pump group and groundwater drainage pump group to carry out drainage operations according to the set ratio and sent to the automation control module. At the same time, a medium warning command is generated and sent to the warning module.

[0027] When R(t)≥1.0, it is judged as L3 high risk, and a control command is generated to start all surface water drainage pump groups and drainage pumps in groundwater drainage pump groups to carry out drainage operations, and sent to the automation control module. At the same time, an emergency warning command is generated and sent to the warning module.

[0028] Meanwhile, when R(t)≥0.5, based on Bayesian theory and historical rainfall data, the impact of future rainfall on the reservoir capacity is calculated according to formula (2), and the probability P of starting the reservoir drainage pump group in advance for drainage is predicted. 排水 (t), when P 排水 When (t)≥0.5, a control command is generated to start the water tank drainage pump group for drainage operation and sent to the automation control module;

[0029]

[0030] Step Six: Upon receiving a control command to activate a portion of the surface water drainage pump group and groundwater drainage pump group according to a set ratio, the automation control module controls the activation of a portion of the surface water pump group to drain surface water from the mining area, and controls the activation of a portion of the groundwater pump group to drain groundwater from the mining area, until R(t) < 0.5. Upon receiving a control command to activate all surface water drainage pump groups and groundwater drainage pump groups, the module controls the activation of all drainage pumps in the surface water drainage pump group to drain surface water from the mining area, and controls the activation of all drainage pumps in the groundwater drainage pump group to drain groundwater from the mining area, until R(t) < 0.5. Upon receiving a control command to activate the water tank drainage pump group, the module controls the activation of all drainage pumps in the water tank drainage pump group to drain water from the water tank, until R(t) < 0.5.

[0031] Meanwhile, during the synchronous operation of the surface water drainage pump group, the groundwater drainage pump group and the water tank drainage pump group, based on the finite time consistency theory of multi-agent systems, the control input for the simultaneously operating surface water pump, groundwater pump and water tank pump is obtained according to formula (3) to achieve multi-dimensional linkage intelligent control.

[0032]

[0033] Where u i (t) represents the control input of the i-th drainage pump; xi Indicates the current state of the i-th drainage pump; x N+1 Indicates the target state; k represents the control gain, used to adjust the system's response speed; a ij Indicates the connection weight between multiple drainage pumps; b i This represents the weight between the drainage pump and the target state; α represents the predictive adjustment coefficient, ranging from 0.1 to 0.5, used to adjust the current drainage strategy based on future rainfall.

[0034] Meanwhile, upon receiving a low-risk warning instruction, the early warning module executes low-risk warning actions; upon receiving a medium-risk warning instruction, it executes medium-risk warning actions; and upon receiving an emergency warning instruction, it executes emergency risk warning actions, so as to effectively remind relevant management personnel to take timely and effective countermeasures.

[0035] Furthermore, to improve the accuracy of dynamic risk assessment, in step four, Q1 警 Values ​​are taken from 60% to 70% of the historical maximum atmospheric precipitation data for the mining area; Q2 警 Values ​​are taken as 70%–80% of the historical maximum total surface water volume; Q3 警 The value is taken as 70% to 80% of the historical maximum total groundwater volume.

[0036] This invention establishes a rainfall prediction module for mining areas based on historical atmospheric rainfall data, facilitating accurate and effective prediction of future rainfall. Simultaneously, addressing the current lack of online monitoring and early warning capabilities for key factors such as atmospheric rainfall, surface water, and groundwater in underground mines, this method provides a comprehensive monitoring and early warning solution. It achieves real-time online monitoring of multi-dimensional parameters such as atmospheric rainfall, surface water, and groundwater, effectively solving the problem of insufficient or inaccurate meteorological and hydrological data in mines, and providing strong support for safe mine production. Furthermore, by integrating real-time monitoring data, historical extreme values, and predicted future rainfall through a dynamic risk assessment model, dynamic risk assessment is conducted. This not only considers the current water situation but also effectively combines future rainfall prediction data and historical data, ensuring more accurate and reliable risk assessment results. This assessment process can accurately quantify the risk level of mine water inrush, and then formulate appropriate drainage strategies based on different risk levels, achieving scientific management of the drainage process, significantly reducing drainage energy consumption, and ensuring the safe operation of mine production. After the automated control module receives control commands from the intelligent analysis and decision-making module based on different risk levels, it further optimizes the control inputs of simultaneously operating surface water pumps, groundwater pumps, and reservoir pumps based on the finite-time consistency theory of multi-agent systems. Through multi-dimensional linkage intelligent control, the actions of multiple operating drainage pumps can be dynamically adjusted, effectively optimizing the response of each pump. Thus, this method, by combining dynamic risk assessment and multi-dimensional linkage control, achieves hierarchical and coordinated control of groundwater drainage, surface water drainage, and reservoir drainage. This allows for dynamic adjustment of the actions of each operating drainage pump according to the risk level, greatly improving the efficiency of drainage operations and significantly reducing overall energy consumption during the drainage process. Furthermore, in situations of L2 medium risk and L3 high risk, the impact of future rainfall on reservoir capacity can be predicted based on Bayesian theory and historical rainfall data. This enables advance prediction of reservoir capacity, allowing for the early activation of reservoir drainage pumps. Consequently, it effectively optimizes reservoir capacity management during surface water and groundwater drainage, significantly enhancing the foresight and proactiveness of prevention and control.

[0037] This invention overcomes the limitations of traditional single-dimensional monitoring by innovatively integrating dynamic risk assessment, predictive control, and multi-agent collaborative algorithms. It enables an integrated intelligent management process for mine flood control and drainage, significantly improving the response efficiency of water hazard early warning. Simultaneously, it effectively optimizes the utilization rate of water storage capacity, significantly enhancing the intelligence level and proactive water hazard prevention capabilities of mine flood control and drainage systems. This highly intelligent method enables dynamic monitoring and drainage operations of mine water inflows, and allows for intelligent, tiered, dynamic drainage operations in the event of water inflows. Furthermore, it provides linked early warning alerts, effectively reducing the risk of mine water hazards and significantly improving the safety of mine production. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the system portion of this invention. Detailed Implementation

[0039] The invention will now be further described with reference to the accompanying drawings.

[0040] like Figure 1 As shown, the present invention provides a drainage system based on multi-dimensional linkage intelligent monitoring in underground mines, including a water tank, several drainage pumps, an atmospheric rainfall monitoring module, a surface water monitoring module, a groundwater monitoring module, a water inflow monitoring module, a water tank water level monitoring module, an environmental monitoring module, an intelligent analysis and decision-making module, an automated control module, and an early warning module;

[0041] The water tank is used to store direct drainage from surface and underground drainage pumps, and to treat the drainage by sedimentation and filtration.

[0042] The drainage pumps are divided into three groups: surface water drainage pump group, groundwater drainage pump group, and water tank drainage pump group.

[0043] The surface water drainage pump set consists of multiple surface water pumps, which are arranged in sequence near multiple surface water pumping points. The suction pipes connected to the inlets of the pumps extend to the multiple surface water pumping points, and the drainage pipes connected to the outlets of the pumps are connected to the inlet of the water tank.

[0044] The groundwater drainage pump set consists of multiple groundwater pumps, which are arranged in sequence near multiple underground pumping points. The suction pipes connected to the pumps' inlets extend to the multiple underground pumping points, and the drainage pipes connected to the pumps' outlets are connected to the inlet of the water tank.

[0045] The water tank drainage pump group consists of multiple water tank pumps, which are arranged sequentially near the water tank. The suction pipes connected to the water inlets are connected to multiple water outlets at the bottom of the water tank, and the drainage pipes connected to the water outlets extend to the target drainage collection area.

[0046] The atmospheric precipitation monitoring module is installed on the surface of the mining area to monitor atmospheric precipitation signals in real time and send them to the intelligent analysis and decision-making module.

[0047] The surface water monitoring module is installed on the surface of the mining area and in the subsidence area to monitor the total surface water volume signal in the mining area in real time and send it to the intelligent analysis and decision-making module.

[0048] The groundwater monitoring module is installed in the goaf and karst caves of the mining area to monitor the groundwater level signal in real time and send it to the intelligent analysis and decision-making module.

[0049] The water inflow monitoring module is installed at known water inflow points in the mining area to monitor water inflow signals in real time and send them to the intelligent analysis and decision-making module.

[0050] The water level monitoring module is installed in the water tank to monitor the water level signal in real time and send it to the intelligent analysis and decision-making module.

[0051] The environmental monitoring module is installed on the surface of the mining area to monitor the temperature, humidity and wind speed signals in the mining area in real time and send them to the intelligent analysis and decision-making module.

[0052] The intelligent analysis and decision-making module is connected to the atmospheric rainfall monitoring module, surface water monitoring module, groundwater monitoring module, water inflow monitoring module, reservoir water level monitoring module, environmental monitoring module, automated control module, and early warning module, respectively. The intelligent analysis and decision-making module receives monitoring signals from each module and determines the dynamic risk level based on a dynamic risk assessment model. It also assesses the impact of future rainfall on the reservoir capacity. Based on the determined dynamic risk level and the assessment results, it generates corresponding control and early warning commands, which are then sent to the automated control module.

[0053] The automated control module is connected to the surface water drainage pump group, the groundwater drainage pump group, and the water tank drainage pump group respectively; the automated control module performs multi-dimensional linkage intelligent control of the actions of each drainage pump based on the received control commands.

[0054] The early warning module is used to execute early warning actions under the control of the automated control module.

[0055] As a preferred embodiment, the intelligent analysis and decision-making module is an industrial computer, and the automation control module is a PLC controller;

[0056] Preferably, the atmospheric precipitation monitoring module is a high-precision rain gauge. The environmental monitoring module includes a temperature sensor, a humidity sensor, and a wind speed sensor.

[0057] As a preferred embodiment, the surface water monitoring module comprises a surface water level sensor and a millimeter-wave radar level gauge. The surface water level sensor is installed on the surface of the mining area to monitor the surface water accumulation signal, and the millimeter-wave radar level gauge is installed in the subsidence area of ​​the mining area to monitor the water accumulation signal in the subsidence area.

[0058] As a preferred embodiment, the groundwater monitoring module comprises a goaf water level sensor and a karst cave water level sensor. The goaf water level sensor is installed in the goaf to monitor the goaf water level signal, and the karst cave water level sensor is installed in the karst cave to monitor the karst cave water level signal.

[0059] As a preferred embodiment, the water flow monitoring module includes a flow rate meter.

[0060] As a preferred embodiment, the water tank level monitoring module includes a water tank level sensor.

[0061] As a preferred embodiment, it also includes a power supply module, a communication module, and a remote monitoring terminal. The power supply module is connected to the intelligent analysis and decision-making module for supplying power, and the communication module is connected to the intelligent analysis and decision-making module for establishing communication connections between the intelligent analysis and decision-making module and external devices.

[0062] As a preferred embodiment, a remote monitoring terminal is also included. The remote monitoring terminal is connected to the intelligent analysis and decision-making module via wired or wireless means. This facilitates remote monitoring and operation of the drainage system, allows for real-time viewing of monitoring data, enables remote control of each drainage pump, and facilitates the reception of remote early warning information.

[0063] In this invention, an atmospheric precipitation monitoring module is deployed at the surface of the mining area to facilitate real-time monitoring of atmospheric precipitation signals; a surface water monitoring module is deployed at the surface of the mining area and in the subsidence area to facilitate real-time monitoring of surface water accumulation signals and subsidence area water accumulation signals; a groundwater monitoring module is deployed in the goaf and karst caves of the mining area to facilitate real-time monitoring of goaf and karst cave water level signals; a water inflow monitoring module is deployed at known water inflow points in the mining area to facilitate real-time monitoring of water inflow signals; a water level monitoring module is deployed in the water tank to facilitate real-time monitoring of water tank water level signals; and an environmental monitoring module is set up to facilitate real-time monitoring of environmental temperature, humidity, and wind speed signals. By configuring the intelligent analysis and decision-making module, it can not only obtain data on atmospheric rainfall, surface water accumulation, subsidence area water accumulation, goaf water level, karst cave water level, water inflow, water reservoir water level, temperature, humidity, and wind speed in the mining area, but also integrate real-time monitoring data through the built-in dynamic risk assessment module to determine the dynamic risk level, thereby quantifying the mine water inflow risk level. Furthermore, the intelligent analysis and decision-making module can also determine the impact of current rainfall on water reservoir capacity, thus generating control commands for water reservoir drainage in advance, optimizing water reservoir capacity management, and ensuring the efficient and smooth drainage of surface and groundwater. By configuring the automated control module, multi-dimensional intelligent control can be implemented for underground drainage pump sets, surface water drainage pump sets, and water tank pump sets. This further enhances the system's intelligence level and allows for dynamic adjustment of the control input signals of each drainage pump, which is beneficial for optimizing drainage strategies. While improving drainage efficiency, it also significantly reduces energy consumption, achieving energy-saving management. Therefore, this system encompasses multi-dimensional online monitoring of atmospheric precipitation, surface water, and groundwater, and can combine dynamic risk assessment with multi-dimensional linkage control to achieve integrated intelligent management of flood prevention and drainage. This enables high-precision prevention and control of mine water hazards, significantly improving the proactive prevention and control capabilities of mine water hazards.

[0064] This system boasts a high degree of intelligence and automation. Through a multi-dimensional monitoring architecture and intelligent control system, it achieves informatization and digitization of the monitoring process and possesses proactive prevention and control capabilities. It enables dynamic monitoring and intelligent management of mine water inflow, significantly improving the intelligence level, control and prevention capabilities, and drainage efficiency of coal mine drainage systems. This effectively reduces the risk of mine water hazards and significantly reduces the labor intensity and monitoring difficulty for workers. It solves the problems of low automation and lack of multi-dimensional linkage control in existing underground mine drainage systems, effectively ensuring the safety of coal mine production.

[0065] This invention also provides a drainage and flood control method based on multi-dimensional linkage intelligent monitoring in underground mines, employing a drainage and flood control system based on multi-dimensional linkage intelligent monitoring in underground mines, comprising the following steps:

[0066] Step 1: Collect historical atmospheric precipitation data of the mining area and establish a rainfall prediction model for the mining area based on the historical atmospheric precipitation data; as a preferred option, the samples in the historical atmospheric precipitation data include relational data such as temperature, humidity, wind speed and precipitation; the rainfall prediction module for the mining area can be established based on a deep learning model (such as CNN);

[0067] Step Two: Utilize high-precision rain gauges installed on the mine surface to monitor atmospheric rainfall signals in real time and send them to the intelligent analysis and decision-making module; utilize surface water level sensors installed on the mine surface to monitor surface water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize millimeter-wave radar level gauges installed in the mine subsidence area to monitor subsidence area water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize goaf water level sensors installed in the goaf area to monitor goaf water level signals in real time and send them to the intelligent analysis and decision-making module. The module includes: a cave water level sensor installed in the cave to monitor the cave water level signal in real time and send it to the intelligent analysis and decision-making module; a water inflow monitoring module installed at known water inflow points to monitor the water inflow signal in real time and send it to the intelligent analysis and decision-making module; a water tank water level sensor installed in the water tank to monitor the water tank water level signal in real time and send it to the intelligent analysis and decision-making module; and temperature, humidity, and wind speed sensors installed in the mining area to monitor the temperature, humidity, and wind speed signals in real time and send them to the intelligent analysis and decision-making module.

[0068] Step 3: The intelligent analysis and decision-making module obtains atmospheric rainfall data Q1 in the mining area based on atmospheric rainfall signals; it obtains surface water accumulation data Q21 based on surface water volume signals in the mining area, and subsidence area water accumulation data Q22 based on subsidence area water accumulation signals. The total surface water accumulation Q2 is obtained by summing surface water accumulation data Q21 and subsidence area water accumulation data Q22; it obtains subsidence area water accumulation data Q31 based on goaf water level signals, and karst cave water accumulation data Q32 based on karst cave water level signals. The total underground water accumulation Q3 is obtained by summing subsidence area water accumulation data Q31 and karst cave water accumulation data Q32; it obtains total mine water inflow Q4 based on monitored water inflow signals; it obtains water accumulation in water sump Q51 based on water sump water level signals; and it obtains temperature data, humidity data, and wind speed data based on temperature signals, humidity signals, and wind speed signals.

[0069] Simultaneously, the atmospheric rainfall data Q1, current temperature data, humidity data, and wind speed data of the mining area are input into the mining area rainfall prediction model. The model is then used to predict future rainfall, yielding the future rainfall prediction data Q1. 预测 (t);

[0070] Step 4: Establish a dynamic risk assessment model based on formula (1) and obtain the dynamic risk level R(t);

[0071]

[0072] In the formula, Q1(t) represents real-time atmospheric rainfall data in the mining area; Q2(t) represents real-time total surface water accumulation; Q3(t) represents real-time total groundwater accumulation; Q4(t) represents real-time total mine water inflow; Q5 represents the total capacity of the water reservoir; Q1 警 This indicates the preset warning threshold for atmospheric rainfall in the mining area; Q2 警 The preset warning threshold for total surface water accumulation; Q3 警 Q1 represents the preset warning threshold for the total groundwater accumulation; 极 β represents the historical extreme values ​​of atmospheric rainfall data in the mining area; β represents the prediction adjustment coefficient of the rainfall prediction model in the mining area, with a value range of 0.1 to 0.3, which is used to adjust the impact of future rainfall on current risks.

[0073] Step 5: Develop a drainage strategy based on the dynamic risk level R(t). When R(t) < 0.5, it is determined to be a low-risk level L1. Maintain the current normal drainage status, generate a low-risk early warning command, and send it to the early warning module.

[0074] When 0.5≤R(t)<1.0, it is judged as a medium risk level L2. A control command is generated to start some of the surface water drainage pump group and groundwater drainage pump group to carry out drainage operations according to the set ratio and sent to the automation control module. At the same time, a medium warning command is generated and sent to the warning module.

[0075] When R(t)≥1.0, it is judged as L3 high risk, and a control command is generated to start all surface water drainage pump groups and drainage pumps in groundwater drainage pump groups to carry out drainage operations, and sent to the automation control module. At the same time, an emergency warning command is generated and sent to the warning module.

[0076] Meanwhile, when R(t)≥0.5, based on Bayesian theory and historical rainfall data, the impact of future rainfall on the reservoir capacity is calculated according to formula (2), and the probability P of starting the reservoir drainage pump group in advance for drainage is predicted. 排水 (t), when P 排水 When (t)≥0.5, a control command is generated to start the water tank drainage pump group for drainage operation and sent to the automation control module;

[0077]

[0078] Step Six: Upon receiving a control command to activate a portion of the surface water drainage pump group and groundwater drainage pump group according to a set ratio, the automation control module controls the activation of a portion of the surface water pump group to drain surface water from the mining area, and controls the activation of a portion of the groundwater pump group to drain groundwater from the mining area, until R(t) < 0.5. Upon receiving a control command to activate all surface water drainage pump groups and groundwater drainage pump groups, the module controls the activation of all drainage pumps in the surface water drainage pump group to drain surface water from the mining area, and controls the activation of all drainage pumps in the groundwater drainage pump group to drain groundwater from the mining area, until R(t) < 0.5. Upon receiving a control command to activate the water tank drainage pump group, the module controls the activation of all drainage pumps in the water tank drainage pump group to drain water from the water tank, until R(t) < 0.5.

[0079] Meanwhile, during the synchronous operation of the surface water drainage pump group, the groundwater drainage pump group and the water tank drainage pump group, based on the finite time consistency theory of multi-agent systems, the control input for the simultaneously operating surface water pump, groundwater pump and water tank pump is obtained according to formula (3) to achieve multi-dimensional linkage intelligent control.

[0080]

[0081] Where u i (t) represents the control input of the i-th drainage pump; x i Indicates the current state of the i-th drainage pump; x N+1 Indicates the target state; k represents the control gain, used to adjust the system's response speed; a ij Indicates the connection weight between multiple drainage pumps; b i This represents the weight between the drainage pump and the target state; α represents the predictive adjustment coefficient, ranging from 0.1 to 0.5, used to adjust the current drainage strategy based on future rainfall.

[0082] Meanwhile, upon receiving a low-risk warning instruction, the early warning module executes low-risk warning actions; upon receiving a medium-risk warning instruction, it executes medium-risk warning actions; and upon receiving an emergency warning instruction, it executes emergency risk warning actions, so as to effectively remind relevant management personnel to take timely and effective countermeasures.

[0083] To improve the accuracy of dynamic risk assessment, in step four, Q1 警 Values ​​are taken from 60% to 70% of the historical maximum atmospheric precipitation data for the mining area; Q2 警Values ​​are taken as 70%–80% of the historical maximum total surface water volume; Q3 警 The value is taken as 70% to 80% of the historical maximum total groundwater volume.

[0084] This invention establishes a rainfall prediction module for mining areas based on historical atmospheric rainfall data, facilitating accurate and effective prediction of future rainfall. Simultaneously, addressing the current lack of online monitoring and early warning capabilities for key factors such as atmospheric rainfall, surface water, and groundwater in underground mines, this method provides a comprehensive monitoring and early warning solution. It achieves real-time online monitoring of multi-dimensional parameters such as atmospheric rainfall, surface water, and groundwater, effectively solving the problem of insufficient or inaccurate meteorological and hydrological data in mines, and providing strong support for safe mine production. Furthermore, by integrating real-time monitoring data, historical extreme values, and predicted future rainfall through a dynamic risk assessment model, dynamic risk assessment is conducted. This not only considers the current water situation but also effectively combines future rainfall prediction data and historical data, ensuring more accurate and reliable risk assessment results. This assessment process can accurately quantify the risk level of mine water inrush, and then formulate appropriate drainage strategies based on different risk levels, achieving scientific management of the drainage process, significantly reducing drainage energy consumption, and ensuring the safe operation of mine production. After the automated control module receives control commands from the intelligent analysis and decision-making module based on different risk levels, it further optimizes the control inputs of simultaneously operating surface water pumps, groundwater pumps, and reservoir pumps based on the finite-time consistency theory of multi-agent systems. Through multi-dimensional linkage intelligent control, the actions of multiple operating drainage pumps can be dynamically adjusted, effectively optimizing the response of each pump. Thus, this method, by combining dynamic risk assessment and multi-dimensional linkage control, achieves hierarchical and coordinated control of groundwater drainage, surface water drainage, and reservoir drainage. This allows for dynamic adjustment of the actions of each operating drainage pump according to the risk level, greatly improving the efficiency of drainage operations and significantly reducing overall energy consumption during the drainage process. Furthermore, in situations of L2 medium risk and L3 high risk, the impact of future rainfall on reservoir capacity can be predicted based on Bayesian theory and historical rainfall data. This enables advance prediction of reservoir capacity, allowing for the early activation of reservoir drainage pumps. Consequently, it effectively optimizes reservoir capacity management during surface water and groundwater drainage, significantly enhancing the foresight and proactiveness of prevention and control.

[0085] This invention overcomes the limitations of traditional single-dimensional monitoring by innovatively integrating dynamic risk assessment, predictive control, and multi-agent collaborative algorithms. It enables an integrated intelligent management process for mine flood control and drainage, significantly improving the response efficiency of water hazard early warning. Simultaneously, it effectively optimizes the utilization rate of water storage capacity, significantly enhancing the intelligence level and proactive water hazard prevention capabilities of mine flood control and drainage systems. This highly intelligent method enables dynamic monitoring and drainage operations of mine water inflows, and allows for intelligent, tiered, dynamic drainage operations in the event of water inflows. Furthermore, it provides linked early warning alerts, effectively reducing the risk of mine water hazards and significantly improving the safety of mine production.

Claims

1. A drainage and flood control method based on multi-dimensional linkage intelligent monitoring in underground mines, characterized in that, Includes the following steps: Step 1: Collect historical atmospheric rainfall data for the mining area and establish a rainfall prediction model for the mining area based on the historical atmospheric rainfall data; Step Two: Utilize high-precision rain gauges installed on the mine surface to monitor atmospheric rainfall signals in real time and send them to the intelligent analysis and decision-making module; utilize surface water level sensors installed on the mine surface to monitor surface water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize millimeter-wave radar level gauges installed in the mine subsidence area to monitor subsidence area water accumulation signals in real time and send them to the intelligent analysis and decision-making module; utilize goaf water level sensors installed in the goaf area to monitor goaf water level signals in real time and send them to the intelligent analysis and decision-making module. The module includes: a cave water level sensor installed in the cave to monitor the cave water level signal in real time and send it to the intelligent analysis and decision-making module; a water inflow monitoring module installed at known water inflow points to monitor the water inflow signal in real time and send it to the intelligent analysis and decision-making module; a water tank water level sensor installed in the water tank to monitor the water tank water level signal in real time and send it to the intelligent analysis and decision-making module; and temperature, humidity, and wind speed sensors installed in the mining area to monitor the temperature, humidity, and wind speed signals in real time and send them to the intelligent analysis and decision-making module. Step 3: The intelligent analysis and decision-making module obtains atmospheric rainfall data Q1 in the mining area based on atmospheric rainfall signals; it obtains surface water accumulation data Q21 based on surface water volume signals in the mining area, and subsidence area water accumulation data Q22 based on subsidence area water accumulation signals. The total surface water accumulation Q2 is obtained by summing surface water accumulation data Q21 and subsidence area water accumulation data Q22; it obtains subsidence area water accumulation data Q31 based on goaf water level signals, and karst cave water accumulation data Q32 based on karst cave water level signals. The total underground water accumulation Q3 is obtained by summing subsidence area water accumulation data Q31 and karst cave water accumulation data Q32; it obtains total mine water inflow Q4 based on monitored water inflow signals; it obtains water accumulation data Q51 in water sump based on water level signals; and it obtains temperature data, humidity data, and wind speed data based on temperature signals, humidity signals, and wind speed signals. Simultaneously, the current atmospheric rainfall data Q1, current temperature data, humidity data, and wind speed data of the mining area are input into the mining area rainfall prediction model. The mining area rainfall prediction model is then used to predict future rainfall, obtaining future rainfall prediction data. ; Step 4: Establish a dynamic risk assessment model based on formula (1) and obtain the dynamic risk level. ; （1）； In the formula, This represents real-time atmospheric rainfall data in the mining area. This indicates the total real-time surface water volume; This indicates the total real-time underground water volume; This indicates the total water inflow in the mine in real time. Indicates the total capacity of the water tank; This indicates the preset warning threshold for atmospheric precipitation in the mining area. A preset warning threshold indicating the total surface water volume; The preset warning threshold indicating the total amount of groundwater accumulation; This represents the historical extreme values ​​of atmospheric precipitation data in the mining area; This represents the prediction adjustment coefficient of the rainfall prediction model for the mining area, with a value ranging from 0.1 to 0.3, used to adjust for the impact of future rainfall on current risks; Step 5: Based on the dynamic risk level Develop drainage strategies, when When the value is less than 0.5, it is determined to be a low-risk level (L1). The current normal drainage status is maintained, a low-risk warning command is generated, and it is sent to the warning module. When 0.5≤ When the value is less than 1.0, it is determined to be a medium risk level L2. A control command is generated to start some of the surface water drainage pump group and groundwater drainage pump group to carry out drainage operations according to a set ratio and sent to the automation control module. At the same time, a medium warning command is generated and sent to the warning module. when When the value is ≥1.0, it is determined to be a high-risk level L3. A control command is generated to start all surface water drainage pump groups and drainage pumps in groundwater drainage pump groups to carry out drainage operations and is sent to the automation control module. At the same time, an emergency warning command is generated and sent to the warning module. At the same time, when When the value is ≥0.5, based on Bayesian theory and historical rainfall data, the impact of future rainfall on the reservoir capacity is calculated according to formula (2), and the probability of starting the reservoir drainage pump group in advance for drainage is predicted. ,when When the value is ≥0.5, a control command is generated to start the water tank drainage pump group for drainage operation and sent to the automation control module; （2）； Step Six: After receiving a control command to activate a portion of the surface water drainage pump group and groundwater drainage pump group according to a set ratio, the automation control module controls the activation of some surface water pumps in the surface water drainage pump group to drain surface water from the mining area, and controls the activation of some groundwater pumps in the groundwater drainage pump group to drain groundwater from the mining area, until... Stop when <0.5; upon receiving a control command to start all surface water drainage pump sets and groundwater drainage pump sets for drainage operations, control to start all drainage pumps in the surface water drainage pump sets to drain surface water in the mining area, and control to start all drainage pumps in the groundwater drainage pump sets to drain groundwater in the mining area, until... Stop when <0.5; upon receiving the control command to start the water tank drainage pump group for drainage operation, control to start all drainage pumps in the water tank drainage pump group to drain the water tank until... Stop when <0.5; Meanwhile, during the synchronous operation of the surface water drainage pump group, the groundwater drainage pump group and the water tank drainage pump group, based on the finite time consistency theory of multi-agent systems, the control input for the simultaneously operating surface water pump, groundwater pump and water tank pump is obtained according to formula (3) to realize multi-dimensional linkage intelligent control. （3）； Where, Indicates the first Control input for a drainage pump; Indicates the first The current status of each drainage pump; Indicates the target state; This represents the control gain, used to adjust the system's response speed. Indicates the connection weights between multiple drainage pumps; This represents the weight between the drainage pump and the target state; This represents the predictive adjustment factor, with a value ranging from 0.1 to 0.5, used to adjust the current drainage strategy based on future rainfall. Meanwhile, upon receiving a low-risk warning instruction, the early warning module executes low-risk warning actions; upon receiving a medium-risk warning instruction, it executes medium-risk warning actions; and upon receiving an emergency warning instruction, it executes emergency risk warning actions, so as to effectively remind relevant management personnel to take timely and effective countermeasures.

2. The drainage and waterproofing method based on multi-dimensional linkage intelligent monitoring of underground mines according to claim 1, characterized in that, In step four, The value is taken as 60% to 70% of the historical maximum atmospheric precipitation data for the mining area; The value is taken as 70% to 80% of the historical maximum total surface water volume; The value is taken as 70% to 80% of the historical maximum total groundwater volume.

3. A drainage system based on multi-dimensional linkage intelligent monitoring of underground mines, used to implement the drainage method based on multi-dimensional linkage intelligent monitoring of underground mines as described in claim 1 or 2, characterized in that, It includes a water tank, several drainage pumps, an atmospheric rainfall monitoring module, a surface water monitoring module, a groundwater monitoring module, a water inflow monitoring module, a water tank water level monitoring module, an environmental monitoring module, an automated control module, an early warning module, and an intelligent analysis and decision-making module; The drainage pumps are divided into three groups: a surface water drainage pump group, a groundwater drainage pump group, and a water tank drainage pump group; the surface water drainage pump group consists of multiple surface water pumps; the groundwater drainage pump group consists of multiple groundwater pumps; and the water tank drainage pump group consists of multiple water tank pumps. The atmospheric precipitation monitoring module is installed at the surface of the mining area; the surface water monitoring module is installed at the surface of the mining area and in the subsidence area; the groundwater monitoring module is installed in the mined-out area and karst caves of the mining area; the water inflow monitoring module is installed at known water inflow points in the mining area; the water level monitoring module is installed in the water tank; the environmental monitoring module is installed at the surface of the mining area; and the automatic control module is connected to the surface water drainage pump group, the groundwater drainage pump group, and the water tank drainage pump group respectively. The intelligent analysis and decision-making module is connected to the atmospheric rainfall monitoring module, surface water monitoring module, groundwater monitoring module, water inflow monitoring module, water reservoir level monitoring module, environmental monitoring module, automated control module, and early warning module, respectively.

4. The drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 3, characterized in that, The atmospheric precipitation monitoring module is a high-precision rain gauge; the environmental monitoring module includes a temperature sensor, a humidity sensor, and a wind speed sensor.

5. A drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 4, characterized in that, The surface water monitoring module consists of a surface water level sensor and a millimeter-wave radar level gauge. The surface water level sensor is installed on the surface of the mining area to monitor the surface water accumulation signal, and the millimeter-wave radar level gauge is installed in the subsidence area of ​​the mining area to monitor the water accumulation signal in the subsidence area.

6. A drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 5, characterized in that, The groundwater monitoring module consists of a goaf water level sensor and a karst cave water level sensor. The goaf water level sensor is installed in the goaf to monitor the goaf water level signal, and the karst cave water level sensor is installed in the karst cave to monitor the karst cave water level signal.

7. A drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 6, characterized in that, The water flow monitoring module includes a flow rate meter.

8. A drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 7, characterized in that, The water level monitoring module for the water tank includes a water level sensor for the water tank.

9. A drainage system based on multi-dimensional linkage intelligent monitoring in underground mines according to claim 8, characterized in that, It also includes a power supply module, a communication module, and a remote monitoring terminal. The power supply module is connected to the intelligent analysis and decision-making module and is used to supply power. The communication module is connected to the intelligent analysis and decision-making module and is used to establish a communication connection between the intelligent analysis and decision-making module and external devices.

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