Multi-mode coal mine intelligent monitoring system

Abstract

The invention discloses a multi-mode coal mine intelligent monitoring system in the technical field of coal mine safety monitoring, and the system comprises a multi-source data collection node which is used for collecting environment data in real time; the mine car positioning module is used for judging whether a mine car exists in the current mine or not based on the time sequence fluctuation characteristics of the environmental data, and if yes, identifying the running state of the mine car; the interference judgment module is used for dynamically delimiting an interfered area based on the running state of the mine car and data disturbance time sequence relevance acquired by the adjacent multi-source data acquisition nodes; the data correction module is used for marking the sensor data in the interfered area, and executing at least one of the following operations: eliminating interfered time period data, and calling historical normal data or adjacent node data for interpolation completion; and triggering the cleaning device to start, and cleaning the influence of environmental disturbance on the multi-source data acquisition node. According to the scheme, the data accuracy problem caused by mine car interference can be solved, and the reliability and accuracy of coal mine monitoring are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal mine safety monitoring, and in particular relates to a multi-modal coal mine intelligent monitoring system. Background Art

[0002] Safety monitoring has always been a top priority in coal mining operations. With the continuous advancement of science and technology, coal mine monitoring technology has also evolved, from simple manual inspections in the early days to the widespread use of various sensors and now to the exploration of intelligent monitoring systems. Each stage has been aimed at improving the safety and efficiency of coal mine production.

[0003] Early coal mine monitoring relied primarily on manual inspections. Workers regularly entered the mines to observe and record equipment and the environment. This approach was not only inefficient but also posed significant safety risks. Manual inspections struggled to obtain comprehensive and accurate information in real time, and were prone to missed inspections and misjudgments. Faced with the complex environment and ever-changing risks of coal mines, the drawbacks of manual monitoring became increasingly apparent.

[0004] Subsequently, various sensors began to play a vital role in coal mine monitoring. For example, gas sensors monitor gas concentrations, sounding an alarm if levels exceed standards; dust sensors monitor dust levels to prevent accidents such as dust explosions; and temperature and pressure sensors are widely used in equipment status monitoring and environmental safety monitoring. These sensors enable real-time monitoring of specific parameters and, to a certain extent, enhance the automation of monitoring. However, existing sensor monitoring systems still have numerous challenges.

[0005] First, sensor monitoring data is relatively sparse. Each sensor monitors only a specific parameter, and there's a lack of effective integration and coordination between sensors. For example, a gas sensor only reports gas concentration, but fails to fully capture complex information such as the spatial distribution of gas accumulation and its relationship to ventilation conditions. This single-source data model makes it difficult to build a comprehensive understanding of the overall safety status of coal mines, and can easily lead to a one-sided assessment of potential risks.

[0006] On the other hand, the existing monitoring system has a limited degree of intelligence. Although it can realize basic real-time monitoring and alarm functions, it has deficiencies in terms of in-depth analysis of monitoring data, intelligent early warning, and automated decision-making. In this regard, the patent publication (announcement) number CN116877203B discloses a coal and gas outburst monitoring and early warning device. By monitoring multiple factors such as gas concentration, surrounding rock stress changes, and gas seepage, an early warning model is established to predict the risk of coal and gas outburst in advance. Although the above scheme has a certain effect in gas monitoring, the scheme mainly focuses on the monitoring of gas itself and related geological factors, and does not consider the disturbance effect of the operation of the mine car on the air around the collection equipment and the gas collection data. In actual mine operations, when the mine car passes through the collection equipment, it may carry gas with a high content of a certain gas, or disturb the surrounding air, resulting in large fluctuations in the collected gas concentration, thereby affecting the accuracy of the data, and the device cannot effectively identify and process such situations.

[0007] In view of the defects of existing technologies, there is an urgent need for a multimodal coal mine intelligent monitoring system to overcome the above problems, comprehensively improve the accuracy, comprehensiveness and intelligence level of coal mine monitoring, and meet the urgent needs of coal mine safety production. Summary of the Invention

[0008] In order to solve the above problems, the purpose of the present invention is to provide a multimodal coal mine intelligent monitoring system that can overcome the data accuracy problem caused by mine car interference in existing coal mine monitoring technology and improve the reliability and accuracy of coal mine monitoring.

[0009] In order to achieve the above object, the technical solution of the present invention is as follows: A multimodal coal mine intelligent monitoring system, comprising: Multi-source data collection nodes are distributed along the mine tunnels to collect environmental data in real time; The mine car positioning module is used to determine whether there is a mine car in the current mine based on the time series fluctuation characteristics of environmental data. If a mine car is present, it will identify the operating status of the mine car, including its direction of travel, speed, and current location area; The interference judgment module dynamically demarcates the interference area based on the operating status of the mine car and the temporal correlation of data disturbances collected by adjacent multi-source data acquisition nodes; The data correction module marks the sensor data in the interfered area and performs at least one of the following operations: Eliminate data from disturbed periods and use historical normal data or adjacent node data for interpolation and completion; Trigger the cleaning device to start and clean up the impact of environmental disturbances on multi-source data acquisition nodes.

[0010] Furthermore, the environmental data includes gas concentration, temperature and humidity, air pressure and dust density.

[0011] Furthermore, the interference judgment module defines the interference area based on the following logic: Align the timestamps of data fluctuations at adjacent multi-source data collection nodes and extract the fluctuation propagation direction and time difference; Calculate the mine car speed based on the mine tunnel topology map; Predict the time window for the mine car to reach the next monitoring area based on the mine car's speed and the branching situation in the mine tunnel; Analyze the trajectory of the mine car in the mine tunnel, and predict the monitoring area that the mine car passes through based on the branching of the mine tunnel and the direction of the mine car; Based on the mine car's speed and the wind speed in the mine tunnel, estimate the range of airflow disturbance generated when the mine car passes through the multi-source data collection node; The temporal correlation of data disturbances collected by adjacent multi-source data acquisition nodes is analyzed. If data fluctuations occur at multiple nodes within the time window when the mine car passes, and the direction of the fluctuation propagation is consistent with the direction of the mine car's travel, and the time difference is consistent with the mine car's travel speed and the mine tunnel structure, the area where these nodes are located is determined to be the disturbed area.

[0012] Furthermore, it also includes a correction module, which is used to use historical data to analyze the disturbance characteristics of the mine car on the multi-source data collection node data under different operating conditions, establish a correlation model between the mine car operating state and the data disturbance characteristics; and dynamically correct the time window affected by the mine car interference according to the correlation model.

[0013] Furthermore, the cleaning device includes a base; a ventilation pipe runs through the base, and the ventilation pipe is connected to an air supply mechanism for conveying airflow into the ventilation pipe; the ventilation pipe is respectively connected to a first branch pipe and a second branch pipe, the first branch pipe is connected to a jet mechanism, and the second branch pipe is connected to a dynamic adjustment mechanism, the jet mechanism is used to perform pulse jet cleaning on the collection end of the multi-source data collection node; the dynamic adjustment mechanism is used to dynamically adjust the cleaning intensity of the jet mechanism based on the current dust situation near the base.

[0014] Furthermore, the air supply mechanism includes a fan, a screen and a flexible connecting pipe; the flexible connecting pipe is used to connect the air outlet of the fan and the ventilation pipe, and the screen is arranged in the air inlet of the fan.

[0015] Furthermore, the jet mechanism includes a nozzle; the nozzle is fixedly connected to one side of the base, and an exhaust channel is opened in the nozzle, and the exhaust channel includes a contraction section and a gradual expansion section; one end of the exhaust channel is connected to a piston groove, and a first one-way valve for limiting the gas from flowing back into the piston groove is provided at the connection between the exhaust channel and the piston groove, and a piston block is slidably fitted in the piston groove, and the piston groove is connected to the first branch pipe, and a second one-way valve for limiting the gas from flowing back to the first branch pipe is provided at the connection between the piston groove and the first branch pipe; a driving mechanism is connected to the piston block for transmission, and the driving mechanism is used to drive the piston block to move back and forth.

[0016] Furthermore, the driving mechanism includes an active cavity provided in the base body; a pair of rotating shafts are symmetrically connected to the active cavity for rotation, a first bevel gear is axially fixedly connected to any one of the rotating shafts, the first bevel gear is meshed with a second bevel gear, a turbine is axially provided on the second bevel gear, and the turbine is rotationally connected to the ventilation pipe; A rotating carrier is provided at one end of each rotating shaft close to each other, and a first connecting rod is eccentrically connected between the rotating carriers. The other end of the first connecting rod is rotatably connected to the second connecting rod and the third connecting rod, the other end of the second connecting rod is rotatably connected to the piston block, and an adjustment block is provided at the other end of the third connecting rod. An adjustment groove is provided on the adjustment block, and a slider is slidably connected in the adjustment groove. A transfer carrier is rotatably connected to the slider, and the third connecting rod is rotatably connected to the transfer carrier.

[0017] Furthermore, the dynamic adjustment mechanism includes a negative pressure groove provided on one side of the movable chamber, an elastic membrane is provided in the negative pressure groove, a fourth connecting rod is rotatably connected to the side of the elastic membrane close to the movable chamber, a sliding groove is further provided on the inner wall of the movable chamber, and the fourth connecting rod is slidably engaged with the sliding groove; a rack is provided on the fourth connecting rod, the rack is meshed with a first gear, a third bevel gear is axially provided on the first gear, the third bevel gear is meshed with a fourth bevel gear, an adjustment rod is axially provided on the fourth bevel gear, the adjustment rod extends through a transfer carrier at one end away from the fourth bevel gear, and the transfer carrier is threadedly engaged with the adjustment rod; The negative pressure tank is connected with a negative pressure three-way pipeline, and the other two ends of the negative pressure three-way pipeline are respectively connected with a negative pressure mechanism and a plurality of sensing holes.

[0018] Furthermore, the negative pressure three-way pipe is connected to the second branch pipe, and the negative pressure mechanism includes a throat arranged in the second branch pipe, and the throat is located at the connection point between the negative pressure three-way pipe and the second branch pipe.

[0019] Working principle of the cleaning device: When the multi-source data acquisition node needs to be cleaned, clean air is transported into the ventilation pipe through the air supply mechanism. When the air passes through the first branch pipe and the second branch pipe, part of the air enters the first branch pipe and the second branch pipe respectively. When the air passes through the turbine, it will drive the turbine to rotate, and the rotation of the turbine drives the second bevel gear to rotate. The rotation of the second bevel gear drives the first bevel gear to rotate. The rotation of the first bevel gear drives the rotating shaft to rotate. The rotation of the rotating shaft drives the rotating carrier to rotate. The rotation of the rotating carrier drives the first connecting rod to move. One end of the first connecting rod performs circular motion around the rotating axis. The other end of the first connecting rod drives the other end of the second connecting rod under the coordinated (support and suspension) action of the third connecting rod and the second connecting rod to push the piston block to reciprocate along the piston groove. During the reciprocating movement, the piston block continuously sucks the air in the first branch pipe into the piston groove and discharges it into the exhaust channel from the piston groove. Finally, after acceleration through the contraction section and gradual expansion section (Laval nozzle structure) in the exhaust channel, the acquisition end of the multi-source data acquisition node is subjected to pulse jet treatment.

[0020] At the same time, during the jet treatment process, the air flow in the second branch pipe will generate negative pressure at the throat (Venturi effect, when the air passes through the throat, the flow rate increases and the pressure decreases). This negative pressure will directly act on the negative pressure three-way pipe. At this time, the negative pressure three-way pipe will inhale the outside air through the sensing hole to offset the negative pressure. If the dust concentration near the multi-source data acquisition node is high, the sensing hole will gradually be blocked by dust, so that the negative pressure in the negative pressure three-way pipe cannot be completely offset, and the negative pressure will gradually increase within a certain range and act on the negative pressure groove through the negative pressure three-way pipe, causing the elastic membrane to deform. The deformation of the elastic membrane will cause the fourth connecting rod to move, and the movement of the fourth connecting rod will drive the rack to move. The movement of the rack drives the first gear to rotate, and the rotation of the first gear drives the third bevel gear to rotate, and then drives the fourth bevel gear to rotate. The rotation of the fourth bevel gear drives the adjusting rod to rotate. Since the adjusting rod is threaded with the transfer carrier, the rotation of the adjusting rod drives the transfer carrier to move along the length direction of the adjusting rod. The movement of the transfer carrier drives the slider to move in the adjusting groove, and then drives the third connecting rod to move, so as to adjust the fulcrum position of the second connecting rod, thereby adjusting the stroke distance of the piston block to adapt to the cleaning of different dust concentrations.

[0021] The above scheme has the following beneficial effects: 1. This solution, through the mine car positioning module, can accurately determine the presence of a mine car in the mine based on the temporal fluctuation characteristics of environmental data, and further identify the mine car's direction of travel, speed, and current location. Directly locating mine cars in complex mine environments presents numerous inconveniences. On the one hand, due to the complex environment within the mine, wireless signal transmission is susceptible to interference, resulting in unstable and inaccurate positioning signals. On the other hand, the layout and structure of mine tunnels are complex and diverse, with numerous obstructions and reflective surfaces, which further affect the transmission quality of wireless signals. This solution, however, does not rely on traditional wireless positioning equipment. By analyzing subtle changes in environmental data, such as fluctuations in gas concentration, temperature and humidity, air pressure, and dust density, it can accurately determine the presence of a mine car in the mine, and further identify the mine car's direction of travel, speed, and current location, providing a key basis for subsequent interference determination.

[0022] 2. This solution uses an interference assessment module to dynamically delineate disturbed areas by combining the operating status of mine cars with the temporal correlation of data disturbances from adjacent multi-source data acquisition nodes. This method accurately identifies the scope of the impact of mine car operation on monitoring data, avoiding the inaccuracies and limitations of fixed range delineation. Through techniques such as timestamp alignment, wave propagation direction, and time difference extraction, combined with mine roadway topology and mine car travel speed, the time window for the mine car to reach the next monitoring area is accurately predicted, enabling dynamic, real-time delineation of disturbed areas and providing precise spatial and temporal information for data correction.

[0023] The correction module uses historical data to analyze the disturbance characteristics of mine cars under different operating conditions on data from multiple data collection nodes and establishes a correlation model. This enables the system to more accurately predict the interference impact of mine cars under different operating conditions based on historical experience, improving the accuracy and foresight of interference judgments. By using a dynamic interference time window, the system can improve the reliability and accuracy of monitoring data.

[0024] By accurately identifying mine vehicles, dynamically demarcating interference zones, and intelligently predicting interference impacts, the system effectively addresses data accuracy challenges associated with mine vehicle operation, improving the reliability and accuracy of coal mine monitoring. The data correction module promptly removes data from disturbed periods and interpolates data to ensure the authenticity and integrity of monitoring data, providing more accurate decision-making for coal mine safety production.

[0025] 3. This solution uses an air supply mechanism to deliver clean air to the ventilation duct. The ingenious coordination of a turbine, bevel gear, rotating shaft, and connecting rod drives a piston block to reciprocate within its groove, achieving pulsed jet cleaning of the data collection end. This pulsed jet effectively impacts and removes dust and other contaminants adhering to the data collection end of multi-source data collection nodes. Compared to traditional continuous cleaning methods, pulsed jet can concentrate greater airflow energy in a shorter period of time, more efficiently removing stubborn stains and ensuring the cleanliness of the sensor collection end, thereby improving the accuracy of monitoring data.

[0026] 4. This solution utilizes the negative pressure generated by the Venturi effect, combined with a negative pressure three-way pipe and sensing hole design, to enable the cleaning device to automatically adjust the jet intensity based on the dust concentration near the substrate. When high dust concentration causes the sensing hole to clog, the negative pressure increases. The elastic membrane, the fourth connecting rod, and the third connecting rod work together to adjust the piston stroke distance, thereby varying the jet volume and pressure to meet the cleaning needs of different pollution levels. This intelligent adjustment mechanism avoids the waste of resources caused by excessive cleaning, while also ensuring effective cleaning in high-dust environments, enhancing the adaptability and energy efficiency of the cleaning device.

[0027] 5. This solution, through the connection of a negative pressure three-way pipe to the outside air and the design of a sensing hole, enables the cleaning device to sense changes in the surrounding dust concentration in real time and automatically make corresponding adjustments. This adaptive design reduces manual intervention, improves the cleaning device's autonomous operation and stability in the complex and changing environment of underground coal mines, and ensures that the multi-source data collection node is always in good working condition. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of the three-dimensional structure of the cleaning device in the multi-modal coal mine intelligent monitoring system of the present invention.

[0029] Figure 2 for Figure 1 Top view of .

[0030] Figure 3 for Figure 2 Cross-sectional view along the AA direction.

[0031] Figure 4 for Figure 3 Cross-sectional view along the BB direction.

[0032] Figure 5 for Figure 4 A partial enlarged schematic diagram of point M in the middle.

[0033] Figure 6 for Figure 5 A local enlarged schematic diagram of point N in the middle.

[0034] Reference numerals in the drawings of the specification include: 1, base; 2, ventilation pipe; 3, nozzle; 4, sensing hole; 101, first branch pipe; 102, second branch pipe; 103, movable chamber; 104, first bevel gear; 105, second bevel gear; 106, rotating shaft; 107, rotating carrier; 108, first connecting rod; 109, second connecting rod; 110, third connecting rod; 111, fourth connecting rod; 112, elastic membrane; 113, negative pressure groove; 114. Negative pressure three-way pipe; 115. Piston groove; 116. Piston block; 117. Exhaust channel; 118. First one-way valve; 119. Adjusting block; 120. Adjusting groove; 121. Slide groove; 122. Rack; 123. First gear; 124. Third bevel gear; 125. Fourth bevel gear; 126. Adjusting rod; 127. External thread; 128. Transfer carrier; 129. Slider; 130. Fixing ring; 131. Slide rail. DETAILED DESCRIPTION

[0035] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0036] In the description of the present invention, it should be understood that the terms "longitudinal", "transverse", "vertical", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention.

[0037] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal communication between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0038] The following is further described in detail through specific implementation methods: Example 1: A multimodal coal mine intelligent monitoring system, comprising: Multi-source data collection nodes are distributed along the mine tunnels to collect real-time environmental data. This data includes key parameters such as gas concentration (such as methane concentration), temperature and humidity, air pressure, and dust density. Each collection node is evenly distributed along the tunnel walls, with adjacent nodes approximately 30 meters apart, ensuring comprehensive and accurate data collection.

[0039] The mine car positioning module is used to determine whether there is a mine car in the current mine based on the time-series fluctuation characteristics of environmental data. If a mine car is present, it will identify the operating status of the mine car, including its direction of travel, speed, and current location area. Specifically, when the mine car is running, it will trigger specific fluctuation patterns in the surrounding environmental data, such as instantaneous changes in gas concentration caused by airflow disturbances and instantaneous increases in dust density. By identifying these fluctuation patterns, the module confirms the presence of the mine car and further utilizes data from multiple nodes for collaborative analysis. It uses the Kalman filter algorithm to fuse multi-source data to identify the operating status of the mine car, including its direction of travel (determined by comparing the direction of airflow fluctuations at adjacent nodes), speed (calculated based on the time difference and spacing between fluctuation propagation times), and current location area (calculated based on the position of the first node that detects the fluctuation and the speed of the mine car).

[0040] The interference judgment module dynamically demarcates the interference area based on the operating status of the mine car and the temporal correlation of the data disturbance collected by adjacent multi-source data collection nodes. Its specific logic is as follows: The data fluctuations of adjacent multi-source data acquisition nodes are timestamped and the fluctuation propagation direction and time difference are extracted. For example, if node A detects gas concentration fluctuations before node B, and the time difference between the two matches the speed of sound corresponding to the distance, then it is determined that the fluctuation propagates from A to B.

[0041] The mine cart's speed is calculated based on the mine tunnel topology. The speed is also calculated based on the environmental data changes as the mine cart passes through different areas. For example, if the topology of a certain tunnel section shows a straight-line distance of 100 meters between two curves, and the dust fluctuations caused by the mine cart are detected at the starting and ending nodes of the section 50 seconds apart, the mine cart's speed is approximately 2 meters per second.

[0042] The time window for a mine car to reach the next monitoring area is predicted based on the car's speed and the presence of branching within the mine tunnels. A probabilistic model is used to predict the time window for the mine car to reach the next monitoring area. If the current speed is stable, the next area is 200 meters away from the current area, and the mine car speed is 2 meters per second, the estimated arrival time is 100 seconds later. Taking into account the speed changes that may occur due to tunnel branching (for example, a 30% probability of deceleration at a branch), the time window is set between 90 and 110 seconds.

[0043] The steps for constructing the probability model are: Historical data collection Collect historical data of mine cars running in mine tunnels, including the speed, direction, current position, tunnel branching conditions, actual time of arrival at each monitoring area, and other information.

[0044] The data covers operation records in different time periods, different tunnel areas, and different mine car load conditions to ensure the comprehensiveness and accuracy of the model.

[0045] Feature extraction Extract key features from historical data, such as the average speed of mine cars in different tunnel sections, the frequency of deceleration or stopping at branch points, and speed changes under different loads.

[0046] Statistics on the probability of a minecart slowing down at a branch point, for example, the probability of slowing down is 30%, and the speed change range after slowing down.

[0047] Probabilistic model building Basic time calculation Calculate the base arrival time in the absence of interference based on the minecart's current speed and the distance to the next monitored area. For example, if the next area is 200 meters away and the minecart's speed is 2 m / s, the base arrival time is 200 m / 2 m / s = 100 seconds.

[0048] Branch Impact Analysis Analyze the impact of branching within a mine tunnel on mine car travel speed. Using historical data, determine the probability of a mine car slowing down at a branching point (e.g., 30%) and the speed range after deceleration (e.g., a deceleration range of 20%-50%).

[0049] Construct a conditional probability distribution representing the probability of the minecart slowing down when encountering a branch point and the probability distribution of the deceleration magnitude.

[0050] Time window setting Combining the base arrival time with the branching impact analysis, a time window is set for the minecart to reach the next monitoring area. The time window takes into account possible deceleration caused by the branching point and other uncertainties (such as temporary avoidance of the minecart and track conditions).

[0051] For example, if we take a base arrival time of 100 seconds and consider a 30% chance of slowing down at a branch, we can set the time window to 90 to 110 seconds. This means that in most cases (e.g., with a 95% confidence level), the minecart will reach the next monitoring area within 90 to 110 seconds.

[0052] Model validation and optimization Model Validation The constructed probability model is verified using the reserved historical data, the consistency between the time window predicted by the model and the actual arrival time is compared, and the prediction accuracy is calculated.

[0053] Model optimization Based on the validation results, we adjust model parameters, such as branch point deceleration probability and deceleration amplitude distribution, to improve the accuracy of model predictions. We continuously collect new operational data and regularly update the model to ensure it can adapt to changes in mine roadways and mine car operating patterns.

[0054] The system also analyzes the trajectory of the mine car within the mine roadway, combining the roadway branching (such as main roadway, branch roadway, etc.) and the direction of the mine car's travel (determined by continuously detecting the direction of node fluctuations) to predict the monitoring areas the mine car will pass through. If the mine car travels from the main roadway toward the branch roadway with a stable speed and direction, it can be predicted that it will pass through the subsequent monitoring areas of the main roadway and may enter the corresponding area of the branch roadway.

[0055] Based on the mine car's speed and the wind speed within the mine tunnel, the range of airflow disturbances generated by the mine car passing through the multi-source data collection nodes is estimated. Specifically, when the mine car travels within the mine tunnel, its motion disturbs the surrounding air, creating a specific airflow field. This airflow field is formed because the movement of the mine car forces the previously relatively static air to flow. Simultaneously, the existing wind speed within the tunnel also affects the airflow disturbances generated by the mine car's movement. The combination of these two factors determines the range of airflow disturbances.

[0056] In order to estimate the range of airflow disturbances generated when a mine car passes through a multi-source data acquisition node, the following detailed fluid dynamics model and calculation steps can be used: Fluid dynamics equation selection The quasi-steady-state Navier-Stokes equation is used to simplify the model, assuming that: The airflow in the tunnel is incompressible turbulent The minecart is a rectangular rigid body (long ,Width ,high ), the size of the mine cars used in the mine is uniform Ignore the effect of temperature gradient on airflow Governing equations:

[0057] in, is the air velocity vector, is the air pressure, The drag force of the minecart.

[0058] Disturbance range calculation process Step 1: Calculation of equivalent drag force The equivalent drag force generated by the minecart movement:

[0059] in, It is the angle between the driving direction of the mine car and the wind flow in the tunnel. is the air density (calculated by the temperature and humidity sensor).

[0060] Specifically:

[0061] in, is atmospheric pressure, is the relative humidity, is the air temperature.

[0062] Step 2: Modeling the Disturbance Propagation Distance According to the momentum conservation theory, the maximum propagation distance of disturbance is :

[0063] in, is the effective action time (the length of time the minecart passes through the sensor area);

[0064] is the initial disturbance radius (taken as 1.5 times the width of the minecart WcWc).

[0065] Step 3: Geometric Constraint Correction Considering the restrictive effect of the tunnel cross-section shape (such as arch / rectangular) on the airflow, a cross-section correction factor is introduced :

[0066] in, is the cross-sectional area of the roadway, is the hydraulic diameter of the roadway ( , p is the wetted perimeter).

[0067] Final disturbance radius:

[0068] Dynamic parameter calibration method Drag coefficient Calibration Wind tunnel test method: A 1:10 scale mine car model was tested in a simulated tunnel to measure different Reynolds numbers ( ) under the resistance Typical fitting formula:

[0069] Optimization of effective action time Correction through inversion of field measured data: Install high-frequency PIV (particle image velocimetry) to capture the tail flow field of the mine car Compare the theoretical teffteff with the actual disturbance duration and establish a correction coefficient table:

[0070] Corrected formula:

[0071] Calculation example demonstration Scene parameters: Minecart Size:

[0072] Travel speed:

[0073] Tunnel wind speed: (Same direction as minecart) Tunnel cross section: arch, cross-sectional area , wet peritoneum

[0074] Calculation process: Drag force calculation:

[0075] Initial disturbance radius:

[0076] Effective time:

[0077] Maximum transmission distance:

[0078] Geometry correction:

[0079]

[0080]

[0081] Conclusion: When the mine car passes, the airflow disturbance radius is about 6.5 meters, and the sensor data in this area needs to be marked as disturbed.

[0082] Conclusion: When the mine car passes, the airflow disturbance radius is about 6.5 meters, and the sensor data in this area needs to be marked as disturbed.

[0083] The temporal correlation of data disturbances collected by adjacent multi-source data collection nodes is analyzed. If data fluctuations occur at multiple nodes within the time window of a mine car's passage, and the direction of the fluctuations aligns with the direction of the mine car's travel, and the time difference is consistent with the mine car's travel speed and the mine tunnel structure, the area where these nodes are located is determined to be disturbed. For example, if multiple consecutive nodes detect a sharp increase in dust density, and the time interval between the increases matches the elapsed time calculated from the mine car's speed, then the area is confirmed to be disturbed by the operation of the mine car. Otherwise, the dust density change is not caused by the operation of the mine car, and the data collected in this area is normal monitoring data.

[0084] It also includes a correction module, which is used to use historical data to analyze the disturbance characteristics of the mine car on the data of the multi-source data collection node under different operating states (such as deceleration, acceleration and constant speed), establish a correlation model between the mine car operating state and the data disturbance characteristics; and dynamically correct the time window affected by the mine car interference based on the correlation model.

[0085] Specifically, the mine car disturbance feature correlation model is constructed Data collection and preprocessing: Collect historical operation data of the mine car under different operating states (deceleration, acceleration, constant speed), including speed, position, driving direction, etc.

[0086] Collect environmental data from multi-source data collection nodes at the corresponding moment, such as gas concentration, dust density, etc.

[0087] The collected data is cleaned and normalized to remove outliers and noise to ensure data quality.

[0088] Association model construction: Extract the mine car running state characteristics and data disturbance characteristics and construct the feature vector.

[0089] Machine learning algorithms (such as random forests and support vector machines) are used to train historical data and establish a correlation model between the operating status of the mine car and the data disturbance characteristics.

[0090] Improve the prediction accuracy and generalization ability of the model through cross-validation and hyperparameter tuning.

[0091] Real-time prediction and correction: Obtain the real-time operating status of the mine car and the real-time data of the collection node online.

[0092] The constructed association model is used to predict the disturbance characteristics of the mine car on the collected node data in real time, and the disturbed time window is dynamically corrected based on the current position and speed of the mine car.

[0093] The corrected time window is sent to the data correction module to guide it to perform accurate data correction operations.

[0094] By establishing a correlation model between the mine car's operating status and data disturbance characteristics, the correction module can more accurately predict the impact of mine car operation on the data collected by the node, thereby more precisely dividing the disturbed area and determining the interference time window (indicating how long the interference data lasts after the mine car passes).

[0095] Coal mine environments are complex and ever-changing, and the operating status of mine cars is constantly changing. The correction module dynamically adjusts the interference time window based on real-time data, ensuring the monitoring system can promptly and accurately respond to data interference caused by mine car operation, improving the system's adaptability and reliability.

[0096] Providing a more accurate interference time window for the data correction module makes data correction operations more targeted and effective, reduces unnecessary data removal or correction, and improves the integrity and accuracy of monitoring data.

[0097] The data correction module marks the sensor data in the interfered area and performs at least one of the following operations: Data from disturbed periods is removed, and historical normal data or data from adjacent nodes is used for interpolation and completion. If data is determined to be severely affected by mining cart interference, the data from that period is directly removed to prevent it from misleading subsequent analysis. For example, if the gas concentration data at a node is detected to fluctuate abnormally when a mining cart passes, exceeding the normal fluctuation range by several times, it is determined to be disturbed data and removed.

[0098] For some disturbed data that still has some reference value, time series interpolation is used. This method uses historical normal data from the same period or data from adjacent, uninterrupted nodes, and performs interpolation calculations according to certain weights (such as distance weighting and time weighting) to complete the data for the disturbed period. For example, if a node is disturbed from 2:00 PM to 2:05 PM, the historical normal data from 1:55 PM to 1:59 PM and the data from adjacent nodes from 2:05 PM to 2:10 PM can be used to generate alternative data for 2:00 PM to 2:05 PM using methods such as linear interpolation.

[0099] Trigger the cleaning device to start and clean up the impact of environmental disturbances on multi-source data acquisition nodes.

[0100] When the dust concentration around a data collection node rises sharply due to the passage of a mining truck, potentially affecting the normal operation of the sensor, a start signal is sent to the cleaning device to eliminate the impact of environmental disturbances on the multi-source data collection node. For example, if the dust density exceeds a preset threshold, the cleaning device is immediately activated, using methods such as pulse jets to remove dust from the sensor surface and surrounding areas, restoring monitoring accuracy.

[0101] Example 2 is basically as shown in the attached Figures 1-6 shown The only difference from the above embodiment 1 is that the cleaning device includes a base 1, which serves as a supporting structure of the cleaning device and is fixedly installed near the multi-source data acquisition node.

[0102] The base 1 is provided with a ventilation pipe 2 which is responsible for guiding the airflow and is the airflow conveying channel of the entire cleaning device. Figure 1 Only a portion of ventilation pipe 2 is shown; it is actually laid along the length of the mine tunnel. In this embodiment, the outlet of ventilation pipe 2 is located outside the mine. The inlet of ventilation pipe 2 is connected to an air supply mechanism (not shown) for conveying air into ventilation pipe 2.

[0103] Specifically, the distribution mechanism mainly includes a fan, a screen, and a flexible connecting pipe. The fan provides the airflow power source for the entire cleaning device. Its air inlet is equipped with a screen to filter the air entering the fan, preventing large particles of impurities from entering the fan and extending the service life of the fan. One end of the flexible connecting pipe is connected to the air outlet of the fan, and the other end is connected to the ventilation pipe 2, which is used to transport the airflow generated by the fan into the ventilation pipe 2. The design of the flexible connecting pipe can effectively reduce the impact of fan vibration on the ventilation pipe 2 and other components, thereby improving the stability and service life of the entire device.

[0104] Combined with attachment Figure 3 As shown, the ventilation pipe 2 is respectively connected to a first branch pipe 101 and a second branch pipe 102, the first branch pipe 101 is connected to a jet mechanism, and the second branch pipe 102 is connected to a dynamic adjustment mechanism. The jet mechanism is used to perform pulse jet cleaning on the collection end of the multi-source data collection node; the dynamic adjustment mechanism is used to dynamically adjust the cleaning intensity of the jet mechanism based on the current dust situation near the substrate 1.

[0105] Specifically, the jet mechanism includes a nozzle 3. In this embodiment, one nozzle 3 is provided. In some other embodiments, the number of nozzles 3 can be determined according to actual needs. Preferably, an arc-shaped groove is provided on one side of the base 1 close to the multi-source data acquisition node, and the nozzle 3 is fixedly connected to the groove at an angle. An exhaust channel 117 is provided in the nozzle 3. The exhaust channel 117 includes a contraction section and a gradual expansion section. Specifically, the exhaust channel 117 is similar to a Laval nozzle structure, and a significant increase in gas flow rate is achieved through the isentropic flow principle. The front half of the exhaust channel 117 is a contraction section, and the gas gradually contracts from a larger cross-sectional area to a narrow throat. In this process, the flow rate of the gas continues to increase, while the pressure gradually decreases. After the contraction section is an expansion section, the gas diffuses outward from the narrow throat. Since the gas flow rate has reached a high speed at the narrow throat, when it enters the expansion section, the flow rate continues to increase and enters the high-speed flow stage.

[0106] Figure 4The right end of the central exhaust channel 117 is connected to the piston groove 115. A first one-way valve 118 is installed at the connection between the exhaust channel 117 and the piston groove 115 to prevent gas from flowing back into the piston groove 115. A piston block 116 slidably fits within the piston groove 115. The piston groove 115 is connected to the first branch pipe 101. A second one-way valve (not shown) is installed at the connection between the piston groove 115 and the first branch pipe 101 to prevent gas from flowing back into the first branch pipe 101. A drive mechanism is connected to the piston block 116 for driving the piston block 116 back and forth.

[0107] Specifically, combined with Figure 3 , Attachment Figure 4 and attached Figure 5 As shown, the driving mechanism includes an active cavity 103 opened in the base 1; a pair of rotating shafts 106 are symmetrically connected to the active cavity 103. Figure 3 A first bevel gear 104 is axially arranged on the middle left rotating shaft 106, and the first bevel gear 104 is fixed to the rotating shaft 106 by a key connection. The first bevel gear 104 is meshed with a second bevel gear 105, and the second bevel gear 105 is axially arranged with a turbine. Preferably, in this embodiment, the second bevel gear 105 is connected and fixed to the turbine by a shaft, and the shaft passes through the inner wall of the active cavity 103 and is fixedly welded to the turbine axial direction. A groove for accommodating the rotation of the turbine is opened in the ventilation pipe 2, and the turbine is rotatably connected to the groove. When the airflow flows in the ventilation pipe 2, it can drive the turbine to rotate.

[0108] Combined with attachment Figure 3 As shown, the rotating shafts 106 are welded and fixed with rotating carriers 107 near one end, and the rotating carriers 107 are eccentrically connected with a first connecting rod 108. The other end of the first connecting rod 108 is rotatably connected with a second connecting rod 109 and a third connecting rod 110. The second connecting rod 109 and the third connecting rod 110 are independent of each other and do not interfere with each other. Figure 4 The top of the second connecting rod 109 is rotatably connected to the bottom of the piston block 116. The other end of the third connecting rod 110 is provided with an adjusting block 119, which is welded and fixed to the inner wall of the movable chamber 103. An adjusting groove 120 is provided on the adjusting block 119, and a slider 129 is slidably connected in the adjusting groove 120. The slider 129 is rotatably connected to the transfer carrier 128, and the third connecting rod 110 is rotatably connected to the transfer carrier 128.

[0109] Specifically, the dynamic adjustment mechanism includes Figure 4 The negative pressure groove 113 on the right side of the middle active cavity 103 has an elastic membrane 112 bonded and fixed in the negative pressure groove 113. The elastic membrane 112 is located at the interface between the negative pressure groove 113 and the active cavity 103. Figure 4 The left side of the middle elastic membrane 112 is rotatably connected to the fourth connecting rod 111, and the side of the elastic membrane 112 close to the active cavity 103 is rotatably connected to the fourth connecting rod 111. Figure 5 As shown, a sliding groove 121 is provided on the inner wall of the active cavity 103. Figure 5 The left end of the fourth connecting rod 111 slides in cooperation with the slide groove 121; the fourth connecting rod 111 is welded and fixed with a rack 122, the rack 122 is meshed with the first gear 123, the first gear 123 is rotatably connected to the inner wall of the movable chamber 103, and the first gear 123 is axially provided with a third bevel gear 124, the first gear 123 and the third gear are fixed by a key connection, the third bevel gear 124 is meshed with the fourth bevel gear 125, and the fourth bevel gear 125 is axially provided with an adjusting rod 126, and the adjusting rod 126 and the fourth bevel gear 125 are also fixed by a key connection. Preferably, in this embodiment, a fixing ring 130 is sleeved on the adjusting rod 126, and a slide rail 131 is also provided on the inner wall of the movable chamber 103. The fixing ring 130 slides in cooperation with the slide rail 131, and the fixing ring 130 rotates in cooperation with the adjusting rod 126, and the stability of the movement process of the adjusting rod 126 is maintained by the coordinated action of the fixing ring 130 and the slide rail 131. The end of the adjusting rod 126 away from the fourth bevel gear 125 passes through the transfer carrier 128, and the transfer carrier 128 is threadedly engaged with the adjusting rod 126. Preferably, in the embodiment, a through groove is provided in the transfer carrier 128, and an internal thread is provided on the inner wall of the through groove. An external thread 127 is provided on the outer side of the adjusting rod 126, and the threaded engagement of the adjusting rod 126 and the transfer carrier 128 is achieved through the external thread 127 and the internal thread.

[0110] Figure 4 The right side of the middle negative pressure groove 113 is connected to a negative pressure three-way pipe 114, and the other two ends of the negative pressure three-way pipe 114 are respectively connected to the negative pressure mechanism and a plurality of sensing holes 4. In this embodiment, the sensing holes 4 are arranged in an array on the top of the base 1.

[0111] Preferably, Figure 4 The bottom outlet of the medium-negative-pressure three-way pipe 114 connects to the second branch pipe 102, while the top outlet of the negative-pressure three-way pipe 114 connects to the sensing hole 4. The negative-pressure mechanism includes a throat (not shown) located at the connection between the negative-pressure three-way pipe 114 and the second branch pipe 102. In this embodiment, the throat is a narrow section within the pipe (the second branch pipe 102). It is a short, circular or elliptical pipe section with a smaller diameter than the adjacent pipe sections, forming a distinct constriction. This design significantly increases the flow velocity and correspondingly reduces the pressure of the fluid as it passes through. The throat operates based on the Venturi effect. When air flows through the throat, the cross-sectional area of the passage suddenly decreases, causing the airflow velocity to increase significantly. According to Bernoulli's equation, the static pressure of the fluid decreases accordingly. This pressure reduction creates a negative pressure region, generating sufficient suction to draw in external air or other gases.

[0112] The specific implementation process is as follows: When the data correction module determines that the multi-source data acquisition node needs to be cleaned, a start signal is sent to the cleaning device.

[0113] The fan in the air supply mechanism starts, delivering filtered, clean air through the flexible connecting tube into ventilation duct 2. The airflow within ventilation duct 2 drives the turbine to rotate. This rotation is transmitted to rotating shaft 106 via second bevel gear 105 and first bevel gear 104, causing shaft 106 to begin rotating. The rotation of rotating shaft 106 drives rotating carrier 107. Through the linkage of first connecting rod 108, second connecting rod 109, and third connecting rod 110, rotating carrier 107 converts the rotational motion into reciprocating linear motion of piston block 116 within piston groove 115.

[0114] During its reciprocating motion, piston block 116 continuously draws air from first branch pipe 101 into piston groove 115 and discharges it from piston groove 115 into exhaust passage 117. Within exhaust passage 117, the air is accelerated by the contraction section and rectified by the expansion section, forming a high-speed pulsed airflow that impacts and cleans the acquisition end of the multi-source data acquisition node, effectively removing attached dust and debris.

[0115] During the air injection process, as the air in the second branch pipe 102 flows through the throat, its narrow structure increases the airflow velocity. According to Bernoulli's equation, the pressure decreases, generating negative pressure (Venturi effect). This negative pressure acts on the negative pressure three-way pipe 114, drawing in outside air through the sensing hole 4 to offset the negative pressure. If the dust concentration near the substrate 1 is high, the sensing hole 4 will gradually become clogged with dust, increasing the negative pressure in the negative pressure tank 113. The change in negative pressure causes the elastic membrane 112 to deform, thereby causing the fourth connecting rod 111 to move, and the fourth connecting rod 111 drives the rack 122 to move synchronously, and the rack 122 drives the first gear 123 to rotate, and the rotation of the first gear 123 drives the third bevel gear 124 to rotate, and then drives the fourth bevel gear 125 to rotate, and the fourth bevel gear 125 rotates to drive the adjusting rod 126 to rotate. Since the adjusting rod 126 is threadedly matched with the transfer carrier 128, the rotation of the adjusting rod 126 drives the transfer carrier 128 to move along the length direction of the adjusting rod 126, and the movement of the transfer carrier 128 drives the slider 129 to move in the adjusting slot 120, and then drives the third connecting rod 110 to move, thereby changing the fulcrum position of the second connecting rod 109 (i.e. Figure 5In the embodiment, the hinge points of the first connecting rod 108, the second connecting rod 109 and the third connecting rod 110, and at the same time, due to the threaded fit between the adjusting rod 126 and the transfer carrier 128, are limited to the adjustment rod 126 rotating to drive the transfer carrier 128 and the slider 129 to move. Therefore, during the movement of the piston block 116, the fulcrum position will not change), thereby adjusting the stroke distance of the piston block 116 to achieve dynamic adjustment of the jet intensity to adapt to different dust concentrations. Specifically, for example, when the dust concentration is high, the negative pressure in the negative pressure tank 113 is large, and the deformation degree of the elastic membrane 112 is large. At this time, the transfer carrier 128 moves to drive the slider 129 to the bottom end of the adjusting tank 120 (as shown in the attached figure). Figure 4 (as shown), the piston block 116 has a greater stroke distance, resulting in higher jet intensity and volume. This is suitable for use in environments with high dust concentrations, ensuring effective cleaning. Conversely, when the negative pressure within the negative pressure tank 113 is low, the elastic membrane 112 deforms less, the piston block 116 has a shorter stroke distance, and the jet intensity and volume are lower. This is suitable for use in environments with lower dust concentrations, avoiding excessive cleaning and waste of resources.

[0116] The above is only an embodiment of the present invention, and common knowledge such as the specific structure and / or characteristics of the scheme is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A multimodal coal mine intelligent monitoring system comprising: Multi-source data collection nodes are distributed along the mine tunnels and are used to collect environmental data in real time. They are characterized by: The mine car positioning module is used to determine whether there is a mine car in the current mine based on the time series fluctuation characteristics of environmental data. If a mine car is present, it will identify the operating status of the mine car, including its direction of travel, speed, and current location area; The interference judgment module dynamically demarcates the interference area based on the operating status of the mine car and the temporal correlation of data disturbances collected by adjacent multi-source data acquisition nodes; The data correction module marks the sensor data in the interfered area and performs at least one of the following operations: Eliminate data from disturbed periods and use historical normal data or adjacent node data for interpolation and completion; Trigger the cleaning device to start and clean up the impact of environmental disturbances on multi-source data acquisition nodes.

2. The multimodal coal mine intelligent monitoring system according to claim 1, characterized in that: The environmental data includes gas concentration, temperature and humidity, air pressure and dust density.

3. The multimodal coal mine intelligent monitoring system according to claim 2, characterized in that: The interference judgment module defines the interference area based on the following logic: Align the timestamps of data fluctuations at adjacent multi-source data collection nodes and extract the fluctuation propagation direction and time difference; Calculate the mine car speed based on the mine tunnel topology map; Predict the time window for the mine car to reach the next monitoring area based on the mine car's speed and the branching situation in the mine tunnel; Analyze the trajectory of the mine car in the mine tunnel, and predict the monitoring area that the mine car passes through based on the branching of the mine tunnel and the direction of the mine car; Based on the mine car's speed and the wind speed in the mine tunnel, estimate the range of airflow disturbance generated when the mine car passes through the multi-source data collection node; The temporal correlation of data disturbances collected by adjacent multi-source data acquisition nodes is analyzed. If data fluctuations occur at multiple nodes within the time window when the mine car passes, and the direction of the fluctuation propagation is consistent with the direction of the mine car's travel, and the time difference is consistent with the mine car's travel speed and the mine tunnel structure, the area where these nodes are located is determined to be the disturbed area.

4. The multimodal coal mine intelligent monitoring system according to claim 3, characterized in that: It also includes a correction module, which is used to use historical data to analyze the disturbance characteristics of the mine car on the multi-source data collection node data under different operating conditions, establish a correlation model between the mine car operating status and the data disturbance characteristics; and dynamically correct the time window affected by the mine car interference based on the correlation model.

5. The multimodal coal mine intelligent monitoring system according to claim 4, characterized in that: The cleaning device comprises a base (1); a ventilation pipe (2) passes through the base (1), and the ventilation pipe (2) is connected to an air supply mechanism for conveying airflow into the ventilation pipe (2); a first branch pipe (101) and a second branch pipe (102) are respectively connected to the ventilation pipe (2), the first branch pipe (101) is connected to an air jet mechanism, and the second branch pipe (102) is connected to a dynamic adjustment mechanism, the air jet mechanism is used to perform pulse jet cleaning on a collection end of a multi-source data collection node; the dynamic adjustment mechanism is used to dynamically adjust the cleaning intensity of the air jet mechanism based on the current dust situation near the base (1).

6. The multimodal coal mine intelligent monitoring system according to claim 5, characterized in that: The air supply mechanism includes a fan, a screen and a flexible connecting pipe; the flexible connecting pipe is used to connect the air outlet of the fan and the ventilation pipe (2), and the screen is arranged in the air inlet of the fan.

7. The multimodal coal mine intelligent monitoring system according to claim 6, characterized in that: The jet mechanism comprises a nozzle (3); the nozzle (3) is fixedly connected to one side of the base (1); an exhaust channel (117) is provided in the nozzle (3); the exhaust channel (117) comprises a contraction section and a gradual expansion section; one end of the exhaust channel (117) is connected to a piston groove (115); a first one-way valve (118) for limiting gas backflow into the piston groove (115) is provided at the connection point between the exhaust channel (117) and the piston groove (115); a piston block (116) is slidably fitted in the piston groove (115); the piston groove (115) is connected to a first branch pipe (101); a second one-way valve for limiting gas backflow into the first branch pipe (101) is provided at the connection point between the piston groove (115) and the first branch pipe (101); a driving mechanism is transmission-connected to the piston block (116); the driving mechanism is used to drive the piston block (116) to move back and forth.

8. The multimodal coal mine intelligent monitoring system according to claim 7, characterized in that: The driving mechanism comprises an active cavity (103) provided in a base body (1); a pair of rotating shafts (106) are symmetrically connected in rotation in the active cavity (103); a first bevel gear (104) is axially fixedly connected to any one of the rotating shafts (106); the first bevel gear (104) is meshed with a second bevel gear (105); a turbine is axially provided on the second bevel gear (105); and the turbine is rotationally connected to the ventilation pipe (2); The rotating shafts (106) are each provided with a rotating carrier (107) at one end close to each other, and a first connecting rod (108) is eccentrically connected to the rotating carriers (107). The other end of the first connecting rod (108) is connected to the second connecting rod (109) and the third connecting rod (110). The other end of the second connecting rod (109) is connected to the piston block (116). The other end of the third connecting rod (110) is provided with an adjusting block (119). The adjusting block (119) is provided with an adjusting groove (120). A slider (129) is connected in a sliding manner in the adjusting groove (120). A transfer carrier (128) is connected to the slider (129). The third connecting rod (110) is connected to the transfer carrier (128).

9. The multimodal coal mine intelligent monitoring system according to claim 8, characterized in that: The dynamic adjustment mechanism includes a negative pressure groove (113) provided on one side of the active cavity (103), an elastic membrane (112) provided in the negative pressure groove (113), the elastic membrane (112) being rotatably connected to a fourth connecting rod (111) on a side close to the active cavity (103), a sliding groove (121) further provided on the inner wall of the active cavity (103), the fourth connecting rod (111) being in sliding engagement with the sliding groove (121); a rack (122) being provided on the fourth connecting rod (111), the rack (122 being engaged with a first gear (123), the first gear (123) being axially provided with a third bevel gear (124), the third bevel gear (124) being engaged with a fourth bevel gear (125), an adjustment rod (126) being axially provided with the fourth bevel gear (125), the adjustment rod (126) being away from the fourth bevel gear (125) and penetrating a transfer carrier (128), the transfer carrier (128) being threadedly engaged with the adjustment rod (126); The negative pressure groove (113) is connected to a negative pressure three-way pipe (114), and the other two ends of the negative pressure three-way pipe (114) are respectively connected to a negative pressure mechanism and a plurality of sensing holes (4).

10. The multimodal coal mine intelligent monitoring system according to claim 9, characterized in that: The negative pressure three-way pipe (114) is connected to the second branch pipe (102), and the negative pressure mechanism includes a throat provided in the second branch pipe (102), and the throat is located at the connection point between the negative pressure three-way pipe (114) and the second branch pipe (102).

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