Fixed coal mine underground roadway surrounding rock deformation monitoring and alarming device and method

Abstract

The invention discloses a fixed coal mine underground roadway surrounding rock deformation monitoring and alarming device and method, relates to the technical field of roadway surrounding rock monitoring, and aims to solve the problem that a conventional monitoring device cannot effectively and comprehensively collect roadway wall deformation parameters due to the influence of factors such as dust and water mist in a coal mine underground roadway. The device comprises two parts, namely a fixed bracket and a self-balancing monitoring system, wherein the self-balancing monitoring system comprises a holder stabilizer, a connecting component and a monitoring system module; wherein the monitoring system module comprises a controller, a communication module, a signal processing module, a narrow beam radar ranging module, a power supply module and a cable interface; wherein the controller is used for controlling the working modes of the four radars in the monitoring module and adjusting the cuboid shell to be in the horizontal position through the horizontal sensor and the holder controller; the communication module is used for packing and transmitting the deformation data acquired by each monitoring system module and performing real-time communication with a ground receiving end; the signal processing module processes information of narrow beam radar cyclic ranging and obtains deformation information. According to the invention, deformation parameters of the roadway wall can be effectively and comprehensively collected, data can be comprehensively analyzed, and early warning service can be provided.

Description

Technical Field

[0001] This invention relates to the field of roadway surrounding rock monitoring technology, specifically to a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device and method. Background Technology

[0002] Coal mine underground roadways are a hazardous working environment. Common accident types in underground roadways include gas leaks, mine collapses, water leakage from rock walls, mechanical equipment collisions, and electrical short circuits. Monitoring underground roadway deformation can effectively prevent collapses and water leakage, thus requiring effective monitoring. However, when using sensors in the underground environment, the performance of optical and laser sensors is often affected or even malfunctions due to factors such as dust and water mist. 81GHz millimeter-wave radar is a high-frequency radar system with strong penetration capabilities in the underground environment, effectively penetrating interference from dust and water mist. Compared to optical and laser sensors, millimeter-wave radar has advantages such as high resolution, high precision, and strong anti-interference capabilities, effectively reducing false alarm and missed alarm rates. Furthermore, millimeter-wave radar features miniaturization, modularity, and low power consumption, making it easier to integrate into existing coal mine safety systems. The small size and modular design of millimeter-wave radar not only help improve system reliability and stability but also reduce energy consumption and lower system operating costs. In the future, millimeter-wave radar is expected to become the mainstream equipment for safety monitoring in underground coal mine roadways.

[0003] Document CN217083639U discloses a device for measuring the deformation of surrounding rock in underground coal mine roadways. The device includes a telescopic rod with graduated markings on its surface and a hook fixedly connected to its top. The hook engages with a suspension device located at a measurement point in the roadway. A first level bubble is located on the bottom end face of the telescopic rod, and a second level bubble is located on the surface of the rod itself. The hook engages with the upper middle measurement point in the roadway and is suspended vertically, acting as a plumb line. Another device engages with the suspension device at either the left or right middle measurement point. The first and second level bubbles ensure that the two devices are in vertical and horizontal positions, respectively. The intersection of these two points represents the position coordinates of the left or right middle measurement point and the upper middle measurement point. By comparing these coordinates with the previous measurement, the deformation of the surrounding rock at the roadway measurement point can be obtained. This method is fast, efficient, and more reliable.

[0004] Document CN110953008A discloses a roadway surrounding rock deformation monitoring anchor bolt, online monitoring device, and monitoring method, belonging to the field of coal mine underground roadway surrounding rock control technology. It solves the problems of existing roadway surrounding rock deformation monitoring methods being severely affected by human factors and unable to reflect the stress and deformation state of the roadway surrounding rock in a real-time, intuitive, and effective manner. The monitoring anchor bolt of this invention includes an anchor bolt body and an anchor bolt tray; the anchor bolt tray displays different colors under different deformation conditions, and the degree of roadway surrounding rock deformation is monitored by the color change of the anchor bolt tray; the anchor bolt tray includes a tray end face and a tray recess, with a central hole on the bottom surface of the tray recess, the size of which matches the anchor bolt body; the wall thickness of the tray recess is greater than the wall thickness of the tray end face, and the longitudinal section of the side wall of the tray recess is arc-shaped. This invention's monitoring anchor bolt and online monitoring device can monitor the deformation of roadway surrounding rock in real time.

[0005] However, the existing technologies mentioned above cannot collect deformation parameters of the surrounding rock in a comprehensive and efficient manner during monitoring, which leads to an inability to effectively analyze deformation and issue early warnings. Summary of the Invention

[0006] In view of the above problems, the present invention proposes a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device and method to solve the problem that existing monitoring devices including radar cannot collect roadway surrounding rock deformation parameters in a comprehensive and efficient manner, thus failing to effectively analyze deformation and provide early warning.

[0007] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0008] A fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device includes two parts: a fixed support frame 1 and a self-balancing monitoring system 2; the fixed support frame 1 is used to install the self-balancing monitoring system 2 in the coal mine underground roadway or on the surrounding rock of the coal mine underground roadway;

[0009] The self-balancing monitoring system includes a gimbal stabilizer 21, a connecting component 22, and a monitoring system module 23;

[0010] The monitoring system module 23 includes a square housing, four narrow-beam radar ranging modules 233 installed inside the square housing, and a horizontal sensor 235 installed on the square housing. The end face of the square housing perpendicular to the four narrow-beam radar ranging modules 233 can be connected to one end of the gimbal stabilizer 21 through the connecting member 22, and the other end of the gimbal stabilizer 21 is connected to the fixed support 1.

[0011] The fixed support frame 1 controls the square shell, four narrow beam radar ranging modules 233 and horizontal sensor 235 to monitor the specific location of the surrounding rock in the underground roadway of the coal mine.

[0012] A narrow-beam radar ranging module 233 is attached to the horizontal plane at the top and bottom of the square shell, and a narrow-beam radar ranging module 233 is attached to the vertical plane at the left and right ends of the square shell; the four narrow-beam radar ranging modules 233 are used to monitor the deformation of the surrounding rock (top, bottom, front, and back) of the underground roadway in the coal mine.

[0013] The level sensor 235 transmits the measured level data of the square shell to the controller, and the controller controls the gimbal stabilizer 21 to keep the square shell level. The level sensor and the gimbal controller adjust the cube shell to a level position.

[0014] The deformation data of the surrounding rock measured by the four narrow-beam radar ranging modules 233 is transmitted to the signal processing module 232 for processing through the cable interface, and then sent to the ground receiving end through the communication module 231.

[0015] The controller is also used to control the working sequence (working in turn) and working time of the four narrow beam radar ranging modules 233 (the controller is used to control the working mode of the four radars in the monitoring module);

[0016] The power supply module 234 is used to supply power to the narrow beam radar ranging module 233, the horizontal sensor 235 mounted on the housing, the controller, the communication module 231, and the signal processing module 232.

[0017] Furthermore, four 81GHz narrow-beam millimeter-wave radars are attached to the four walls of the square housing of the monitoring system module (upper, lower, left, and right corresponding to the four walls of the tunnel). The radar beamwidth is ±5°, the detection range is 10m, and the range resolution is 3mm. They are used to monitor the deformation of the upper, lower, left, and right walls of the tunnel.

[0018] The communication module of the monitoring system module includes a 485 bus and a LoRa module. The two communication modules adopt a combination of wired and wireless methods (to overcome the problem of failure of a single method). The data from the top, bottom position and lateral position ranging modules are transmitted to the signal processing module in sequence. After the signal processing module processes the radar data, it packages and transmits the deformation data acquired by each monitoring system module through the 485 bus and LoRa module to communicate with the ground receiving end in real time.

[0019] The signal processing module processes the information from the narrow-beam radar's cyclic ranging (cyclic ranging means that each radar module works for only 30 seconds, with a 5-minute interval, and so on). Each radar module acquires periodic data, and the deformation information is obtained by processing the periodic data acquired within 1 hour.

[0020] A method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway includes the following steps:

[0021] Step 1: Divide a tunnel into 4 monitoring areas: tunnel top, tunnel bottom, left side, and right side. To better monitor the tunnel, install a radar beacon (corner reflector) at the top of each monitoring area and install corresponding radar beacons at the positions of the lateral monitoring areas. Scan the top, bottom, and lateral positions sequentially to obtain radar detection data parameters. Since the radar mounting bracket is fixed at the bottom or side, the measurement data of one side can be reduced.

[0022] The specific process of using radar to monitor the top and lateral positions within a working cycle includes: within a cycle, the radar scans the corresponding top position radar beacon, bottom position radar beacon, and lateral position radar beacon respectively to obtain the area data of the key areas of interest in the top and lateral positions;

[0023] Step 2: Define a certain range within each monitoring area where the radar beacon is located as the key monitoring area. Perform periodic scanning on the key monitoring area. Since the radar will report all points in the illumination area whose intensity exceeds the threshold (radar illumination is a beam, and the rock wall is a non-uniform flat surface, so several target points with near-range resolution can be obtained), a set of data can be obtained. Analyze the point group data of the key monitoring area obtained by the radar. After numerical sorting, use the strong and near filtering method and the multipath matching elimination method to eliminate multipath false targets. Set a threshold limit condition for a set of echo points in the key monitoring area. Compare the radar data in one cycle with the radar data of the position point in the previous cycle. Pixels that exceed the threshold limit condition are regarded as deformed points.

[0024] The specific process of the periodic scanning includes: starting from the beginning of this scan, analyzing the top and side point group data and traversing the radar image points in sequence, and the time interval until the start of the next scan is one cycle. The time interval of each cycle is adjusted according to specific environmental factors. When the deformation at a certain location exceeds the set risk threshold and an alarm is issued, the corresponding monitoring time interval should be shortened to conduct more intensive monitoring.

[0025] The specific process of traversing the radar image includes: based on the depth-first traversal algorithm, starting from the initial node A and marking the initial node A as visited, after visiting the initial node A, randomly select an unvisited adjacent node B, then mark the selected adjacent node B as visited, and use adjacent node B as the initial node, and then randomly select the next unvisited adjacent node C, and so on until all nodes have been visited.

[0026] Step 3: Based on the DBSCAN density clustering algorithm, target points exceeding the threshold limit are taken as core points. Starting from the core points, the point groups are clustered according to the density of the distribution of deformed points. Point groups that meet the judgment conditions are divided into clusters. The area of ​​the deformed region is calculated based on the sum of the areas of deformed points within the cluster.

[0027] Step 4: Calculate the change in deformation area at each location by subtracting the deformation area of ​​the previous cycle from the deformation area of ​​the current cycle, and record the detection data; when the change in deformation area at each location exceeds the set risk threshold, issue an alarm message.

[0028] Furthermore, the specific process of eliminating multipath false targets in step two includes: after acquiring the detection radar data parameters, using the Minimum Variance Distortionless Response Algorithm (MVDR algorithm) to obtain the initial target's angle parameter θ1, and calculating the initial target's position coordinates O1(x1, y1) based on the obtained angle parameter, where the formulas for calculating the horizontal and vertical coordinates are:

[0029]

[0030] Where φ is the angle between the direction of the millimeter-wave radar array and the horizontal direction, and R is the distance from the target to the radar;

[0031] By combining the reflection patterns during electromagnetic wave propagation and the distance L from the radar to the reflecting surface, the position coordinates of the other three multipath targets can be calculated. Finally, a set of initial targets are arranged in ascending order according to their distances to the radar. Then, for the first initial target, the position coordinates of its corresponding three multipath targets and the distance errors with other initial targets are calculated. If the distance error is less than 1 meter, the initial target is considered a real target, the coordinate values ​​are retained, and the remaining initial targets that match its corresponding multipath targets are deleted. The above process is repeated for the remaining initial targets to identify real targets and delete the corresponding false multipath targets until all real targets are identified.

[0032] Furthermore, the Minimum Variance Distortionless Response (MVDR) algorithm is an adaptive beamforming algorithm based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion. It can measure the angle parameters of targets at different angles at the same distance without requiring additional prior information.

[0033] Furthermore, the propagation paths of the other three multipath targets are as follows: radar → beacon → reflector → radar, radar → reflector → beacon → radar, and radar → reflector → beacon → reflector → radar.

[0034] The calculation process for the position coordinates corresponding to the multipath target's path "radar → reflector → beacon → reflector → radar" is as follows: Combining the reflection law during electromagnetic wave propagation, the position coordinates O2(x2,y2) of the mirror-reflecting target are calculated using the initial target's position coordinates O1(x1,y1). The formulas for calculating the horizontal and vertical coordinates are as follows:

[0035]

[0036] Where L is the distance from the radar to the reflecting surface.

[0037] Furthermore, the calculation process for the position coordinates corresponding to the multipath target paths "radar → reflector → beacon → radar" and "radar → beacon → reflector → radar" is as follows: combining the multipath target O 21 Based on the angle and distance characteristics, using the initial target's position coordinates O1(x1,y1) and the mirror reflection target's position coordinates O2(x2,y2), calculate O 21 Distance R to radar 21 :

[0038]

[0039] Then combine multipath target O 12 The angle and distance characteristics, and its distance R from the radar. 12 With R 21 If they are the same, then the target O can be calculated. 12 O 21 azimuth angle θ 12 θ 21 The calculation formula is:

[0040]

[0041] Wherein, angle θ 12 =θ2, θ 12 =θ2;

[0042] Then calculate O respectively. 12 O 21 Position coordinates (x) 12 ,y 12 ), (x 21 ,y 21 The calculation formula is:

[0043]

[0044] The formula for calculating the distance error is:

[0045]

[0046] Where, x i yi These are the horizontal and vertical coordinates of the three multipath targets.

[0047] Further, the threshold constraints in step two are the distance change threshold and the deformation rate change threshold. These thresholds are set by analyzing the maximum distance change and the fastest deformation rate change in historical detection data, and adjusted according to specific environmental factors. The historical detection data refers to the distance change and deformation rate change of radar-measured parameters within one cycle relative to the radar-measured parameters of the previous cycle. The mathematical expressions for the distance change L and deformation rate V at time T within the time interval Δt are as follows:

[0048]

[0049]

[0050] Further, the specific process of density clustering in step three is as follows: Set the neighborhood radius R and the minimum number of pixels (MinPoints) within the neighborhood. Traverse all pixels in the radar image and take any pixel that exceeds the threshold condition as the core point. Start from the initial core point and diffuse outwards to the density-reachable area. If there are at least MinPoints deformed pixels within the neighborhood radius R, then all deformed pixels in the neighborhood are considered to belong to the same cluster. Repeat the above operation until all deformed pixels that meet the threshold condition and are directly reachable from the core point density are included. Finally, a DBSCAN cluster is formed, which is density-reachable from all core points and contains the set of deformed pixels in each neighborhood. The number of deformed pixels in the neighborhood of each core point in the cluster is not less than MinPoints.

[0051] The density can be reached if the density from core point 1 to core point 2 is directly accessible, and the density from core point 2 to core point 3 is directly accessible, then the density from core point 1 to core point 3 is accessible; the density can be reached if all deformed pixels with a neighborhood radius R centered on the core point are directly accessible to the density of the core point.

[0052] Furthermore, in step three, when calculating the area of ​​the deformed region based on the sum of the pixel areas, since a single pixel in the actual deformed region is not a regular rectangle but rather a fan-shaped ring, and the further the target is from the radar, the larger the fan-shaped ring of a single pixel becomes, the actual deformed area can be obtained by calculating the sum of the areas of the fan-shaped rings of a single pixel. The mathematical expression is:

[0053]

[0054] Where α is the azimuth resolution, β is the range resolution, r is the radar near range, and d is the range sampling position;

[0055] The risk threshold mentioned in step four is 10% of the maximum change in deformation area over N consecutive working cycles in the historical detection data.

[0056] The beneficial technical effects of this invention are:

[0057] The "fixed" in the present invention, referring to a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device and method, means that the self-balancing monitoring system is installed in the coal mine underground roadway or on the surrounding rock of the underground roadway via a fixed support frame. This invention solves the problem that conventional monitoring devices cannot effectively and comprehensively collect roadway wall deformation parameters due to the influence of dust, water mist, and other factors in underground coal mine roadways. Key technical points of this invention: It comprises two parts: a fixed support frame and a self-balancing monitoring system. The self-balancing monitoring system includes a gimbal stabilizer, connecting components, and a monitoring system module. The monitoring system module includes a controller, a communication module, a signal processing module, a narrow-beam radar ranging module, a power supply module, and a cable interface. The controller controls the operating modes of the four radars in the monitoring module and adjusts the cube shell to a horizontal position through a level sensor and the gimbal controller. The communication module packages and transmits the deformation data acquired by each monitoring system module, enabling real-time communication with the ground receiving end. The signal processing module processes the information from the narrow-beam radar cyclic ranging and obtains deformation information. This invention can effectively and comprehensively collect deformation parameters of tunnel walls, fully analyze the data, and provide early warning services. Attached Figure Description

[0058] The present invention can be better understood by referring to the description given below in conjunction with the accompanying drawings, which together with the detailed description below are incorporated in and form part of this specification, and serve to further illustrate preferred embodiments of the invention and explain the principles and advantages of the invention.

[0059] Figure 1 This is a schematic diagram of the embedded wall structure of a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device according to the present invention;

[0060] Figure 2 This is a schematic diagram of the insertion structure of a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device according to the present invention;

[0061] Figure 3 This is a schematic diagram of the detection range of the millimeter-wave radar in this invention;

[0062] Figure 4 This is a flowchart of a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm method according to the present invention;

[0063] Figure 5 This is a schematic diagram of DBSCAN density clustering in this invention;

[0064] Figure 6 This is a schematic diagram of the radar signal path and three multipath interference paths in this invention;

[0065] Figure 7 This is a schematic diagram of the radar image traversal process in this invention. Detailed Implementation

[0066] To enable those skilled in the art to better understand the present invention, exemplary embodiments or examples of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments or examples are merely some, not all, of the embodiments or examples of the present invention. All other embodiments or examples obtained by those skilled in the art based on the embodiments or examples of the present invention without inventive effort should fall within the scope of protection of the present invention.

[0067] like Figure 1-7 This invention proposes a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device, comprising two parts: a fixed support frame and a self-balancing monitoring system. The self-balancing monitoring system includes a gimbal stabilizer, connecting components, and a monitoring system module. One end of the gimbal stabilizer is connected to the fixed support frame, and the other end is connected to the monitoring system module, both secured with nuts. The monitoring system module is a cubic shell, with a horizontal sensor attached to its upper surface. The sensor is connected to the gimbal controller via a cable, ensuring the shell is in a horizontal position.

[0068] The fixed support is a linkage assembly with a rotatable clamp at the joint; the fixed support has a triangular claw anchor at the bottom, which can be inserted into a wall or the ground.

[0069] The monitoring system module includes a controller, a communication module, a signal processing module, a narrow-beam radar ranging module, a power supply module, and a cable interface.

[0070] The monitoring system module has four 81GHz narrow-beam millimeter-wave radars attached to the four walls of the cubic shell (top, bottom, left, and right corresponding to the four walls of the tunnel). The radar beamwidth is ±5°, the detection range is 10m, and the range resolution is 3mm. These radars are used to monitor the deformation of the four walls of the tunnel.

[0071] The communication module of the monitoring system module includes a 485 bus and a LoRa module. The two communication modules adopt a combination of wired and wireless methods to overcome the problem of failure of a single method. The data from the top, bottom position and lateral position ranging modules are transmitted to the signal processing module in sequence. After the signal processing module processes the radar data, it packages and transmits the deformation data acquired by each monitoring system module through the 485 bus and LoRa module to communicate with the ground receiver in real time.

[0072] The signal processing module processes the information from the narrow-beam radar's cyclic ranging (cyclic ranging means that each radar module works for only 30 seconds, with a 5-minute interval, and so on). Each radar module acquires periodic data, and the deformation information is obtained by processing the periodic data acquired within 1 hour.

[0073] The controller is a high-performance, low-power DSP chip used to control the four narrow-beam millimeter-wave radars to work in turn, perform priority selection in the signal processing module, and control the communication module to transmit data. The controller is used to control the working mode of the four radars in the monitoring module and adjust the cube shell to a horizontal position through the level sensor and the gimbal controller.

[0074] The power module uses a combination of underground power lines and batteries. If the external power line is disconnected, the battery can be used as a backup power source.

[0075] The present invention also includes a ground receiving end, which includes a display module and an alarm module. The display module is used to display the data analysis results transmitted back by the communication module; the ground alarm module is used to issue a ground alarm when the relative deformation of a specific point on the rock wall exceeds a risk threshold.

[0076] This invention also provides a method for monitoring and alarming deformation of surrounding rock in fixed coal mine underground roadways, comprising the following steps:

[0077] Step 1: Divide a tunnel into 4 monitoring areas: tunnel top, tunnel bottom, left side, and right side. To better monitor the tunnel, install a radar beacon (corner reflector) at the top of each monitoring area and install corresponding radar beacons at the positions of the lateral monitoring areas. Scan the top, bottom, and lateral positions sequentially to obtain radar detection data parameters. Since the radar mounting bracket is fixed at the bottom or side, the measurement data of one side can be reduced.

[0078] Step 2: Define a certain range within each monitoring area where the radar beacon is located as the key monitoring area. Perform periodic scanning on the key monitoring area. Since the radar will report all points in the illumination area whose intensity exceeds the threshold (radar illumination is a beam, and the rock wall is a non-uniform flat surface, so several target points with near-range resolution can be obtained), a set of data can be obtained. Analyze the point group data of the key monitoring area obtained by the radar. After numerical sorting, use the strong and near filtering method and the multipath matching elimination method to eliminate multipath false targets. Set a threshold limit condition for a set of echo points in the key monitoring area. Compare the radar data in one cycle with the radar data of the position point in the previous cycle. Pixels that exceed the threshold limit condition are regarded as deformed points.

[0079] Step 3: Based on the DBSCAN density clustering algorithm, target points exceeding the threshold limit are taken as core points. Starting from the core points, the point groups are clustered according to the density of the distribution of deformed points. Point groups that meet the judgment conditions are divided into clusters. The area of ​​the deformed region is calculated based on the sum of the areas of deformed points within the cluster.

[0080] Step 4: Calculate the change in deformation area at each location by subtracting the deformation area of ​​the previous cycle from the deformation area of ​​the current cycle, and record the detection data; when the change in deformation area at each location exceeds the set risk threshold, issue an alarm message.

[0081] The specific process of using radar to monitor the top and lateral positions within one working cycle in step one includes: within one cycle, the radar scans the corresponding top position radar beacon, bottom position radar beacon, and lateral position radar beacon respectively to obtain the area data of the key areas of interest in the top and lateral positions.

[0082] The specific process of the periodic scanning described in step two includes: starting from the beginning of this scan, analyzing the top and side point group data and traversing the radar image points in sequence, and the time interval until the start of the next scan is one cycle. The time interval of each cycle is adjusted according to specific environmental factors. When the deformation at a certain location exceeds the set risk threshold and an alarm is issued, the corresponding monitoring time interval should be shortened to conduct more intensive monitoring.

[0083] The specific process of traversing the radar image includes: based on the depth-first traversal algorithm, starting from the initial node A and marking the initial node A as visited, after visiting the initial node A, randomly select an unvisited adjacent node B, then mark the selected adjacent node B as visited, and use adjacent node B as the initial node, and then randomly select the next unvisited adjacent node C, and so on until all nodes have been visited.

[0084] Step two describes the specific process for eliminating multipath false targets, which includes: after acquiring the detection radar data parameters, using the Minimum Variance Distortionless Response (MVDR) algorithm to obtain the initial target's angle parameters θ1, and calculating the initial target's position coordinates O1(x1, y1) based on the obtained angle parameters, where the formulas for calculating the horizontal and vertical coordinates are:

[0085]

[0086] Where φ is the angle between the direction of the millimeter-wave radar array and the horizontal direction, and R is the distance from the target to the radar;

[0087] By combining the reflection patterns during electromagnetic wave propagation and the distance L from the radar to the reflecting surface, the position coordinates of the other three multipath targets can be calculated. Finally, a set of initial targets are arranged in ascending order according to their distances to the radar. Then, for the first initial target, the position coordinates of its corresponding three multipath targets and the distance errors with other initial targets are calculated. If the distance error is less than 1 meter, the initial target is considered a real target, the coordinate values ​​are retained, and the remaining initial targets that match its corresponding multipath targets are deleted. The above process is repeated for the remaining initial targets to identify real targets and delete the corresponding false multipath targets until all real targets are identified.

[0088] The Minimum Variance Distortionless Response (MVDR) algorithm is an adaptive beamforming algorithm based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion. It can measure the angle parameters of targets at different angles at the same distance without requiring additional prior information.

[0089] The propagation paths of the other three multipath targets are as follows: radar → beacon → reflector → radar, radar → reflector → beacon → radar, and radar → reflector → beacon → reflector → radar.

[0090] The calculation process for the position coordinates corresponding to the multipath target's path "radar → reflector → beacon → reflector → radar" is as follows: Combining the reflection law during electromagnetic wave propagation, the position coordinates O2(x2,y2) of the mirror-reflecting target are calculated using the initial target's position coordinates O1(x1,y1). The formulas for calculating the horizontal and vertical coordinates are as follows:

[0091]

[0092] Where L is the distance from the radar to the reflecting surface.

[0093] Furthermore, the calculation process for the position coordinates corresponding to the multipath target paths "radar → reflector → beacon → radar" and "radar → beacon → reflector → radar" is as follows: combining the multipath target O 21 Based on the angle and distance characteristics, using the initial target's position coordinates O1(x1,y1) and the mirror reflection target's position coordinates O2(x2,y2), calculate O 21 Distance R to radar 21 :

[0094]

[0095] Then combine multipath target O 12 The angle and distance characteristics, and its distance R from the radar. 12 With R 21 If they are the same, then the target O can be calculated. 12 O 21 azimuth angle θ12 θ 21 The calculation formula is:

[0096]

[0097] Wherein, angle θ 12 =θ2, θ 12 =θ2;

[0098] Then calculate O respectively. 12 O 21 Position coordinates (x) 12 ,y 12 ), (x 21 ,y 21 The calculation formula is:

[0099]

[0100] The formula for calculating the distance error is:

[0101]

[0102] Where, x i y i These are the horizontal and vertical coordinates of the three multipath targets.

[0103] The threshold constraints in step two are the distance change threshold and the deformation rate change threshold. These thresholds are set by analyzing the maximum distance change and the fastest deformation rate change in historical detection data, and adjusted according to specific environmental factors. The historical detection data refers to the distance change and deformation rate change of radar data parameters measured within one cycle relative to the radar data parameters measured in the previous cycle. The mathematical expressions for the distance change L and deformation rate V at time T within the time interval Δt are as follows:

[0104]

[0105]

[0106] The specific process of density clustering in step three is as follows: Set the neighborhood radius R and the minimum number of pixels (MinPoints) within the neighborhood. Traverse all pixels in the radar image and take any pixel that exceeds the threshold condition as the core point. Start from the initial core point and diffuse outwards to the density-reachable area. If there are at least MinPoints deformed pixels within the neighborhood radius R, then all deformed pixels in the neighborhood are considered to belong to the same cluster. Repeat the above operation until all deformed pixels that meet the threshold condition and are directly reachable from the core point density are included. Finally, a DBSCAN cluster is formed, which is a set of deformed pixels in each neighborhood that is reachable from all core points density. The number of deformed pixels in the neighborhood of each core point in the cluster is not less than MinPoints.

[0107] The density can be reached if the density from core point 1 to core point 2 is directly accessible, and the density from core point 2 to core point 3 is directly accessible, then the density from core point 1 to core point 3 is accessible; the density can be reached if all deformed pixels with a neighborhood radius R centered on the core point are directly accessible to the density of the core point.

[0108] In step three, when calculating the area of ​​the deformed region based on the sum of the pixel areas, since a single pixel in the actual deformed region is not a regular rectangle but rather a fan-shaped ring, and the farther the target is from the radar, the larger the fan-shaped ring of a single pixel becomes, the actual deformed area can be obtained by calculating the sum of the areas of the fan-shaped rings of a single pixel. The mathematical expression is:

[0109]

[0110] Where α is the azimuth resolution, β is the range resolution, r is the radar near range, and d is the range sampling position.

[0111] The risk threshold mentioned in step four is 10% of the maximum change in deformation area over N consecutive working cycles in the historical detection data.

[0112] Implementation Case:

[0113] This invention provides a fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device, which includes two parts: a fixed support frame 1 and a self-balancing monitoring system 2. The self-balancing monitoring system 2 includes a gimbal stabilizer 21, a connecting component 22, and a monitoring system module 23. One end of the gimbal stabilizer 21 is connected to the fixed support frame 1, and the other end is connected to the monitoring system module 23, both of which are fixed with nuts.

[0114] The fixed support 1 can be a linkage assembly 11, with a rotatable clamp 12 at the joint for fixation (the middle of the horizontal bar and the upper end of the vertical bar are hinged); the fixed support 1 has a triangular claw fixing anchor 13 at the bottom, which can be inserted into the wall or the ground; a certain end of the linkage mechanism on the fixed support 1 can be connected to the surrounding rock.

[0115] The positions of the four 81GHz narrow-beam millimeter-wave radars 233 in the monitoring system module 23 are adjusted by fixing the support frame 1.

[0116] The monitoring system module 23 includes a controller, a communication module 231, a signal processing module 232, a narrow-beam radar ranging module 233, a power supply module 234, and a cable interface. The monitoring system module 23 is a cubic shell. A horizontal sensor 235 is attached to the upper surface of the shell. The horizontal sensor 235 is connected to the pan-tilt controller via a cable to keep the shell in a horizontal position. Four 81GHz narrow-beam millimeter-wave radars 233 are attached to the four walls of the cubic shell of the monitoring system module 23 (top, bottom, left, and right corresponding to the four walls of the tunnel). The radar beamwidth is ±5°, the detection range is 10m, and the range resolution is 3mm. They are used to monitor the deformation of the four walls of the tunnel.

[0117] The communication module 231 of the monitoring system module 23 includes a 485 bus and a LoRa module. The two communication modules adopt a combination of wired and wireless methods to overcome the problem of failure of a single method. The data from the top, bottom position and lateral position ranging modules are transmitted to the signal processing module 232 in sequence. After the signal processing module 232 processes the radar data, it packages and transmits the deformation data acquired by each monitoring system module through the 485 bus and LoRa module to communicate with the ground receiving end in real time.

[0118] The signal processing module 232 processes the information from the narrow-beam radar cyclic ranging. Each radar module acquires periodic data and processes the periodic data acquired within 1 hour to obtain deformation information. Both the signal processing module 232 and the millimeter-wave radar ranging module 233 are controlled by the controller.

[0119] The controller is a high-performance, low-power DSP chip used to control the four narrow-beam millimeter-wave radars 233 to work in turn, perform priority selection in the signal processing module 232, and control the communication module 231 to transmit data. The controller is used to control the working mode of the four radars in the monitoring module and adjust the cube housing to a horizontal position through the horizontal sensor 235 and the gimbal controller.

[0120] The power module 234 uses a combination of underground power line and battery. Once the external power line is disconnected, the battery can be used as backup power.

[0121] The ground receiving end includes a display module and an alarm module. The display module is used to display the data analysis results transmitted back by the communication module; the ground alarm module is used to issue a ground alarm when the relative deformation of a specific point on the rock wall exceeds a risk threshold.

[0122] The power module uses a combination of underground power lines and batteries. If the external power line is disconnected, the battery can be used as a backup power source.

Claims

1. A fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device, characterized in that, It includes two parts: a fixed support frame (1) and a self-balancing monitoring system (2); the fixed support frame (1) is used to install the self-balancing monitoring system (2) in the underground roadway of the coal mine or on the surrounding rock of the underground roadway of the coal mine. The self-balancing monitoring system includes a gimbal stabilizer (21), a connecting component (22), and a monitoring system module (23); The monitoring system module (23) includes a square housing, four narrow-beam radar ranging modules (233) installed inside the square housing, and a horizontal sensor (235) installed on the square housing; the end face of the square housing perpendicular to the four narrow-beam radar ranging modules (233) can be connected to one end of the gimbal stabilizer (21) through the connecting member (22), and the other end of the gimbal stabilizer (21) is connected to the fixed support (1); The square shell, four narrow-beam radar ranging modules (233) and horizontal sensor (235) are controlled by a fixed support frame (1) to monitor the specific location of the surrounding rock in the underground roadway of the coal mine. A narrow-beam radar ranging module (233) is attached to the horizontal plane at the top and bottom of the square shell, and a narrow-beam radar ranging module (233) is attached to the vertical plane at the left and right ends of the square shell; the four narrow-beam radar ranging modules 233 are used to monitor the deformation of the surrounding rock (top, bottom, front, and back) of the underground roadway in the coal mine. The level sensor (235) transmits the measured level data of the square shell to the controller, and the controller controls the gimbal stabilizer (21) to keep the square shell level. The level sensor and the gimbal controller adjust the cube shell to a level position. The deformation data of the surrounding rock measured by the four narrow beam radar ranging modules (233) is transmitted to the signal processing module (232) through the cable interface for processing, and then sent to the ground receiving end through the communication module (231). The controller is also used to control the working sequence (working in turn) and working time of the four narrow beam radar ranging modules 233 (the controller is used to control the working mode of the four radars in the monitoring module); The power supply module (234) is used to supply power to the narrow beam radar ranging module (233), the horizontal sensor (235) mounted on the housing, the controller, the communication module (231), and the signal processing module (232).

2. The fixed coal mine underground roadway surrounding rock deformation monitoring and alarm device according to claim 1, characterized in that, The four walls of the square housing of the monitoring system module (top, bottom, left, and right corresponding to the four walls of the tunnel) are fitted with four 81GHz narrow-beam millimeter-wave radars. The radar beamwidth is ±5°, the detection range is 10m, and the range resolution is 3mm. They are used to monitor the deformation of the four walls of the tunnel. The communication module of the monitoring system module includes a 485 bus and a LoRa module. The two communication modules adopt a combination of wired and wireless methods (to overcome the problem of failure of a single method). The data from the top, bottom position and lateral position ranging modules are transmitted to the signal processing module in sequence. After the signal processing module processes the radar data, it packages and transmits the deformation data acquired by each monitoring system module through the 485 bus and LoRa module to communicate with the ground receiving end in real time. The signal processing module processes the information from the narrow-beam radar's cyclic ranging (cyclic ranging means that each radar module works for only 30 seconds, with a 5-minute interval, and so on). Each radar module acquires periodic data, and the deformation information is obtained by processing the periodic data acquired within 1 hour.

3. A method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway, characterized in that, Includes the following steps: Step 1: Divide a tunnel into 4 monitoring areas: tunnel top, tunnel bottom, left side, and right side. To better monitor the tunnel, install a radar beacon (corner reflector) at the top of each monitoring area and install corresponding radar beacons at the positions of the lateral monitoring areas. Scan the top, bottom, and lateral positions sequentially to obtain radar detection data parameters. Since the radar mounting bracket is fixed at the bottom or side, the measurement data of one side can be reduced. The specific process of using radar to monitor the top and lateral positions within a working cycle includes: within a cycle, the radar scans the corresponding top position radar beacon, bottom position radar beacon, and lateral position radar beacon respectively to obtain the area data of the key areas of interest in the top and lateral positions; Step 2: Define a certain range within each monitoring area where the radar beacon is located as the key monitoring area. Perform periodic scanning on the key monitoring area. Since the radar will report all points in the illumination area whose intensity exceeds the threshold (radar illumination is a beam, and the rock wall is a non-uniform flat surface, so several target points with near-range resolution can be obtained), a set of data can be obtained. Analyze the point group data of the key monitoring area obtained by the radar. After numerical sorting, use the strong and near filtering method and the multipath matching elimination method to eliminate multipath false targets. Set a threshold limit condition for a set of echo points in the key monitoring area. Compare the radar data in one cycle with the radar data of the position point in the previous cycle. Pixels that exceed the threshold limit condition are regarded as deformed points. The specific process of the periodic scanning includes: starting from the beginning of this scan, analyzing the top and side point group data and traversing the radar image points in sequence, and the time interval until the start of the next scan is one cycle. The time interval of each cycle is adjusted according to specific environmental factors. When the deformation at a certain location exceeds the set risk threshold and an alarm is issued, the corresponding monitoring time interval should be shortened to conduct more intensive monitoring. The specific process of traversing the radar image includes: based on the depth-first traversal algorithm, starting from the initial node A and marking the initial node A as visited, after visiting the initial node A, randomly select an unvisited adjacent node B, then mark the selected adjacent node B as visited, and use adjacent node B as the initial node, and then randomly select the next unvisited adjacent node C, and so on until all nodes have been visited. Step 3: Based on the DBSCAN density clustering algorithm, target points exceeding the threshold limit are taken as core points. Starting from the core points, the point groups are clustered according to the density of the distribution of deformed points. Point groups that meet the judgment conditions are divided into clusters. The area of ​​the deformed region is calculated based on the sum of the areas of deformed points within the cluster. Step 4: Calculate the change in deformation area at each location by subtracting the deformation area of ​​the previous cycle from the deformation area of ​​the current cycle, and record the detection data; when the change in deformation area at each location exceeds the set risk threshold, issue an alarm message.

4. The method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway according to claim 3, characterized in that, Step two describes the specific process for eliminating multipath false targets, which includes: after acquiring the detection radar data parameters, using the Minimum Variance Distortionless Response (MVDR) algorithm to obtain the initial target's angle parameters θ1, and calculating the initial target's position coordinates O1(x1, y1) based on the obtained angle parameters, where the formulas for calculating the horizontal and vertical coordinates are: Where φ is the angle between the direction of the millimeter-wave radar array and the horizontal direction, and R is the distance from the target to the radar; By combining the reflection patterns during electromagnetic wave propagation and the distance L from the radar to the reflecting surface, the position coordinates of the other three multipath targets can be calculated. Finally, a set of initial targets are arranged in ascending order according to their distances to the radar. Then, for the first initial target, the position coordinates of its corresponding three multipath targets and the distance errors with other initial targets are calculated. If the distance error is less than 1 meter, the initial target is considered a real target, the coordinate values ​​are retained, and the remaining initial targets that match its corresponding multipath targets are deleted. The above process is repeated for the remaining initial targets to identify real targets and delete the corresponding false multipath targets until all real targets are identified.

5. A method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway according to claim 4, characterized in that, The Minimum Variance Distortionless Response (MVDR) algorithm is an adaptive beamforming algorithm based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion. It can measure the angle parameters of targets at different angles at the same distance without requiring additional prior information.

6. The method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway according to claim 5, characterized in that, The propagation paths of the other three multipath targets are as follows: radar → beacon → reflector → radar, radar → reflector → beacon → radar, and radar → reflector → beacon → reflector → radar. The calculation process for the position coordinates corresponding to the multipath target's path "radar → reflector → beacon → reflector → radar" is as follows: Combining the reflection law during electromagnetic wave propagation, the position coordinates O2(x2,y2) of the mirror-reflecting target are calculated using the initial target's position coordinates O1(x1,y1). The formulas for calculating the horizontal and vertical coordinates are as follows: Where L is the distance from the radar to the reflecting surface.

7. A fixed coal mine underground roadway surrounding rock deformation monitoring and alarm method according to claim 6, characterized in that, The calculation process for the position coordinates corresponding to the multipath target paths "radar → reflector → beacon → radar" and "radar → beacon → reflector → radar" is as follows: combining the multipath target O 21 Based on the angle and distance characteristics, using the initial target's position coordinates O1(x1,y1) and the mirror reflection target's position coordinates O2(x2,y2), calculate O 21 Distance R to radar 21 : Then combine multipath target O 12 The angle and distance characteristics, and its distance R from the radar. 12 With R 21 If they are the same, then the target O can be calculated. 12 O 21 azimuth angle θ 12 θ 21 The calculation formula is: Among them, the angle θ 12 = θ2, θ 12 = θ2; Then calculate O respectively. 12 O 21 Position coordinates (x) 12 ,y 12 ), (x 21 ,y 21 The calculation formula is: The formula for calculating the distance error is: Where, x i y i These are the horizontal and vertical coordinates of the three multipath targets.

8. A method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway according to claim 7, characterized in that, The threshold constraints in step two are the distance change threshold and the deformation rate change threshold. These thresholds are set by analyzing the maximum distance change and the fastest deformation rate change in historical detection data, and adjusted according to specific environmental factors. The historical detection data refers to the distance change and deformation rate change of radar data parameters measured within one cycle relative to the radar data parameters measured in the previous cycle. The mathematical expressions for the distance change L and deformation rate V at time T within the time interval Δt are as follows:

9. A method for monitoring and alarming deformation of surrounding rock in a fixed coal mine underground roadway according to claim 8, characterized in that, The specific process of density clustering in step three is as follows: Set the neighborhood radius R and the minimum number of pixels (MinPoints) in the neighborhood. Traverse all pixels in the radar image and take any pixel that exceeds the threshold condition as the core point. Start from the initial core point and spread outward to the density-reachable area. If there are at least MinPoints deformed pixels within the neighborhood radius R, then all deformed pixels in the neighborhood are considered to belong to the same cluster. Repeat the above operation until all deformed pixels that meet the threshold condition and are directly reachable from the core point density are included. Finally, a DBSCAN cluster is formed that is reachable from all core points density and contains the set of deformed pixels in each neighborhood. The number of deformed pixels in the neighborhood of each core point within the cluster is no less than MinPoints; The density can be reached if the density from core point 1 to core point 2 is directly accessible, and the density from core point 2 to core point 3 is directly accessible, then the density from core point 1 to core point 3 is accessible; the density can be reached if all deformed pixels with a neighborhood radius R centered on the core point are directly accessible to the density of the core point.

10. A fixed coal mine underground roadway surrounding rock deformation monitoring and alarm method according to claim 9, characterized in that, In step three, when calculating the area of ​​the deformed region based on the sum of the pixel areas, since a single pixel in the actual deformed region is not a regular rectangle but rather a fan-shaped ring, and the further the target is from the radar, the larger the fan-shaped ring of a single pixel becomes, the actual deformed area can be obtained by calculating the sum of the areas of the fan-shaped rings of a single pixel. The mathematical expression is: Where α is the azimuth resolution, β is the range resolution, r is the radar near range, and d is the range sampling position; The risk threshold mentioned in step four is 10% of the maximum change in deformation area over N consecutive working cycles in the historical detection data.

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