Karst tunnel surrounding rock disease monitoring equipment and method

Abstract

The application provides a karst tunnel surrounding rock disease monitoring device and method, and relates to the technical field of geological survey, and comprises a rod-shaped unmanned aerial vehicle, a tracked unmanned vehicle and a control system; wherein the rod-shaped unmanned aerial vehicle comprises an on-board 3D laser scanning sensor and a spiral fan motor connected through an elastic telescopic probe rod; in the case that the spiral fan motor is not started, the extension line of the elastic telescopic probe rod points to a first direction; in the case that the spiral fan motor is started, the extension line of the elastic telescopic probe rod points to a second direction; the first direction and the second direction are perpendicular; the tracked unmanned vehicle comprises a probe rod fixing device, a limiting column, an on-board 3D laser scanning sensor and a track; the control system is configured to control the activities of the rod-shaped unmanned aerial vehicle and the tracked unmanned vehicle. The application combines the three-dimensional laser scanning technology with devices such as unmanned vehicles and unmanned aerial vehicles, and can provide more comprehensive and flexible data acquisition capabilities in the monitoring process.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, and in particular to a monitoring device and method for the surrounding rock defects in karst tunnels. Background Technology

[0002] 3D laser scanning technology is a measurement technique that uses a laser beam to rapidly scan a target surface and acquire high-precision 3D spatial data. It involves a laser scanner emitting a laser beam and receiving reflected signals to calculate point cloud data of the target surface, thereby obtaining the 3D coordinate information of the object's surface. It features high precision, full coverage, and rapid data acquisition, and is widely used in fields such as construction, geology, and tunnel inspection. However, the construction and operation of karst tunnels face many complex geological environmental problems. Karst tunnel surrounding rock defects typically include tunnel lining deformation, water leakage, cracks, and karst caves. Existing technologies also suffer from poor adaptability to special working environments, low automation of equipment operation, and the inability to monitor dynamic changes in real time. Summary of the Invention

[0003] The purpose of this invention is to address the problems of low automation and poor adaptability in current karst tunnel monitoring equipment. This invention provides a monitoring device and method for karst tunnel surrounding rock defects.

[0004] The technical solution of this application embodiment is implemented as follows:

[0005] The first aspect of this application provides a monitoring device for surrounding rock defects in karst tunnels, comprising: a pole-shaped unmanned aerial vehicle (UAV), a tracked unmanned vehicle, and a control system; wherein...

[0006] The pole-shaped UAV includes an onboard 3D laser scanning sensor and a spiral fan motor connected by a telescopic elastic detection pole; when the spiral fan motor is not activated, the extension line of the telescopic elastic detection pole points in a first direction; when the spiral fan motor is activated, the extension line of the telescopic elastic detection pole points in a second direction; the first direction and the second direction are perpendicular.

[0007] The tracked unmanned vehicle includes a probe fixing device, a limiting post, an on-board 3D laser scanning sensor, and tracks; the probe fixing device is used to fix the telescopic elastic probe, and the limiting post is used to cooperate with the limiting groove on the rod-shaped unmanned vehicle;

[0008] The control system is configured to control the activities of the pole-shaped drone and the tracked unmanned vehicle.

[0009] Optionally, the rod-shaped UAV also includes a spiral fan blade and a spiral fan blade protective shell; when the spiral fan blade motor is activated, the spiral fan blade provides airflow to adjust the direction of the telescopic elastic detection rod.

[0010] Optionally, the conical sides of the limiting post and the limiting groove are provided with buffer pads.

[0011] Optionally, the limiting post and the limiting groove are provided with hardware interfaces to complete data transmission and power supply between the pole-shaped UAV and the tracked unmanned vehicle.

[0012] A second aspect of this application provides a method for monitoring rock defects in karst tunnels, applied to the monitoring equipment described in the first aspect, comprising:

[0013] Point cloud data of the surrounding rock of karst tunnels were acquired using a pole-mounted UAV and a tracked unmanned vehicle, respectively; the point cloud data of the surrounding rock of karst tunnels includes spatial location information and reflection intensity information.

[0014] Feature extraction is performed on the spatial location information and reflection intensity information to obtain the characteristics of surrounding rock defects in karst tunnels;

[0015] The characteristics of the surrounding rock defects in karst tunnels are integrated and classified to determine the types of defects.

[0016] Optionally, the acquisition of point cloud data of surrounding rock in karst tunnels using pole-mounted UAVs and tracked unmanned vehicles respectively includes:

[0017] When probing the surrounding rock at the top of the tunnel, the spiral fan motor is kept off so that the extension line of the telescopic elastic probe points in the first direction, thereby acquiring point cloud data of the karst tunnel surrounding rock at the top of the tunnel.

[0018] Optionally, the acquisition of point cloud data of surrounding rock in karst tunnels using pole-mounted UAVs and tracked unmanned vehicles respectively includes:

[0019] When probing the surrounding rock on the side of the tunnel, the spiral fan motor is started so that the extension line of the telescopic elastic probe points in the second direction to obtain point cloud data of the karst tunnel surrounding rock on the side of the tunnel.

[0020] Optionally, the step of extracting features from the spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects includes:

[0021] Based on the spatial location information and reflection intensity information, wavelet packet transform decomposition is used to divide the karst tunnel surrounding rock point cloud data into multiple different levels to obtain the karst tunnel surrounding rock disease characteristics, which include point features, line features, surface features and volume features.

[0022] A third aspect of this application provides a monitoring system for surrounding rock defects in karst tunnels, comprising: a data acquisition module, a feature extraction module, and a fusion classification module; wherein...

[0023] The data acquisition module is configured to acquire point cloud data of the surrounding rock of the karst tunnel using a pole-shaped UAV and a tracked unmanned vehicle, respectively; the point cloud data of the surrounding rock of the karst tunnel includes spatial location information and reflection intensity information.

[0024] The feature extraction module is configured to extract features from the spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects.

[0025] The fusion classification module is configured to fuse and classify the characteristics of the surrounding rock defects in the karst tunnel to determine the defect type.

[0026] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the second aspect.

[0027] Compared with the prior art, the beneficial effects of the technical solution provided in this application are:

[0028] This invention provides a monitoring device and method for karst tunnel surrounding rock defects. It combines three-dimensional laser scanning technology with unmanned vehicles (UAVs) and drones, enabling three-dimensional structural detection of defects such as karst caves on the sides and top of karst tunnels. When the drone is mounted on the UAV, the two communicate via a hardware interface for energy transfer and wired communication. When the drone is detached from the UAV, they communicate wirelessly in real time. During monitoring, the device balances the stability and accuracy of the UAV's acquisition of position, attitude, and trajectory information with the flexibility of the drone in detecting the tunnel's three-dimensional structure, providing a more comprehensive and flexible data acquisition capability. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the structure of a monitoring device for surrounding rock defects in karst tunnels, provided in an embodiment of this application.

[0030] Figure 2 This is a schematic diagram of the structure of the pole-shaped UAV provided in the embodiments of this application;

[0031] Figure 3 This is a schematic diagram of the structure of the tracked unmanned vehicle provided in the embodiments of this application;

[0032] Figure 4 This is a schematic diagram of the structure of the connection platform provided in an embodiment of this application;

[0033] Figure 5 This is a schematic diagram of the separation of the drone and the unmanned vehicle provided in an embodiment of this application;

[0034] Figure 6A flowchart illustrating a method for monitoring surrounding rock defects in karst tunnels, provided in an embodiment of this application;

[0035] Figure 7 This is a schematic diagram of the structure of a karst tunnel surrounding rock disease monitoring system provided in an embodiment of this application;

[0036] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0037] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0038] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0039] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0040] The accompanying drawings show some block diagrams and / or flowcharts. It should be understood that some blocks or combinations thereof in the block diagrams and / or flowcharts can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when executed by the processor, these instructions can create means for implementing the functions / operations described in these block diagrams and / or flowcharts.

[0041] In some embodiments, please refer to Figure 1 , Figure 1 This is a schematic diagram of the structure of a karst tunnel surrounding rock defect monitoring device provided in an embodiment of this application; the karst tunnel surrounding rock defect monitoring device provided in this embodiment includes: a pole-shaped unmanned aerial vehicle 100, a tracked unmanned vehicle 200, and a control system 300; wherein...

[0042] The pole-shaped unmanned aerial vehicle 100 includes an airborne 3D laser scanning sensor and a helical fan motor connected by a telescopic elastic detection pole; when the helical fan motor is not activated, the extension line of the telescopic elastic detection pole points in a first direction; when the helical fan motor is activated, the extension line of the telescopic elastic detection pole points in a second direction; the first direction and the second direction are perpendicular.

[0043] In some embodiments, the pole-shaped drone 100 further includes a helical fan blade and a protective shell for the helical fan blade; when the helical fan blade motor is activated, the helical fan blade provides airflow to adjust the direction of the telescopic elastic probe.

[0044] For example, the specific structure of the pole-shaped drone 100 is as follows: Figure 2 As shown, component 101 is an airborne 3D laser scanning sensor, component 102 is a telescopic elastic detection rod, component 103 is a spiral fan blade protective shell, component 104 is a spiral fan blade, and component 105 is a spiral fan blade motor. The module comprises an airborne 3D laser scanning sensor, a telescopic elastic probe, and a spiral fan motor, providing pitch freedom. The front section of the probe is a telescopic elastic rod, allowing it to extend and retract through curved karst cave entrances. A transparent protective shell surrounds the airborne 3D laser scanning sensor connected to the front of the telescopic elastic probe. The rear section of the telescopic elastic probe is a rigid rod, supporting the spiral fan structure connected to its rear end as a counterweight. The telescopic elastic probe can extend into the interior of karst caves and other defects on the sides and top of karst tunnels for three-dimensional structural detection. When detecting the top of the tunnel, the spiral fan motor is not activated, and the entire module hangs naturally with the airborne 3D laser scanning sensor facing upwards and the spiral fan motor facing downwards. When detecting the side of the tunnel, the spiral fan indicated by the spiral fan motor is activated, and the module gradually becomes horizontal, with the airborne 3D laser scanning sensor facing forward and the spiral fan motor facing backwards. It should be noted that the telescopic elastic detection rod 102 can be divided into multiple segments, allowing it to cover detection points at different distances during the detection process, thereby expanding the detection range. Furthermore, because it is elastic, it can detect along curved paths, thus adapting to a wider range of detection scenarios.

[0045] The tracked unmanned vehicle 200 includes a probe fixing device, a limiting post, an onboard 3D laser scanning sensor, tracks, a tracked odometer, and an inertial measurement unit. The probe fixing device is used to fix the telescopic elastic probe, and the limiting post is used to cooperate with the limiting groove on the rod-shaped UAV. It should be noted that the onboard 3D laser scanning sensor can work with the tracked odometer and inertial measurement unit to calculate the position, attitude, and trajectory of the tracked unmanned vehicle.

[0046] In some embodiments, the conical sides of the limiting post and the limiting groove are provided with buffer pads.

[0047] In some embodiments, the limiting post and limiting groove are provided with hardware interfaces to complete data transmission and power supply between the pole-shaped drone and the tracked unmanned vehicle.

[0048] In one example, the specific structure of the tracked unmanned vehicle 200 is as follows: Figure 3 As shown, component 201 is a probe rod fixing device, component 202 is a limit post interface, component 203 is a vehicle-mounted 3D laser scanning sensor, and component 204 is a track.

[0049] The pole-mounted drone 100 and the tracked unmanned vehicle 200 can be connected via a connection platform. Please refer to [link / reference]. Figure 4 , Figure 4 This is a schematic diagram of the connection platform provided in the embodiment of this application; wherein, component 111 is a limiting groove interface, component 112 is a motor bearing, component 113 is an energy data control center, and component 114 is a binocular camera.

[0050] The control system 300 is configured to control the activities of the stick-type unmanned aerial vehicle and the tracked unmanned vehicle. Here, the control system 300 can be an automatic control system.

[0051] In an alternative embodiment, when the pole-shaped drone 100 is mounted on the tracked unmanned vehicle 200, the tracked unmanned vehicle 200 and the pole-shaped drone 100 perform integrated detection. Figure 5 This is a schematic diagram of the separation of the drone and the unmanned vehicle provided in an embodiment of this application, with the control system 300 and... Figure 1 The same applies, so it will not be displayed here. For example... Figure 5 As shown, when the stick-shaped UAV 100 detaches from the tracked UAV 200 and flies, the tracked UAV 200 stops moving, and the two communicate wirelessly. The UAV establishes a spherical reference system with the stick-shaped UAV 100 as the origin of the coordinates and is controlled by the operator to fly within the safe radius of the set reference system. When the stick-shaped UAV 100 flies close to the safe radius, the operator's control is transferred to the automatic control system, which then controls the stick-shaped UAV 100.

[0052] The karst tunnel surrounding rock disease monitoring equipment proposed in this application can extend into the interior of karst tunnel sidewalls and top surface surrounding rock, such as caves, to conduct three-dimensional structural detection and obtain a more comprehensive spatial structure of karst tunnel diseases. When the UAV is mounted on the unmanned vehicle, the two communicate via a hardware interface for energy transfer and wired communication. When the UAV is detached from the unmanned vehicle and flies, the two communicate wirelessly in real time. During the monitoring process, it can provide more comprehensive and flexible data acquisition capabilities.

[0053] In some embodiments, please refer to Figure 6 , Figure 6 This is a flowchart illustrating the method for monitoring surrounding rock defects in karst tunnels provided in this application embodiment; the method for monitoring surrounding rock defects in karst tunnels provided in this application embodiment, applied to the monitoring equipment of the first aspect, includes:

[0054] The S610 uses a pole-mounted drone and a tracked unmanned vehicle to acquire point cloud data of the surrounding rock of karst tunnels; the point cloud data of the surrounding rock of karst tunnels includes spatial location information and reflection intensity information.

[0055] S620 extracts features from spatial location information and reflection intensity information to obtain the characteristics of surrounding rock defects in karst tunnels.

[0056] S630 integrates and classifies the characteristics of surrounding rock defects in karst tunnels to determine the types of defects.

[0057] In some embodiments, S610, point cloud data of the surrounding rock of karst tunnels are acquired using a pole-mounted drone and a tracked unmanned vehicle, respectively, including:

[0058] When probing the surrounding rock at the top of the tunnel, the spiral fan motor is kept off so that the extension line of the telescopic elastic probe points in the first direction, thereby acquiring point cloud data of the karst tunnel surrounding rock at the top of the tunnel.

[0059] In some embodiments, S610, point cloud data of the surrounding rock of karst tunnels are acquired using a pole-mounted drone and a tracked unmanned vehicle, respectively, including:

[0060] When probing the surrounding rock on the side of the tunnel, the spiral fan motor is started so that the extension line of the telescopic elastic probe points in the second direction to obtain point cloud data of the karst tunnel surrounding rock on the side of the tunnel.

[0061] In some embodiments, S620, feature extraction is performed on the spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects, including:

[0062] Based on spatial location information and reflection intensity information, wavelet packet transform decomposition is used to divide the karst tunnel surrounding rock point cloud data into multiple different levels to obtain the karst tunnel surrounding rock disease characteristics, which include point features, line features, surface features and volume features.

[0063] In this embodiment, data acquired by the pole-mounted UAV and the tracked unmanned vehicle are registered and stored in the pole-mounted UAV and the tracked unmanned vehicle respectively. The point cloud data score is calculated using a point cloud quality evaluation method, and the unmanned vehicle is trained using reinforcement learning algorithms and operator assistance to achieve automatic driving. After measurement, the data is uploaded to the backend command and dispatch system. Based on the spatial location and reflection intensity information of the point cloud, wavelet packet transform decomposition is used to divide the karst tunnel surrounding rock point cloud data into different levels. Defect point clouds are extracted and clustered, and the defect point clouds are fitted into spatial elements of points, lines, surfaces, and volumes. R-tree spatial indexing is used to organize and store different types of surrounding rock defects and their characteristics. Point clouds are acquired using manned equipment, i.e., using stationary and handheld 3D laser scanning equipment to periodically acquire more accurate overall point cloud data of the karst tunnel surrounding rock as a supplement. This data is uploaded to the backend command and dispatch system and registered with the point cloud acquired by the unmanned equipment to achieve multi-source heterogeneous point cloud data fusion. In the background system, neural networks and expert systems are combined to classify defects under different processes, and a bidirectional reference is established between spatial data and attribute data of different types of karst tunnel surrounding rock defects based on the spatial database management system. For example, the specific steps may include: 1) using 3D laser scanning unmanned equipment and manned equipment in collaboration to obtain karst tunnel surrounding rock point cloud data; 2) extracting karst tunnel surrounding rock defects based on the spatial location information and reflection intensity information of the point cloud data in step (1); 3) fitting the defect point cloud in step (2) into spatial entities of shapes such as points, lines, surfaces, and volumes, and integrating their corresponding attribute information to classify various types of defects; 4) importing the karst tunnel surrounding rock defects classified from different tunnel processes in step (3) into the spatial database management system.

[0064] In some embodiments, this application provides a karst tunnel surrounding rock disease monitoring system 700, including: a data acquisition module 710, a feature extraction module 720, and a fusion classification module 730; wherein...

[0065] The data acquisition module 710 is configured to acquire point cloud data of the surrounding rock of karst tunnels using a pole-shaped UAV and a tracked unmanned vehicle, respectively; the point cloud data of the surrounding rock of karst tunnels includes spatial location information and reflection intensity information.

[0066] The feature extraction module 720 is configured to extract features from spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects.

[0067] The fusion classification module 730 is configured to fuse and classify the characteristics of karst tunnel surrounding rock defects to determine the defect type.

[0068] In some embodiments, the data acquisition module 710 is specifically configured as follows:

[0069] When probing the surrounding rock at the top of the tunnel, the spiral fan motor is kept off so that the extension line of the telescopic elastic probe points in the first direction, thereby acquiring point cloud data of the karst tunnel surrounding rock at the top of the tunnel.

[0070] In some embodiments, the data acquisition module 710 is specifically configured as follows:

[0071] When probing the surrounding rock on the side of the tunnel, the spiral fan motor is started to make the extension line of the telescopic elastic probe point in the second direction to obtain point cloud data of the karst tunnel surrounding rock on the side of the tunnel.

[0072] In some embodiments, the feature extraction module 720 is specifically configured as follows:

[0073] Based on spatial location information and reflection intensity information, wavelet packet transform decomposition is used to divide the karst tunnel surrounding rock point cloud data into multiple different levels to obtain the karst tunnel surrounding rock disease characteristics, which include point features, line features, surface features and volume features.

[0074] The detection mechanism control system provided in this application embodiment can realize the various processes in the embodiments corresponding to the karst tunnel surrounding rock disease monitoring equipment. To avoid repetition, it will not be described again here.

[0075] It should be noted that the detection mechanism control system provided in this application embodiment and the karst tunnel surrounding rock disease monitoring equipment provided in this application embodiment are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned karst tunnel surrounding rock disease monitoring equipment, and the repeated parts will not be described again.

[0076] In some embodiments, please refer to Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 800 provided in this embodiment includes a processor 810 and a memory 820; the memory 820 stores a computer program, wherein the computer program, when executed by the processor, implements the aforementioned karst tunnel surrounding rock disease monitoring device.

[0077] Specifically, processor 810 may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. Processor 810 may also include onboard memory for caching purposes. Processor 810 may be a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this application.

[0078] Memory 820 may be any medium capable of containing, storing, transmitting, propagating, or transmitting instructions. For example, memory 820 may include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, instruments, or propagation media. Specific examples of memory 820 include: magnetic storage devices such as magnetic tape or hard disk drives (HDDs); optical storage devices such as optical discs (CD-ROMs); and may also be random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0079] This application also provides a computer-readable medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned karst tunnel surrounding rock defect monitoring device. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into that device / apparatus / system. The aforementioned computer-readable medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0080] According to embodiments of this application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, optical fiber, radio frequency signals, etc., or any suitable combination thereof.

[0081] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Therefore, the scope of this application should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

1. A monitoring device for surrounding rock defects in karst tunnels, characterized in that, include: Pole-shaped drones, tracked unmanned vehicles, and control systems; among them, The pole-shaped UAV includes an onboard 3D laser scanning sensor, five spiral blades, and five corresponding spiral blade motors connected via a telescopic elastic detection rod. Four spiral blades and their corresponding motors are positioned around the rear end of the telescopic elastic detection rod to control the UAV's vertical, horizontal, and vertical movement. The remaining spiral blade and its corresponding motor are positioned at the end of the telescopic elastic detection rod. When the spiral blade motor at the end of the telescopic elastic detection rod is not activated, the extension line of the telescopic elastic detection rod points in a first direction. When the spiral fan motor at the end of the probe is activated, the extension line of the telescopic elastic probe points to the second direction; the first direction and the second direction are perpendicular; when the spiral fan motor at the end of the telescopic elastic probe is activated, its corresponding spiral fan blades provide airflow to adjust the direction of the telescopic elastic probe; wherein, when it is to detect the surrounding rock on the top surface of the tunnel, the spiral fan motor at the end of the telescopic elastic probe is not activated, and the entire module hangs down naturally; when it is to detect the surrounding rock on the side of the tunnel, the spiral fan motor at the end of the telescopic elastic probe is activated, and the module gradually becomes horizontal; The tracked unmanned vehicle includes a probe fixing device, a limiting post, an on-board 3D laser scanning sensor, and tracks; the probe fixing device is used to fix the telescopic elastic probe, and the limiting post is used to cooperate with the limiting groove on the rod-shaped unmanned vehicle; The control system is configured to control the activities of the pole-shaped drone and the tracked unmanned vehicle.

2. The karst tunnel surrounding rock disease monitoring equipment according to claim 1, characterized in that, The conical sides of the limiting post and the limiting groove are provided with buffer pads.

3. The karst tunnel surrounding rock disease monitoring equipment according to claim 1, characterized in that, The limiting post and the limiting groove are provided with hardware interfaces to complete data transmission and power supply between the pole-shaped UAV and the tracked unmanned vehicle.

4. A method for monitoring surrounding rock defects in karst tunnels, applied to the monitoring equipment described in claims 1-3, characterized in that, include: Point cloud data of the surrounding rock of karst tunnels were acquired using pole-mounted drones and tracked unmanned vehicles, respectively. The karst tunnel surrounding rock point cloud data includes spatial location information and reflection intensity information; Feature extraction is performed on the spatial location information and reflection intensity information to obtain the characteristics of surrounding rock defects in karst tunnels; The characteristics of the surrounding rock defects in karst tunnels are integrated and classified to determine the types of defects.

5. The karst tunnel surrounding rock disease monitoring equipment according to claim 4, characterized in that, The acquisition of point cloud data of surrounding rock in karst tunnels using pole-mounted drones and tracked unmanned vehicles includes: When probing the surrounding rock at the top of the tunnel, the spiral fan motor is kept off so that the extension line of the telescopic elastic probe points in the first direction, thereby acquiring point cloud data of the karst tunnel surrounding rock at the top of the tunnel.

6. The karst tunnel surrounding rock disease monitoring equipment according to claim 4, characterized in that, The acquisition of point cloud data of surrounding rock in karst tunnels using pole-mounted drones and tracked unmanned vehicles includes: When probing the surrounding rock on the side of the tunnel, the spiral fan motor is started so that the extension line of the telescopic elastic probe points in the second direction to obtain point cloud data of the karst tunnel surrounding rock on the side of the tunnel.

7. The karst tunnel surrounding rock disease monitoring equipment according to claim 4, characterized in that, The process of extracting features from the spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects includes: Based on the spatial location information and reflection intensity information, wavelet packet transform decomposition is used to divide the karst tunnel surrounding rock point cloud data into multiple different levels to obtain the karst tunnel surrounding rock disease characteristics, which include point features, line features, surface features and volume features.

8. A karst tunnel surrounding rock disease monitoring system for implementing the karst tunnel surrounding rock disease monitoring method of claim 4, characterized in that, include: The module consists of a data acquisition module, a feature extraction module, and a fusion classification module; among which, The data acquisition module is configured to acquire point cloud data of the surrounding rock of the karst tunnel using a pole-shaped UAV and a tracked unmanned vehicle, respectively; the point cloud data of the surrounding rock of the karst tunnel includes spatial location information and reflection intensity information. The feature extraction module is configured to extract features from the spatial location information and reflection intensity information to obtain the characteristics of karst tunnel surrounding rock defects. The fusion classification module is configured to fuse and classify the characteristics of the surrounding rock defects in the karst tunnel to determine the defect type.

9. A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method of claims 4-7.

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