An automated apparatus for acquiring the profile of the inner wall of a tunnel and the amount of settlement and a method of use

Abstract

The application discloses a kind of automatic equipment and use method of obtaining tunnel inner wall profile and settlement, it is related to tunnel monitoring technical field.The application includes main structure, tunnel monitoring structure, control and data post-processing structure, device advancing structure and power supply structure, the outside of main structure is sequentially provided with tunnel monitoring structure, control and data post-processing structure, device advancing structure and power supply structure.The application obtains the point cloud data of tunnel inner wall profile within a certain distance by laser radar sensor at the measuring point, then the measured point cloud coordinates are transmitted to embedded computer, the computer selects the point cloud data of certain same X value and sequentially connects each point cloud coordinate, so as to obtain tunnel cross section two-dimensional graph, the measuring point is taken as origin, the length of tunnel wall is sequentially divided by equal division method, and the sequential division angle is obtained, finally the divided angle is transmitted to rudder by the upper computer software of rudder, so that rudder drives high-precision laser ranging sensor to uniformly measure tunnel wall.

Description

Technical Field

[0001] This invention relates to the field of tunnel monitoring technology, specifically to an automated equipment and method for acquiring the contour and settlement of the tunnel inner wall. Background Technology

[0002] Tunnel engineering is an important and complex undertaking, involving the construction and management of underground spaces. During tunnel construction and operation, the need for acquiring tunnel wall profiles and monitoring tunnel settlement has become increasingly prominent. These two technologies and monitoring methods are crucial for ensuring the safety of tunnel structures and the reliability of their operation.

[0003] Accurately obtaining the contour information of the tunnel interior walls is crucial for design, construction, and maintenance during tunnel construction and maintenance. Traditional methods include manual measurement and the use of optical instruments, but these methods are inefficient, costly, and limited by environmental conditions. In recent years, with the development of modern technologies such as laser scanners and 3D LiDAR, wall contour acquisition has entered a new stage. However, some problems still exist, such as the potential inadequacy of laser scanner coverage for complex-shaped tunnel interior walls, requiring further research and improvement.

[0004] Tunnel settlement is the phenomenon of tunnel structure subsidence caused by underground engineering construction, changes in groundwater levels, or other factors. Settlement monitoring is an important means to ensure the safe operation of tunnel structures. Traditional settlement monitoring methods mainly include benchmark point measurement and strain measurement, but these methods have problems such as long monitoring cycles and limited coverage.

[0005] Due to the imperfections in intelligent tunnel monitoring technology and the inability of detection instruments to meet accuracy requirements, most tunnel monitoring projects still rely on traditional manual monitoring methods and techniques. Considering the positive impact of intelligent tunnel monitoring technology on tunnel construction, research on the technology of obtaining tunnel inner wall contours and monitoring tunnel settlement is needed to provide guidance and reference for future tunnel monitoring technologies. Therefore, a new solution to the above problems is required. Summary of the Invention

[0006] The purpose of this invention is to provide an automated equipment and method for obtaining the contour and settlement of the inner wall of a tunnel.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an automated equipment for acquiring the contour and settlement of the inner wall of a tunnel, and an automated equipment and method for acquiring the contour and settlement of the inner wall of a tunnel, comprising a main structure, a tunnel monitoring structure, a control and data post-processing structure, a device travel structure and a power supply structure, wherein the tunnel monitoring structure, the control and data post-processing structure, the device travel structure and the power supply structure are arranged sequentially on the outer side of the main structure. The main structure includes a first-level foundation and a second-level foundation, which are connected by support columns. The tunnel monitoring structure includes lidar sensors and high-precision laser rangefinders; The device's traveling mechanism includes a motor with an encoder; The control and data post-processing architecture includes a two-dimensional servo gimbal and an embedded tablet PC; The power supply structure includes a power supply unit and a power adapter. The power supply unit is placed at the top of the first-layer support of the device and is located in the middle of the first-layer support. The top of the first-layer foundation is also equipped with a first core plate, which is used to control the motor with an encoder.

[0008] Four motors with encoders are symmetrically arranged at the bottom of the first-level platform. One end of each motor with an encoder is equipped with a rubber tire. The encoders on the motors can obtain the number of rotations of the tire. The top of the second-layer foundation is equipped with an auxiliary support frame and a vertical plate. The auxiliary support frame is located at one end of the top of the second-layer foundation, and the vertical plate is located at one end of the auxiliary support frame. Preferably, an embedded tablet computer is provided at the top of the auxiliary carrier, and a two-dimensional servo gimbal is provided at the end of the vertical plate away from the auxiliary carrier. The two-dimensional servo gimbal is connected to the vertical plate in a horizontal inverted manner. Preferably, the lidar sensor is located at the top of the second-layer support platform and at the end of the second-layer support platform away from the auxiliary frame. A high-precision laser rangefinder sensor is installed at the end of the two-dimensional servo gimbal away from the vertical plate. The lidar sensor is a multi-line lidar sensor, and its scanning angle and scanning distance limits are determined by the size of the tunnel. Preferably, the two-dimensional servo gimbal is horizontally fixedly connected to the high-precision laser rangefinder, thereby controlling the rotation of the high-precision laser rangefinder in all directions. The embedded tablet computer controls the operation of other devices and data collection and transmission through various communication interfaces, and performs data processing. The high-precision laser rangefinder is a millimeter-level high-precision laser rangefinder. The measurement range of the high-precision laser rangefinder is determined by the monitoring distance required for the monitored tunnel. The mass of the high-precision laser rangefinder and the required rotation angle range determine the torque value and rotation angle range of the corresponding two-dimensional servo gimbal. Preferably, the power supply is a multi-interface power supply device. The type of power adapter and the interface type of the power supply are determined by the voltage used by each structure and instrument of the equipment, and the power capacity of the power supply is determined by the power consumption of each device. Preferably, an ultrasonic sensor is installed and connected to the lower end of the embedded tablet computer. A second core board for controlling the two-dimensional servo gimbal and the ultrasonic sensor is also provided on the upper surface of the second support platform. The second core board is located between the lidar sensor and the embedded tablet computer. The ultrasonic sensor determines its measurement distance range based on the required distance traveled from the tunnel wall. The embedded tablet computer is a mini multi-interface touch tablet computer. The embedded tablet computer is connected to the first core board, the second core board, the lidar sensor, and the high-precision laser rangefinder sensor through multiple communication interfaces. Preferably, the embedded tablet computer controls the rotation of the two-dimensional servo gimbal and the motor in real time through host computer software. It uses the Pythagorean theorem, the method of equal division, and outlier monitoring to process point cloud data and controls the differential rotation of the motor through the distance value of the ultrasonic sensor to achieve a fixed distance travel along the tunnel wall. The position of the motor and the number of revolutions are determined by calculating the number of pulses, and the total travel distance is obtained by multiplying the wheel axle circumference by the number of revolutions.

[0009] Preferably, the lidar sensor acquires point cloud data of the tunnel inner wall contour at a certain distance from the starting point, and obtains the required rotation angle of the servo motor through the equal division method. The high-precision laser rangefinder sensor obtains the three-dimensional coordinate value of the measured point by combining the measured distance value with the preset angle value of the servo motor through the Pythagorean theorem algorithm, thereby fitting the point cloud data of the lidar sensor at that position. The outlier detection method is used to filter out points that are not within the specified range near the line connecting the corresponding points of two consecutive sections of the rangefinder, thereby achieving the high-precision requirements for monitoring the tunnel inner wall contour and settlement.

[0010] A method for using automated equipment to obtain tunnel inner wall contours and settlement: S1: Write corresponding instructions in the embedded tablet computer for the monitoring path required for the tunnel; S2: Place the invention device at the tunnel monitoring starting point and turn on the power supply structure; S3: The lidar sensor acquires point cloud data of the inner wall contour of the tunnel at a certain distance from the starting point. Then, it transmits the measured point cloud coordinates to the embedded tablet computer. The embedded tablet computer selects the point cloud data with X=m value and connects the point cloud coordinates in sequence to obtain a two-dimensional graphic of the tunnel cross section. Taking the starting point as the origin, the tunnel wall length is divided into equal parts by the equal division method, and the division angles are obtained in sequence. Finally, the division angles are transmitted to the two-dimensional servo gimbal through the host computer software of the two-dimensional servo gimbal, so that the two-dimensional servo gimbal drives the high-precision laser rangefinder to uniformly measure the tunnel wall. S4: The high-precision laser rangefinder combines the measured distance value with the preset angle value of the two-dimensional servo gimbal and uses the Pythagorean theorem algorithm to obtain the three-dimensional coordinate value of the measured point, thereby fitting the point cloud data of the laser radar at that location. The outlier detection method is used to filter out points that are not within the specified range near the line connecting the corresponding points of two consecutive sections of the high-precision laser rangefinder, thereby achieving the high-precision requirements for tunnel inner wall contour and settlement monitoring. S5: After the cross-section monitoring is completed, the ultrasonic sensor uses the distance between the detection device and the tunnel wall to realize the fixed distance movement of the device relative to the tunnel wall. For straight tunnels, the number of pulses obtained by the encoder in the encoder motor is converted into the travel distance, thereby realizing the real-time positioning function. S6: After the device travels a certain distance, the high-precision laser ranging sensor will perform the next round of monitoring. The laser radar sensor will scan once after m. The above operation is repeated until the monitoring is completed. S7: After monitoring is completed, the device returns to the starting position, prepares for the second monitoring, and uploads the measured results to the cloud.

[0011] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention uses a lidar sensor to acquire point cloud data of the tunnel wall contour at a certain distance from the starting point. The measured point cloud coordinates are then transmitted to an embedded computer. The computer selects point cloud data with the same X value and connects the coordinates of each point cloud sequentially to obtain a two-dimensional graphic of the tunnel cross-section. Taking the starting point as the origin, the tunnel wall length is divided into equal parts using the equal division method, and the division angles are obtained sequentially. Finally, the division angles are transmitted to the servo motor via the host computer software, thereby enabling the servo motor to drive a high-precision laser rangefinder to uniformly measure the tunnel wall. The high-precision laser rangefinder combines the measured distance value with the angle value preset by the servo motor and uses the Pythagorean theorem algorithm to obtain the three-dimensional coordinate value of the measured point, thereby fitting the lidar point cloud data at that location. An outlier detection method is used to filter out points that are not within the specified range near the line connecting two consecutive cross-sections of the rangefinder, thus achieving high-precision monitoring of the tunnel wall contour and settlement. The device then uses the number of wheel axle rotations and the distance from the device to the tunnel wall obtained by the motor encoder and ultrasonic sensor to achieve fixed-distance travel with the tunnel wall. 2. The lidar sensor described in this invention is a multi-line lidar sensor, which can obtain the detailed outline of the tunnel inner wall through high-frequency scanning.

[0012] 3. The ranging sensor described in this invention is a high-precision ranging sensor that can accurately measure the distance from each section of the tunnel to the monitoring robot. The coordinate values ​​of the measured points are obtained by measuring the distance and the rotation angle of the servo motor, thereby fitting the point cloud coordinates of the lidar and realizing high-precision tunnel settlement monitoring.

[0013] 4. The two-dimensional servo gimbal described in this invention can effectively control the rotation of the high-precision laser rangefinder sensor in all directions, and can effectively realize the high-precision laser rangefinder sensor's comprehensive distance measurement of tunnels. 5. The motor described in this invention is a motor with an encoder. By converting the number of revolutions of the wheel axle obtained by the encoder into the travel distance of the device, real-time positioning in a straight tunnel can be achieved.

[0014] 6. The computer described in this invention is an embedded tablet computer with multiple communication interfaces, which can make full use of the device space and connect to various instruments and equipment through various communication interfaces to realize real-time control, data acquisition and processing of various instruments and equipment, thereby realizing full automation of tunnel monitoring.

[0015] 7. The ultrasonic sensor described in this invention can obtain the distance between the device and the tunnel wall in real time, thereby controlling the differential rotation of the motor and realizing the fixed-distance movement of the device.

[0016] 8. This invention first obtains the tunnel outline using a lidar, and then obtains the servo motor rotation angle using the equal division method. This can effectively control the servo motor to swing uniformly at any position on the tunnel cross section at a fixed distance, thereby preventing the influence of uneven spotting and poor fitting effect of high-precision laser rangefinders.

[0017] 9. This invention filters out point clouds with large deviations from lidar data through outlier detection, thereby making the point clouds of tunnel wall contours and settlement more accurate and detailed.

[0018] 10. For straight tunnels, the location of the detection device can be obtained by using the number of pulses from the motor encoder.

[0019] 11. This invention occupies little space, has a simple structure, and has high measurement efficiency and automation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a flowchart illustrating the overall operation of the device of the present invention.

[0022] Figure 3 This is a flowchart of the high-precision point cloud data acquisition process of the present invention. The attached diagram lists the components represented by each number as follows: In the diagram: 1. Power supply; 2. First core board; 3. Motor with encoder; 4. Embedded tablet computer; 5. Ultrasonic sensor; 6. Two-dimensional servo gimbal; 7. Second core board; 8. High-precision laser rangefinder sensor; 9. LiDAR sensor. Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Example

[0024] Please see Figures 1-3 An automated equipment and method for acquiring the contour and settlement of the inner wall of a tunnel, comprising a main structure, a tunnel monitoring structure, a control and data post-processing structure, a device travel structure and a power supply structure, wherein the tunnel monitoring structure, the control and data post-processing structure, the device travel structure and the power supply structure are arranged sequentially on the outer side of the main structure. The main structure includes a first-level foundation and a second-level foundation, which are connected by support columns. The tunnel monitoring structure includes a lidar sensor 9 and a high-precision laser rangefinder sensor 8; The device's traveling structure includes a motor 3 with an encoder; The control and data post-processing architecture includes a two-dimensional servo gimbal 6 and an embedded tablet computer 4; The power supply structure includes a power supply unit 1 and a power adapter. The power supply unit 1 is placed at the top of the first layer of the device and is located in the middle of the first layer of the device. The top of the first-layer support is also equipped with a first core plate 2, which is used to control the motor 3 with an encoder.

[0025] Four motors 3 with encoders are symmetrically arranged at the bottom of the first layer of the platform. One end of each motor 3 with encoder is equipped with a rubber tire. The encoder of the motor 3 with encoder can obtain the number of rotations of the tire. The top of the second-layer foundation is equipped with an auxiliary support frame and a vertical plate. The auxiliary support frame is located at one end of the top of the second-layer foundation, and the vertical plate is located at one end of the auxiliary support frame. An embedded tablet computer 4 is installed at the top of the auxiliary frame, and a two-dimensional servo gimbal 6 is installed at the end of the vertical plate away from the auxiliary frame. The two-dimensional servo gimbal 6 is connected to the vertical plate in a horizontal inverted manner. The lidar sensor 9 is located at the top of the second-layer platform and at the end of the second-layer platform away from the auxiliary frame. The two-dimensional servo gimbal 6 is equipped with a high-precision laser range sensor 8 at the end away from the vertical plate. The lidar sensor 9 is a multi-line lidar sensor, and its scanning angle and scanning distance limits are determined by the size of the tunnel. The two-dimensional servo gimbal 6 is horizontally fixedly connected to the high-precision laser rangefinder 8, thereby controlling the rotation of the high-precision laser rangefinder 8 in all directions. The embedded tablet computer 4 controls the operation of other devices and data collection and transmission through various communication interfaces, and performs data processing. The high-precision laser rangefinder 8 is a millimeter-level high-precision laser rangefinder. The measurement range of the high-precision laser rangefinder 8 is determined by the monitoring distance required for monitoring the tunnel. The mass of the high-precision laser rangefinder 8 and the required rotation angle range determine the torque value and rotation angle range of the corresponding two-dimensional servo gimbal 6. Power supply 1 is a multi-interface power supply device. The type of power adapter and the interface type of power supply 1 are determined by the voltage used by each structure and instrument of the equipment, and the capacity of power supply 1 is determined by the power consumption of each device. An ultrasonic sensor 5 is installed and connected to the lower end of the embedded tablet PC 4. A second core board 7 for controlling the two-dimensional servo gimbal 6 and the ultrasonic sensor 5 is also set on the upper surface of the second layer platform. The second core board 7 is located between the lidar sensor 9 and the embedded tablet PC 4. The ultrasonic sensor 5 determines its measurement distance range based on the required distance traveled from the tunnel wall. The embedded tablet PC 4 is a mini multi-interface touch tablet PC. The embedded tablet PC 4 is connected to the first core board 2, the second core board 7, the lidar sensor 9, and the high-precision laser rangefinder 8 through multiple communication interfaces. The embedded tablet computer 4 controls the rotation of the two-dimensional servo gimbal 6 and the motor in real time through the host computer software. It uses the Pythagorean theorem, the method of equal division, and outlier monitoring to process point cloud data and controls the differential rotation of the motor through the distance value of the ultrasonic sensor 5 to achieve a fixed distance travel along the tunnel wall. It determines the position of the motor and the number of revolutions by calculating the number of pulses, and then obtains the total travel distance by multiplying the wheel axle circumference by the number of revolutions.

[0026] The lidar sensor 9 acquires point cloud data of the tunnel inner wall contour at a certain distance from the starting point, and obtains the required rotation angle of the servo motor through the equal division method. The high-precision laser rangefinder 8 obtains the three-dimensional coordinate value of the measured point by combining the measured distance value with the angle value preset by the servo motor and using the Pythagorean theorem algorithm. This fits the point cloud data of the lidar sensor 9 at that location, and filters out points that are not within the specified range near the line connecting the corresponding points of two consecutive sections of the rangefinder through the outlier detection method, thereby achieving the high-precision requirements for monitoring the tunnel inner wall contour and settlement. Example

[0027] To verify the efficiency and automation of this invention in acquiring tunnel inner wall contours and monitoring tunnel settlement, a comparative analysis was conducted on tunnel contour acquisition using a handheld lidar and tunnel settlement monitoring using a total station, comparing them with the device of this invention. Two highway tunnels in a certain region were selected, with inner wall widths and heights of 7m and 10m respectively. The operation of tunnel contour acquisition using a handheld lidar and tunnel settlement monitoring using a total station was first analyzed, including the following steps: Step 1: Install the lidar equipment on the support frame at the starting point of the tunnel measurement, ensuring the equipment is stable. Also, set up the total station and adjust all components.

[0028] Step 2: Handhold the lidar device and move it slowly along the predetermined path, maintaining an appropriate distance between the device and the tunnel wall. Select target points for the total station to monitor within the tunnel, and place reflectors or reflective patches at each target point to ensure accurate measurement by the total station.

[0029] Step 3: Import the point cloud data acquired by the LiDAR into the appropriate data processing software to filter the point cloud data and output the tunnel outline graphic. Then, use a total station to measure each target point and obtain the three-dimensional coordinates of the target points.

[0030] Step 4: Repeat the above operations periodically to achieve detailed drawing of the tunnel outline and comparative analysis of tunnel settlement.

[0031] To verify the efficiency and automation of this invention in acquiring tunnel inner wall contours and monitoring tunnel settlement, a comparative analysis was conducted between manual handheld lidar for tunnel contour acquisition and total station for tunnel settlement monitoring, and the device of this invention. Two highway tunnels in a certain region were selected, with inner wall widths and heights of 7m and 10m respectively. An experiment was conducted using the device of this invention to acquire tunnel inner wall contours and monitor tunnel settlement, including the following steps: Step 1: Write the corresponding instructions in the embedded tablet PC 4 for the required monitoring path of the tunnel.

[0032] Step Two: Place the invention device at the tunnel monitoring starting point and turn on the power. The lidar sensor 9 acquires point cloud data of the tunnel wall contour at a certain distance from the starting point. The measured point cloud coordinates are then transmitted to an embedded computer. The computer selects point cloud data with an X=1m value and connects the coordinates sequentially to obtain a two-dimensional cross-section of the tunnel. Using the starting point as the origin, the tunnel wall length is divided equally using the equal division method, and the resulting angles are obtained sequentially. Finally, the angles are transmitted to the servo motor via its host computer software, causing the servo motor to drive the high-precision laser rangefinder sensor to uniformly measure the tunnel wall. The high-precision laser rangefinder sensor 8 combines the measured distance value with the angle value preset by the servo motor and uses the Pythagorean theorem algorithm to obtain the three-dimensional coordinates of the measured point. This fits the point cloud data of the lidar sensor 9 at that location. An outlier detection method is used to filter out points not within the specified range near the line connecting two consecutive cross-sections of the rangefinder, thus achieving the high-precision requirements for monitoring the tunnel wall contour and settlement. After the cross-sectional monitoring is completed, the ultrasonic module uses the distance between the detection device and the tunnel wall to achieve fixed-distance movement of the device relative to the tunnel wall. For straight tunnels, the number of pulses obtained by the encoder of the motor is converted into the travel distance, thereby achieving real-time positioning. After the device travels 10cm, the high-precision laser ranging sensor 8 performs the next round of monitoring, while the lidar sensor scans once every 1m. The above operation is repeated until the monitoring is completed.

[0033] Step 3: After the monitoring is completed, the device returns to the starting position, prepares for the second monitoring, and uploads the measured results to the cloud.

[0034] In summary: The present invention addresses the technical problems by employing the technical solutions of the above embodiments. Through the above-described settings, this application can certainly solve the aforementioned technical problems and achieve the following technical effects: 1. The lidar sensor of the present invention is a multi-line lidar sensor, which can obtain the detailed contour of the tunnel inner wall through high-frequency scanning.

[0035] 2. The ranging sensor of the present invention is a high-precision ranging sensor that can accurately measure the distance from each section of the tunnel to the monitoring robot. The coordinate values ​​of the measured points are obtained by measuring the distance and the rotation angle of the servo motor, thereby fitting the point cloud coordinates of the lidar and realizing high-precision tunnel settlement monitoring.

[0036] 3. The two-dimensional servo gimbal of this invention can effectively control the rotation of the high-precision laser rangefinder sensor in all directions, enabling the high-precision laser rangefinder sensor to perform comprehensive distance measurements in tunnels. 4. The motor of this invention is a motor with an encoder. By converting the number of revolutions of the wheel axle obtained by the encoder into the travel distance of the device, real-time positioning in a straight tunnel can be achieved.

[0037] 5. The computer of this invention is an embedded tablet computer with multiple communication interfaces, which can make full use of the device space and connect to various instruments and equipment through various communication interfaces to realize real-time control, data acquisition and processing of various instruments and equipment, thereby realizing full automation of tunnel monitoring.

[0038] 6. The ultrasonic sensor of this invention can obtain the distance between the device and the tunnel wall in real time, thereby controlling the rotation speed of the motor and realizing the fixed-distance movement of the device.

[0039] 7. This invention first obtains the tunnel outline using a lidar, and then obtains the servo motor rotation angle using the equal division method. This can effectively control the servo motor to swing uniformly at any position on the tunnel cross section at a fixed distance, thereby preventing the influence of uneven spotting and poor fitting effect of high-precision laser rangefinders.

[0040] 8. This invention filters out point clouds with large deviations from lidar data using outlier detection methods, thereby making the point clouds of tunnel wall contours and settlement more accurate and detailed.

[0041] 10. For straight tunnels, the location of the detection device can be obtained by using the number of pulses from the motor encoder.

[0042] 11. This invention occupies little space, has a simple structure, and offers high measurement efficiency and automation.

[0043] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An automated device for acquiring the contour and settlement of the tunnel inner wall, characterized in that: It includes a main structure, a tunnel monitoring structure, a control and data post-processing structure, a device travel structure, and a power supply structure. The tunnel monitoring structure, the control and data post-processing structure, the device travel structure, and the power supply structure are arranged sequentially on the outside of the main structure. The main structure includes a first-layer support platform and a second-layer support platform, which are connected by support columns. The tunnel monitoring structure includes a lidar sensor (9) and a high-precision laser ranging sensor (8). The traveling structure of the device includes a motor (3) with an encoder; The control and data post-processing structure includes a two-dimensional servo gimbal (6) and an embedded tablet computer (4). The power supply structure includes a power supply unit (1) and a power adapter. The power supply unit (1) is placed at the top of the first layer of the device and is located in the middle of the first layer of the device. A first core plate (2) is also provided at the top of the first layer of the support platform. The first core plate (2) is used to control the motor (3) with encoder. An ultrasonic sensor (5) is installed and connected to the lower end of the embedded tablet computer (4). A second core board (7) for controlling the two-dimensional servo gimbal (6) and the ultrasonic sensor (5) is also provided on the upper surface of the second layer platform. The second core board (7) is located between the laser radar sensor (9) and the embedded tablet computer (4). The ultrasonic sensor (5) determines its measurement distance range by the required distance traveled from the tunnel wall. The embedded tablet computer (4) is a mini multi-interface touch tablet computer. The embedded tablet computer (4) is connected to the first core board (2), the second core board (7), the laser radar sensor (9), and the high-precision laser rangefinder (8) by multiple communication interfaces. The lidar sensor (9) obtains point cloud data of the inner wall contour of the tunnel at a certain distance from the starting point, and obtains the required rotation angle of the servo motor by the equal division method; the high-precision laser rangefinder (8) obtains the three-dimensional coordinate value of the measured point by combining the measured distance value with the angle value preset by the servo motor through the Pythagorean theorem algorithm, thereby fitting the point cloud data of the lidar sensor (9) at this position, and filtering out points that are not within the specified range near the line connecting the corresponding points of two consecutive sections of the rangefinder by the outlier detection method.

2. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 1, characterized in that: Four encoder motors (3) are symmetrically arranged at the bottom of the first layer of the platform. One end of each encoder motor (3) is equipped with a rubber tire. The encoder of the encoder motor (3) can obtain the number of rotations of the tire.

3. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 1, characterized in that: An auxiliary support frame and a vertical plate are provided at the top of the second-layer support platform. The auxiliary support frame is located at one end of the top of the second-layer support platform, and the vertical plate is located at one end of the auxiliary support frame.

4. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 3, characterized in that: An embedded tablet computer (4) is provided at the top of the auxiliary carrier, and a two-dimensional servo gimbal (6) is provided at the end of the vertical plate away from the auxiliary carrier. The two-dimensional servo gimbal (6) is horizontally inverted and connected to the vertical plate.

5. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 4, characterized in that: The lidar sensor (9) is located at the top of the second-layer platform and at the end of the second-layer platform away from the auxiliary frame. The two-dimensional servo gimbal (6) is equipped with a high-precision laser rangefinder sensor (8) at the end away from the vertical plate. The lidar sensor (9) is a multi-line lidar sensor, and its scanning angle and scanning distance limit are determined by the size of the tunnel.

6. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 5, characterized in that: The two-dimensional servo gimbal (6) is horizontally fixedly connected to the high-precision laser rangefinder (8), thereby controlling the rotation of the high-precision laser rangefinder (8) in all directions. The embedded tablet computer (4) controls the operation of other devices and data collection and transmission through various communication interfaces, and performs data processing. The high-precision laser rangefinder (8) is a millimeter-level high-precision laser rangefinder. The measurement range of the high-precision laser rangefinder (8) is determined by the monitoring distance required for monitoring the tunnel. The mass of the high-precision laser rangefinder (8) and the required rotation angle range determine the torque value and rotation angle range of the corresponding two-dimensional servo gimbal (6).

7. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 1, characterized in that: The power supply (1) is a multi-interface power supply device. The type of power adapter and the interface type of the power supply (1) are determined by the voltage used by each structure and instrument of the equipment, and the power capacity of the power supply (1) is determined by the power consumption of each device.

8. The automated equipment for obtaining the contour and settlement of the tunnel inner wall according to claim 1, characterized in that: The embedded tablet computer (4) controls the rotation of the two-dimensional servo gimbal (6) and the rotation of the motor in real time through the host computer software.

9. A method of using an automated equipment for acquiring the contour and settlement of a tunnel inner wall, used in any one of claims 1-8, characterized in that: S1: Write the corresponding instructions in the embedded tablet computer (4) for the monitoring path required for the tunnel; S2: Place the device at the tunnel monitoring starting point and turn on the power supply (1); S3: The lidar (9) sensor acquires point cloud data of the inner wall contour of the tunnel at a certain distance from the starting point, and then transmits the measured point cloud coordinates to the embedded tablet computer (4). The embedded tablet computer (4) selects the point cloud data with X=1m value and connects the point cloud coordinates in sequence to obtain a two-dimensional graphic of the tunnel cross section. Taking the starting point as the origin, the tunnel wall length is divided into equal parts by the equal division method, and the division angles are obtained in sequence. Finally, the division angles are transmitted to the two-dimensional servo gimbal (6) through the host computer software of the two-dimensional servo gimbal (6), so that the two-dimensional servo gimbal (6) drives the high-precision laser ranging sensor (8) to uniformly measure the tunnel wall. S4: The high-precision laser rangefinder (8) combines the measured distance value with the angle value preset by the two-dimensional servo gimbal (6) and obtains the three-dimensional coordinate value of the measured point through the Pythagorean theorem algorithm, thereby fitting the point cloud data of the laser radar (9) at this position, and filtering out points that are not within the specified range near the line connecting the corresponding points of two consecutive sections of the high-precision laser rangefinder (8) through the outlier detection method, thereby achieving the high-precision requirements for tunnel inner wall contour and settlement monitoring; S5: After the cross-section monitoring is completed, the ultrasonic sensor (5) realizes the fixed distance movement of the device relative to the tunnel wall by detecting the distance between the device and the tunnel wall. For straight tunnels, the number of pulses obtained by the encoder in the motor (3) with encoder is converted into the travel distance, thereby realizing the real-time positioning function. S6: After the device travels a certain distance, the high-precision laser ranging sensor (8) will perform the next round of monitoring. The sensor of the laser radar (9) will scan once every 1m. The operation is repeated until the monitoring is completed. S7: After monitoring is completed, the device returns to the starting position, prepares for the second monitoring, and uploads the measured results to the cloud.

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