Karst tunnel surrounding rock disease monitoring equipment and method

Abstract

The invention provides karst tunnel surrounding rock disease monitoring equipment and a karst tunnel surrounding rock disease monitoring method, and relates to the technical field of geological investigation, the karst tunnel surrounding rock disease monitoring equipment comprises a rod-shaped unmanned aerial vehicle, a crawler-type unmanned vehicle and a control system; the rod-shaped unmanned aerial vehicle comprises an airborne 3D laser scanning sensor and a spiral fan blade motor which are connected through a telescopic elastic detection rod. Under the condition that the spiral fan blade motor is not started, the extension line of the telescopic elastic detection rod points to the first direction; under the condition that the spiral fan blade motor is started, the extension line of the telescopic elastic detection rod points to a second direction; the first direction is perpendicular to the second direction; the crawler-type unmanned vehicle comprises a detection rod fixing device, a limiting column, a vehicle-mounted 3D laser scanning sensor and a crawler, and the control system is configured to control the movement of the rod-shaped unmanned aerial vehicle and the crawler-type unmanned vehicle. According to the invention, a three-dimensional laser scanning technology is combined with equipment such as an unmanned vehicle and an unmanned aerial vehicle, so that a more comprehensive and flexible data acquisition capability can be provided in a monitoring process.

Description

Technical Field

[0001] The invention relates to the technical field of geological exploration, and in particular to a karst tunnel surrounding rock disease monitoring device and method. Background Art

[0002] 3D laser scanning technology is a measurement technology that uses a laser beam to quickly scan the target surface and obtain high-precision 3D spatial data. It uses a laser scanner to emit a laser beam and receive the reflected signal to calculate the point cloud data of the target surface, thereby obtaining the 3D coordinate information of the object surface. It has the characteristics of high precision, full coverage, and rapid acquisition, and is widely used in the fields of construction, geology, and tunnel detection. However, the construction and operation of karst tunnels face many complex geological environmental problems. Karst tunnel surrounding rock diseases usually include tunnel lining deformation, water leakage, cracks, and caves. The existing technology also has problems such as poor adaptability in special working environments, low degree of equipment operation automation, and inability to monitor dynamic changes in real time. Summary of the invention

[0003] The purpose of the present invention is to solve the problems of low automation and poor adaptability of current karst tunnel monitoring equipment, and to provide a karst tunnel surrounding rock disease monitoring device and method.

[0004] The technical solution of the embodiment of the present application is implemented as follows: The first aspect of the embodiment of the present application provides a karst tunnel surrounding rock disease monitoring device, including: a pole-shaped unmanned aerial vehicle, a crawler-type unmanned vehicle and a control system; wherein, The rod-shaped drone comprises an airborne 3D laser scanning sensor and a spiral blade motor connected by a telescopic elastic detection rod; when the spiral blade motor is not started, the extension line of the telescopic elastic detection rod points to a first direction; when the spiral blade motor is started, the extension line of the telescopic elastic detection rod points to a second direction; the first direction is perpendicular to the second direction; The crawler-type unmanned vehicle comprises a detection rod fixing device, a limiting column, a vehicle-mounted 3D laser scanning sensor and a crawler; the detection rod fixing device is used to fix the telescopic elastic detection rod, and the limiting column 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 UAV and the tracked unmanned vehicle.

[0005] Optionally, the rod-shaped drone further includes a spiral fan blade and a spiral fan blade protective shell; when the spiral fan blade motor is started, the spiral fan blade provides airflow to adjust the direction of the telescopic elastic detection rod.

[0006] Optionally, buffer pads are provided on the conical sides of the limiting column and the limiting groove.

[0007] Optionally, a hardware interface is provided on the limiting column and the limiting groove to complete data transmission and power supply between the pole-shaped UAV and the tracked unmanned vehicle.

[0008] A second aspect of the embodiment of the present application provides a method for monitoring surrounding rock diseases in a karst tunnel, which is applied to the monitoring device described in the first aspect, comprising: The point cloud data of the surrounding rock of the karst tunnel are obtained by using a pole-shaped UAV and a crawler-type unmanned vehicle respectively; the point cloud data of the surrounding rock of the karst tunnel includes spatial position information and reflection intensity information; Extracting features from the spatial position information and the reflection intensity information to obtain the features of the surrounding rock damage of the karst tunnel; The characteristics of the surrounding rock diseases of the karst tunnel are integrated and classified to determine the disease type.

[0009] Optionally, the method of respectively using a pole-shaped UAV and a tracked unmanned vehicle to obtain point cloud data of the surrounding rock of the karst tunnel includes: When detecting the surrounding rock on the top surface of the tunnel, the spiral fan motor is controlled not to start, so that the extension line of the telescopic elastic detection rod points to the first direction, and the point cloud data of the karst tunnel surrounding rock on the top surface of the tunnel is obtained.

[0010] Optionally, the method of respectively using a pole-shaped UAV and a tracked unmanned vehicle to obtain point cloud data of the surrounding rock of the karst tunnel includes: When detecting the surrounding rock on the side of the tunnel, the spiral fan motor is controlled to start so that the extension line of the telescopic elastic detection rod points to the second direction, and the point cloud data of the karst tunnel surrounding rock on the side of the tunnel is obtained.

[0011] Optionally, the feature extraction of the spatial position information and the reflection intensity information to obtain the surrounding rock disease characteristics of the karst tunnel includes: Based on the spatial position information and the reflection intensity information, the karst tunnel surrounding rock point cloud data is divided into multiple different levels by wavelet packet transform decomposition to obtain the karst tunnel surrounding rock disease characteristics, which include point characteristics, line characteristics, surface characteristics and volume characteristics.

[0012] The third aspect of the embodiment of the present application provides a karst tunnel surrounding rock disease monitoring system, including: a data acquisition module, a feature extraction module and a fusion classification module; wherein, The data acquisition module is configured to respectively use a pole-shaped UAV and a crawler-type unmanned vehicle to acquire point cloud data of the surrounding rock of the karst tunnel; the point cloud data of the surrounding rock of the karst tunnel includes spatial position information and reflection intensity information; The feature extraction module is configured to extract features from the spatial position information and the reflection intensity information to obtain the features of the surrounding rock damage of the karst tunnel; The fusion classification module is configured to fuse and classify the karst tunnel surrounding rock disease characteristics to determine the disease type.

[0013] A fourth aspect of an embodiment of the present 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.

[0014] Compared with the prior art, the technical solution provided by this application has the following beneficial effects: The present invention provides a karst tunnel surrounding rock disease monitoring device and method, which combines three-dimensional laser scanning technology with unmanned vehicles, unmanned aerial vehicles and other equipment, and can be used to extend into the side and top surrounding rocks of karst tunnels to perform three-dimensional structure detection on the inside of diseases such as karst caves, and when the unmanned aerial vehicle is mounted on the unmanned vehicle, the two perform energy transmission and wired communication through a hardware interface, and when the unmanned aerial vehicle is separated from the unmanned vehicle for flight, the two perform wireless real-time communication. During the monitoring process, the stability and accuracy of the unmanned vehicle in acquiring position, posture and driving trajectory information and the flexibility of the unmanned aerial vehicle in detecting the three-dimensional structure of the tunnel are taken into account, and a more comprehensive and flexible data collection capability can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of the structure of a karst tunnel surrounding rock disease monitoring device provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a pole-shaped drone provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a tracked unmanned vehicle provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of the connection platform provided in the embodiment of the present application; Figure 5 This is a schematic diagram of the structure of the separation of the unmanned aerial vehicle and the unmanned vehicle provided in the embodiment of the present application; Figure 6 A schematic diagram of a flow chart of a method for monitoring surrounding rock diseases in a karst tunnel provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of a karst tunnel surrounding rock disease monitoring system provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] Below, embodiments of the present application will 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 the present application. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present application. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present application.

[0017] The terms used herein are only for describing specific embodiments and are not intended to limit the present application. The terms "include", "comprising", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0018] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0019] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some blocks or combinations thereof in the block diagrams and / or flow charts may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that these instructions, when executed by the processor, may create a device for implementing the functions / operations described in these block diagrams and / or flow charts.

[0020] In some embodiments, see Figure 1 , Figure 1 A schematic diagram of the structure of a karst tunnel surrounding rock disease monitoring device provided in an embodiment of the present application; A karst tunnel surrounding rock disease monitoring device provided in an embodiment of the present application comprises: a pole-shaped UAV 100, a crawler-type unmanned vehicle 200 and a control system 300; wherein, The pole-shaped drone 100 includes an airborne 3D laser scanning sensor and a propeller blade motor connected by a telescopic elastic detection rod; when the propeller blade motor is not started, the extension line of the telescopic elastic detection rod points to a first direction; when the propeller blade motor is started, the extension line of the telescopic elastic detection rod points to a second direction; the first direction is perpendicular to the second direction.

[0021] In some embodiments, the pole-shaped drone 100 further includes a spiral blade and a spiral blade protective shell; when the spiral blade motor is started, the spiral blade provides airflow to adjust the direction of the telescopic elastic detection rod.

[0022] 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 airborne 3D laser scanning sensor, telescopic elastic detection rod and spiral fan motor and other structures constitute a module with pitch freedom. The front section of the detection rod is a telescopic elastic rod to ensure that it can be extended from the curved cave entrance, and the airborne 3D laser scanning sensor connected to the front end of the telescopic elastic detection rod is surrounded by a transparent protective shell, and the rear section of the telescopic elastic detection rod is a rigid rod, which supports the overall spiral fan structure connected to the rear end of the telescopic elastic detection rod as a counterweight. The telescopic elastic detection rod can be extended into the karst caves and other defects on the side and top surrounding rocks of the karst tunnel for three-dimensional structure detection. When the surrounding rock on the top of the tunnel is to be detected, the spiral fan motor is not started, the entire module droops naturally, the airborne 3D laser scanning sensor faces upward, and the spiral fan motor faces downward. When the surrounding rock on the side of the tunnel is to be detected, the spiral fan pointed to by the spiral fan motor starts, and the module gradually becomes horizontal, with the airborne 3D laser scanning sensor facing forward and the spiral fan motor facing backward. It should be noted that the telescopic elastic detection rod 102 can be divided into multiple sections, so that it can take into account detection points at different distances during the detection process, thereby expanding the detection range. And because it is elastic, it can be used for detection along a curved path, so it can adapt to more detection scenarios.

[0023] The crawler-type unmanned vehicle 200 includes a probe rod fixing device, a limit column, a vehicle-mounted 3D laser scanning sensor, a crawler, a crawler-type odometer and an inertial measurement unit; the probe rod fixing device is used to fix the telescopic elastic probe rod, and the limit column is used to cooperate with the limit groove on the rod-shaped unmanned aerial vehicle. It should be noted that the vehicle-mounted 3D laser scanning sensor can cooperate with the crawler-type odometer and the inertial measurement unit to calculate the position, posture and driving trajectory of the crawler-type unmanned vehicle.

[0024] In some embodiments, buffer pads are provided on the conical sides of the limiting pillar and the limiting groove.

[0025] In some embodiments, a hardware interface is provided on the limiting column and the limiting groove to complete data transmission and power supply between the pole-shaped UAV and the tracked unmanned vehicle.

[0026] In one example, the specific structure of the crawler unmanned vehicle 200 is as follows: Figure 3 As shown, component 201 is a detection rod fixing device, component 202 is a limit column interface, component 203 is a vehicle-mounted 3D laser scanning sensor, and component 204 is a crawler track.

[0027] The pole-shaped UAV 100 and the crawler-type unmanned vehicle 200 can be connected via a connection platform. Figure 4 , Figure 4 A schematic diagram of the structure of the connection platform provided for an embodiment of the present application; wherein component 111 is a limit groove interface, component 112 is a motor bearing, component 113 is an energy data control center, and component 114 is a binocular camera.

[0028] The control system 300 is configured to control the activities of the rod-shaped UAV and the crawler-type unmanned vehicle. Here, the control system 300 may be an automatic control system.

[0029] In an optional embodiment, when the pole-shaped UAV 100 is mounted on the tracked unmanned vehicle 200, the tracked unmanned vehicle 200 and the pole-shaped UAV 100 perform integrated detection. Figure 5 3 is a schematic diagram of the structure of the separation of the unmanned aerial vehicle and the unmanned vehicle provided in the embodiment of the present application, the control system 300 and Figure 1 Same, no longer shown here. Figure 5 As shown, when the pole-shaped UAV 100 is separated from the tracked unmanned vehicle 200, the tracked unmanned vehicle 200 stops driving, and the two communicate wirelessly. The UAV establishes a spherical reference system with the pole-shaped UAV 100 as the coordinate origin, and is controlled by the operator to fly within the safety radius of the set reference system. When the pole-shaped UAV 100 flies close to the safety radius, the operator's control is transferred to the automatic control system, and the automatic control system controls the pole-shaped UAV 100.

[0030] The karst tunnel surrounding rock disease monitoring equipment proposed in the embodiment of the present application can extend into the karst tunnel side and top surrounding rock diseases such as karst caves to perform three-dimensional structural detection, and obtain a more comprehensive spatial structure of the karst tunnel disease. When the drone is mounted on the unmanned vehicle, the two carry out energy transmission and wired communication through the hardware interface, and when the drone is separated from the unmanned vehicle, the two carry out wireless real-time communication, which can provide more comprehensive and flexible data collection capabilities during the monitoring process.

[0031] In some embodiments, see Figure 6 , Figure 6 A flow chart of a method for monitoring surrounding rock defects in a karst tunnel provided in an embodiment of the present application; a method for monitoring surrounding rock defects in a karst tunnel provided in an embodiment of the present application, applied to the monitoring device of the first aspect, comprising: S610, using a pole-shaped UAV and a tracked unmanned vehicle to obtain point cloud data of the surrounding rock of the karst tunnel; the point cloud data of the surrounding rock of the karst tunnel includes spatial position information and reflection intensity information.

[0032] S620, extracting features from the spatial position information and the reflection intensity information to obtain the surrounding rock disease features of the karst tunnel.

[0033] S630, integrate and classify the characteristics of karst tunnel surrounding rock diseases to determine the disease type.

[0034] In some embodiments, S610, using a pole-shaped UAV and a crawler-type unmanned vehicle to obtain point cloud data of the surrounding rock of a karst tunnel includes: When detecting the surrounding rock on the top surface of the tunnel, the spiral fan motor is controlled not to start, so that the extension line of the telescopic elastic detection rod points to the first direction, and the point cloud data of the karst tunnel surrounding rock on the top surface of the tunnel is obtained.

[0035] In some embodiments, S610, using a pole-shaped UAV and a crawler-type unmanned vehicle to obtain point cloud data of the surrounding rock of a karst tunnel includes: When detecting the surrounding rock on the side of the tunnel, the spiral fan motor is controlled to start so that the extension line of the telescopic elastic detection rod points to the second direction, and the point cloud data of the karst tunnel surrounding rock on the side of the tunnel is obtained.

[0036] In some embodiments, S620, feature extraction is performed on the spatial position information and the reflection intensity information to obtain the surrounding rock disease features of the karst tunnel, including: Based on the spatial position information and the reflection intensity information, the karst tunnel surrounding rock point cloud data is divided into multiple different levels by wavelet packet transform decomposition to obtain the karst tunnel surrounding rock disease characteristics, which include point characteristics, line characteristics, surface characteristics and volume characteristics.

[0037] In this embodiment, the data obtained by the pole-shaped UAV and the crawler-type unmanned vehicle are registered, and the data are stored in the pole-shaped UAV and the crawler-type unmanned vehicle respectively. The scanned point cloud data score is calculated by the point cloud quality evaluation method, and the automatic driving of the unmanned vehicle equipment is realized based on the reinforcement learning algorithm and operator-assisted training. After the measurement is completed, the data is uploaded to the background command and dispatch system. Based on the spatial position and reflection intensity information of the point cloud, the wavelet packet transform is used to decompose the karst tunnel surrounding rock point cloud data into different levels, and the disease point cloud is extracted and clustered, and the disease point cloud is fitted into spatial elements of the shape of points, lines, surfaces, bodies, etc., and the R-tree spatial index is used to organize and store different types of surrounding rock diseases and characteristics. The point cloud is obtained by manned equipment, that is, the three-dimensional laser scanning equipment such as the stand-type and handheld is used to regularly obtain more accurate karst tunnel surrounding rock overall point cloud data as a supplement, and the data is uploaded to the background command and dispatch system, and registered with the point cloud obtained by the unmanned equipment to realize multi-source heterogeneous point cloud data fusion. In the background system, neural networks and expert systems are combined to classify the defects under different processes, and based on the spatial database management system, a two-way reference is established between the spatial data and attribute data of different types of karst tunnel surrounding rock defects. Exemplarily, the following steps may be specifically included: 1) using 3D laser scanning unmanned equipment and manned equipment to collaborate to obtain karst tunnel surrounding rock point cloud data; 2) extracting karst tunnel surrounding rock defects based on the spatial position 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 in the shape of points, lines, surfaces, bodies, etc., 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.

[0038] In some embodiments, the present 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, The data acquisition module 710 is configured to acquire point cloud data of the surrounding rock of the karst tunnel using a pole-shaped UAV and a crawler-type unmanned vehicle respectively; the point cloud data of the surrounding rock of the karst tunnel includes spatial position information and reflection intensity information; The feature extraction module 720 is configured to extract features from the spatial position information and the reflection intensity information to obtain the features of the surrounding rock damage of the karst tunnel; The fusion classification module 730 is configured to fuse and classify the karst tunnel surrounding rock disease characteristics to determine the disease type.

[0039] In some embodiments, the data acquisition module 710 is specifically configured as follows: When detecting the surrounding rock on the top surface of the tunnel, the spiral fan motor is controlled not to start, so that the extension line of the telescopic elastic detection rod points to the first direction, and the point cloud data of the karst tunnel surrounding rock on the top surface of the tunnel is obtained.

[0040] In some embodiments, the data acquisition module 710 is specifically configured as follows: When detecting the surrounding rock on the side of the tunnel, the spiral fan motor is controlled to start so that the extension line of the telescopic elastic detection rod points to the second direction, and the point cloud data of the karst tunnel surrounding rock on the side of the tunnel is obtained.

[0041] In some embodiments, the feature extraction module 720 is specifically configured as follows: Based on the spatial position information and reflection intensity information, the wavelet packet transform is used to decompose the point cloud data of the karst tunnel surrounding rock into multiple different levels, and the karst tunnel surrounding rock disease characteristics are obtained. The karst tunnel surrounding rock disease characteristics include point characteristics, line characteristics, surface characteristics and volume characteristics.

[0042] The detection mechanism control system provided in the embodiment of the present application can realize each process in the embodiment corresponding to the above-mentioned karst tunnel surrounding rock disease monitoring equipment. To avoid repetition, it will not be described here.

[0043] It should be noted that the detection mechanism control system provided in the embodiment of the present application and the karst tunnel surrounding rock disease monitoring equipment provided in the embodiment of the present application 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 repeated.

[0044] In some embodiments, see Figure 8 , Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. An electronic device 800 provided in an embodiment of the present application includes a processor 810 and a memory 820; the memory 820 stores a computer program, wherein the computer program implements the above-mentioned karst tunnel surrounding rock disease monitoring device when executed by the processor.

[0045] Specifically, the processor 810 may include, for example, a general-purpose microprocessor, an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 810 may also include an onboard memory for cache purposes. The processor 810 may be a single processing unit or multiple processing units for executing different actions of the method flow according to an embodiment of the present application.

[0046] The memory 820 may be any medium capable of containing, storing, conveying, propagating or transmitting instructions. For example, the memory 820 may include, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device, component or propagation medium. Specific examples of the memory 820 include: a magnetic storage device, such as a magnetic tape or a hard disk (HDD); an optical storage device, such as a compact disk (CD-ROM); a random access memory (RAM) or flash memory; and / or a wired / wireless communication link.

[0047] The present application also provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned karst tunnel surrounding rock disease monitoring device is implemented. The computer-readable medium may be included in the device / device / system described in the above-mentioned embodiment; or it may exist independently without being assembled into the device / device / system. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed, the method according to the embodiment of the present application is implemented.

[0048] According to an embodiment of the present application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical cable, radio frequency signal, etc., or any suitable combination of the above.

[0049] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present application. In particular, without departing from the spirit and teachings of the present application, the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present application. Therefore, the scope of the present application should not be limited to the above-described embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

1. A karst tunnel surrounding rock disease monitoring device, characterized in that: include: Pole-shaped UAV, crawler-type unmanned vehicle and control system; among them, The rod-shaped drone comprises an airborne 3D laser scanning sensor and a spiral blade motor connected by a telescopic elastic detection rod; when the spiral blade motor is not started, the extension line of the telescopic elastic detection rod points to a first direction; when the spiral blade motor is started, the extension line of the telescopic elastic detection rod points to a second direction; the first direction is perpendicular to the second direction; The crawler-type unmanned vehicle comprises a detection rod fixing device, a limiting column, a vehicle-mounted 3D laser scanning sensor and a crawler; the detection rod fixing device is used to fix the telescopic elastic detection rod, and the limiting column 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 UAV and the tracked unmanned vehicle.

2. The karst tunnel surrounding rock disease monitoring device according to claim 1 is characterized in that: The rod-shaped drone also includes a spiral fan blade and a spiral fan blade protective shell; when the spiral fan blade motor is started, the spiral fan blade provides airflow to adjust the direction of the telescopic elastic detection rod.

3. The karst tunnel surrounding rock disease monitoring device according to claim 1 is characterized in that: Buffer pads are arranged on the conical sides of the limiting column and the limiting groove.

4. The karst tunnel surrounding rock disease monitoring device according to claim 1 is characterized in that: The limiting column and the limiting groove are provided with a hardware interface for completing data transmission and power supply between the pole-shaped UAV and the crawler-type unmanned vehicle.

5. A method for monitoring surrounding rock diseases in a karst tunnel, applied to the monitoring equipment described in claims 1-4, characterized in that: include: The point cloud data of the surrounding rock of the karst tunnel were obtained by using a pole-shaped UAV and a tracked unmanned vehicle respectively; The karst tunnel surrounding rock point cloud data includes spatial position information and reflection intensity information; Extracting features from the spatial position information and the reflection intensity information to obtain the features of the surrounding rock damage of the karst tunnel; The characteristics of the surrounding rock diseases of the karst tunnel are integrated and classified to determine the disease type.

6. The karst tunnel surrounding rock disease monitoring device according to claim 5 is characterized in that: The method of obtaining the surrounding rock point cloud data of the karst tunnel by using a pole-shaped UAV and a crawler-type unmanned vehicle respectively includes: When detecting the surrounding rock on the top surface of the tunnel, the spiral fan motor is controlled not to start, so that the extension line of the telescopic elastic detection rod points to the first direction, and the point cloud data of the karst tunnel surrounding rock on the top surface of the tunnel is obtained.

7. The karst tunnel surrounding rock disease monitoring device according to claim 5 is characterized in that: The method of obtaining the surrounding rock point cloud data of the karst tunnel by using a pole-shaped UAV and a crawler-type unmanned vehicle respectively includes: When detecting the surrounding rock on the side of the tunnel, the spiral fan motor is controlled to start so that the extension line of the telescopic elastic detection rod points to the second direction, and the point cloud data of the karst tunnel surrounding rock on the side of the tunnel is obtained.

8. The karst tunnel surrounding rock disease monitoring device according to claim 5 is characterized in that: The feature extraction of the spatial position information and the reflection intensity information to obtain the surrounding rock disease characteristics of the karst tunnel includes: Based on the spatial position information and the reflection intensity information, the karst tunnel surrounding rock point cloud data is divided into multiple different levels by wavelet packet transform decomposition to obtain the karst tunnel surrounding rock disease characteristics, which include point characteristics, line characteristics, surface characteristics and volume characteristics.

9. A karst tunnel surrounding rock disease monitoring system, characterized in that: include: Data acquisition module, feature extraction module and fusion classification module; among them, The data acquisition module is configured to respectively use a pole-shaped UAV and a crawler-type unmanned vehicle to acquire point cloud data of the surrounding rock of the karst tunnel; the point cloud data of the surrounding rock of the karst tunnel includes spatial position information and reflection intensity information; The feature extraction module is configured to extract features from the spatial position information and the reflection intensity information to obtain the features of the surrounding rock damage of the karst tunnel; The fusion classification module is configured to fuse and classify the karst tunnel surrounding rock disease characteristics to determine the disease type.

10. A computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method according to claims 5 to 8.

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