Tunnel inspection vehicle based on geological radar and tunnel lining quality inspection system and method

Abstract

The present invention provides a tunnel inspection vehicle and a tunnel lining quality inspection system and method based on geological radar. The tunnel inspection vehicle is characterized by comprising: a plurality of inspection arms for supporting geological radars to move on the tunnel lining surface; a carrying engineering vehicle for carrying a mechanical arm to move on the road surface; a plurality of geological radars for inspecting the tunnel lining quality based on radar signals; a tunnel lining quality inspection system for acquiring lining surface data and trajectory data of the carrying engineering vehicle in real time, and adaptively controlling the telescopic parameters of the inspection arms and the supporting angle of the geological radar based on the lining surface data and trajectory data. Through the coordinated cooperation between various components and systems, the present invention achieves stable fitting of the geological radar antenna to the tunnel lining curved surface under various road conditions, thereby improving the efficiency, accuracy, and safety of tunnel lining quality inspection, while meeting the inspection needs of different scenarios of tunnels under construction and in operation.

Description

Technical Field

[0001] The present invention relates to the technical field of geological radar tunnel detection, and in particular to a geological radar-based tunnel detection vehicle and a tunnel lining quality detection system and method. Background Art

[0002] With the continuous development of transportation infrastructure, the number of tunnel projects is increasing. Tunnel lining quality is directly related to tunnel safety and service life, making accurate inspection of tunnel lining quality crucial. Currently, commonly used tunnel lining quality inspection methods include manual percussion and acoustic transmission. The manual percussion method relies on the inspector's experience, resulting in low efficiency, poor accuracy, and potential safety hazards. The acoustic transmission method requires pre-embedded inspection tubes in the tunnel lining, which is complex and costly. It also fails to fully detect defects such as voids and looseness within the lining. Geological radar inspection technology has been widely used in tunnel lining quality inspection due to its advantages of fast speed, non-destructiveness, and high resolution. However, existing tunnel inspection equipment struggles to ensure continuous alignment of the geological radar antenna with the curved tunnel lining surface under complex road conditions. The antenna is prone to shaking and drifting during inspection, resulting in large errors in the inspection data and a high rate of missed detections. Furthermore, most equipment lacks the flexibility to adapt to the varying inspection environments and requirements of tunnels under construction and in operation, limiting the effectiveness of inspections. New inspection technologies and equipment are urgently needed to address these issues. Summary of the Invention

[0003] The present invention provides a tunnel inspection vehicle and a tunnel lining quality inspection system and method based on geological radar. Through the coordinated cooperation between various components and systems, the geological radar antenna and the tunnel lining curved surface can be stably fitted under various road conditions, thereby improving the efficiency, accuracy and safety of tunnel lining quality inspection, while meeting the inspection needs of different scenarios of tunnels under construction and in operation.

[0004] The present invention provides a tunnel inspection vehicle based on geological radar, comprising: a plurality of inspection arms and a carrying engineering vehicle, a plurality of geological radars and a tunnel lining quality inspection system;

[0005] Among them, the bottom ends of several detection arms are connected to the carrying engineering vehicles respectively, and the top ends are equipped with geological radar supporting equipment to support the geological radar to move on the tunnel lining surface;

[0006] The transport engineering vehicle is used to carry the robotic arm and move it on the road;

[0007] Multiple geological radars for detecting tunnel lining quality based on radar signals;

[0008] The tunnel lining quality inspection system is used to obtain real-time lining surface data and the trajectory data of the carrying engineering vehicle. Based on the lining surface data and trajectory data, the telescopic parameters of the inspection arm and the supporting angle of the geological radar are adaptively controlled.

[0009] Preferably, a tunnel lining quality inspection system based on a tunnel inspection vehicle using a geological radar comprises:

[0010] The surface adaptive system is used to collect the contour data of the tunnel lining surface using a 3D laser scanner, establish a 3D surface model of the lining, and update the 3D surface model based on the real-time collected contour data;

[0011] The self-balancing control system is used to actually collect the tilt parameters, vibration frequency and acceleration changes of the transport engineering vehicle, generate vehicle operation data, and adaptively adjust the extension and retraction of the hydraulic suspension of the detection arm base based on the vehicle operation data;

[0012] The surface fitting planning system is used to plan the detection trajectory of each detection arm according to the lining three-dimensional surface model, and to adjust the telescopic parameters of the detection arm and the detection angle of the geological radar in real time according to the height change of the detection arm base. The detection planning trajectory is adaptively corrected according to the adjustment results;

[0013] The radar detection control system is used to control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signals.

[0014] Preferably, in a tunnel lining quality detection system of a tunnel inspection vehicle based on geological radar, the surface adaptive system includes:

[0015] A contour data acquisition module is used to collect contour data of the tunnel lining surface based on a three-dimensional laser scanner arranged in front of the transport engineering vehicle;

[0016] A three-dimensional model building module is used to adjust the parameters of the preset lining contour model based on the contour data to obtain a three-dimensional surface model of the lining;

[0017] The real-time update module is used to obtain real-time contour data according to the movement of the transport engineering vehicle, and dynamically update the lining three-dimensional surface model based on the real-time contour data.

[0018] Preferably, in a tunnel lining quality detection system of a tunnel inspection vehicle based on geological radar, the self-balancing control system includes:

[0019] The vehicle data acquisition module is used to collect chassis tilt parameters, vibration frequency, and acceleration changes of engineering vehicles during tunnel lining quality inspection, and generate vehicle operation data after pre-processing.

[0020] The intelligent adaptive analysis module is used to determine the tilt angle and tilt direction of the detection arm based on the chassis tilt parameters, and the tilt height of each point on the detection arm base in combination with the fixed position of the detection arm on the transport engineering vehicle;

[0021] Determine the highest tilt point and the lowest tilt point on the detection arm base in the tilt direction, obtain a tilt height difference, and perform compression adjustment on the hydraulic support device on the side of the highest tilt point based on the tilt height difference;

[0022] The tilt height at the lowest tilt point is sent to the surface fitting control system.

[0023] Preferably, in a tunnel lining quality inspection system based on a tunnel inspection vehicle using a geological radar, the surface fitting planning system includes:

[0024] The vehicle path planning subsystem is used to determine the geometric parameters of the tunnel based on the 3D surface model of the lining, and generate a preset vehicle trajectory based on the tunnel's operating data and the maximum arm span of the detection arm;

[0025] Radar inspection movement planning subsystem, used to determine the basic inspection strategy for the current lining inspection based on geometric parameters and vehicle preset running trajectory;

[0026] According to the basic detection strategy and the preset running trajectory of the vehicle, the moving speed and trajectory of each geological radar are determined to obtain the detection planning trajectory;

[0027] The telescopic strategy planning subsystem is used to determine the initial detection position based on the detection planning trajectory, obtain the detection angle corresponding to the initial detection position, and determine the detection angle change of each geological radar on its corresponding detection planning path in combination with the lining three-dimensional surface model and radar antenna position data;

[0028] determining an angle change of the detection arm forearm based on the detected angle change;

[0029] According to the transformation correlation relationship between the large and small arms of the detection arm and the angle transformation of the small arm of the detection arm, combined with the height change data on the radar detection planning path corresponding to each detection arm, the preset extension and retraction strategy of the detection arm corresponding to each radar antenna is determined respectively.

[0030] Preferably, in a tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar, the radar inspection movement planning subsystem further includes:

[0031] Radar movement parameter planning unit, used to predict the position change of the detection arm base based on the preset vehicle trajectory;

[0032] According to the position change of the detection arm base, the relative position relationship between each detection arm and its corresponding one-way responsibility area is determined, and based on the relative position relationship, the movement trajectory of each geological radar is determined respectively;

[0033] According to the length of a single detection moving trajectory on the one-way responsibility area of ​​the detection arm corresponding to each geological radar, based on the single-round detection consistent completion rule and combined with the minimum holding time of the geological radar, the moving speed of each geological radar is calculated to determine the corresponding moving speed of each geological radar;

[0034] Based on the moving speed and trajectory of each geological radar, the corresponding detection planning trajectory is generated.

[0035] Preferably, in a tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar, the vehicle path planning subsystem includes:

[0036] A real-time determination module is used to determine whether the tunnel lining is not completed based on the tunnel's operational data;

[0037] If the tunnel lining is completed, the geometric parameters of the tunnel are determined based on the 3D surface model of the lining. Combined with the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full surface inspection of the lining in a single pass.

[0038] If possible, a straight running trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory;

[0039] If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel and the maximum arm span of the detection arm. The tunnel surface is segmented based on the optimal number of single-trip detections to determine the single-trip responsibility area corresponding to each single-trip detection.

[0040] Based on the regional center line of the one-way responsible area, multiple straight-line running tracks are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple straight-line running tracks is determined to generate a preset vehicle track;

[0041] If the tunnel lining is not completed, obstacle data is collected inside the tunnel. Based on this obstacle data and the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full curved surface inspection of the lining in a single pass.

[0042] If possible, an obstacle detour trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory;

[0043] If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel, the maximum arm span of the detection arm, and the fact that the obstacle cannot be moved. The tunnel surface is segmented based on the optimal number of single-trip detections, and the single-trip responsibility area corresponding to each single-trip detection is determined.

[0044] Based on the position of the unmovable obstacles in the one-way responsible area, multiple obstacle detour operation trajectories are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple obstacle detour operation trajectories is determined to generate a preset vehicle trajectory;

[0045] The area determination unit is used to determine the responsible area of ​​each detection arm based on the vehicle's preset trajectory and its corresponding one-way responsible area, combined with the basic detection strategy, to obtain the one-way responsible area of ​​each detection arm.

[0046] Preferably, in a tunnel lining quality inspection system based on a tunnel inspection vehicle using geological radar, the surface fitting planning system further includes:

[0047] The posture adaptive subsystem is used to obtain the real-time running trajectory of the transport engineering vehicle, compare the real-time running trajectory with the vehicle's preset running trajectory, obtain the trajectory difference, and determine the position error of the detection arm base based on the trajectory difference;

[0048] Based on the three-dimensional surface model of the lining, the position coordinates of the next lining detection point of each detection arm are determined respectively. Based on the position difference of the detection arm base and the position coordinates of each detection arm at the next lining detection point, the posture defect of the preset arm span posture is determined, and the detection angle of the detection arm holding the geological radar at the next lining detection point is kept unchanged. Based on the posture defect and the transformation association relationship between the large and small arms of the detection arm, the adjustment strategy of the large and small arms of each detection arm is determined respectively.

[0049] Based on the adjustment strategy, the preset telescopic strategy of the corresponding detection arm is synchronously corrected and updated.

[0050] Preferably, in a tunnel lining quality inspection system based on a tunnel inspection vehicle using geological radar, the surface fitting planning system further includes:

[0051] The bump adaptive subsystem is used to obtain the height of the lowest tilt point when the transport vehicle tilts or the detection arm base sends vibrations. Based on the height of the maximum tilt point and the original height of the transport vehicle chassis, the detection arm base height error is obtained. The detection arm base height error is sent to the attitude adaptive subsystem for adaptive adjustment of the detection arm extension and retraction strategy.

[0052] According to the vibration frequency and vertical acceleration changes of the transport engineering vehicle, the bumpy vibration pattern of the transport engineering vehicle is predicted. Based on the bumpy vibration pattern and combined with the adjustment strategy of the detection arm, the preset telescopic strategy of the detection arm is adaptively corrected.

[0053] The present invention provides a tunnel lining quality detection method, comprising:

[0054] Using a 3D laser scanner to collect contour data of the tunnel lining surface, a 3D surface model of the lining is established, and the 3D surface model of the lining is updated based on the real-time collected contour data;

[0055] The tilt parameters, vibration frequency, and acceleration changes of the transport engineering vehicle are actually collected to generate vehicle operation data. Based on the vehicle operation data, the extension and retraction of the hydraulic suspension of the detection arm base are adaptively adjusted;

[0056] According to the 3D surface model of the lining, the detection trajectory of each detection arm is planned, and the telescopic parameters of the detection arm and the detection angle of the geological radar are adjusted in real time according to the height change of the detection arm base. According to the adjustment results, the detection planning trajectory is adaptively corrected;

[0057] Control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signal.

[0058] Compared with the prior art, the present invention has at least the following beneficial effects:

[0059] The multiple detection arms of the present invention cooperate with the geological radar supporting equipment, so that the geological radar can be flexibly moved on the tunnel lining surface, and the detection arms are carried by the carrying engineering vehicle to move under various road conditions in the tunnel, ensuring that the geological radar can cover the detection areas at different positions and angles, maximizing the integrity of the tunnel lining detection, and greatly reducing the probability of missed detection. In addition, the tunnel lining quality detection system can obtain lining surface data in real time, and based on this, adaptively adjust the fitting curvature of the geological radar and the tunnel lining and the arm height, so that the geological radar can always fit the tunnel lining surface in the best state during the detection process, ensuring the stable transmission and reception of the radar signal, and effectively reducing the signal attenuation or distortion caused by poor fit, thereby improving the accuracy and reliability of the detection of internal defects in the tunnel lining (such as voids, looseness, etc.), and reducing the probability of missed detection and false detection. The present invention uses the collaborative operation of an automated detection arm and a transport engineering vehicle to quickly and continuously inspect tunnel linings, reducing the time consumed by manual adjustments and equipment movement. In addition, the adaptive control function of the tunnel lining quality inspection system eliminates the need for frequent manual intervention in the position and angle of the geological radar, further accelerating the inspection process and significantly improving overall inspection efficiency and accuracy.

[0060] The tunnel lining quality inspection system includes a surface adaptive system, a self-balancing control system, a surface fitting planning system, and the surface adaptive system uses a 3D laser scanner to collect tunnel lining surface contour data, which can quickly and accurately establish a 3D surface model of the lining, and continuously update the model based on real-time collected data, so that the system can grasp the actual shape of the tunnel lining in real time, improve the ability to capture subtle changes and complex structures on the lining surface, and provide an accurate data basis for subsequent inspection work; the self-balancing control system generates vehicle operation data by collecting the tilt parameters, vibration frequency and acceleration changes of the carrying engineering vehicle, and adaptively adjusts the extension and contraction amount of the hydraulic suspension of the inspection arm base accordingly. In complex road conditions in the tunnel, such as unevenness, slope changes, etc., the inspection vehicle can be kept stable through real-time dynamic adjustment to avoid the impact of vehicle shaking on inspection accuracy, and ensure that the geological radar is maintained during the inspection process. Maintain stability, reduce detection errors caused by equipment instability, and ensure the reliability of detection work; the surface fitting planning system plans the detection trajectory of the detection arm according to the three-dimensional surface model of the lining, and adjusts the detection arm telescopic parameters and the geological radar detection angle in real time according to the change of the detection arm base height. At the same time, it adaptively corrects the detection planning trajectory to ensure that the geological radar always keeps a close fit to the tunnel lining surface for detection, effectively improving the detection accuracy. Moreover, real-time adjustment and trajectory correction can adapt to the irregular shape of the tunnel lining and slight deviations during vehicle operation, improve the integrity of the detection, and ensure the validity of the detection data; the radar detection control system controls the geological radar to perform fitting detection along the planned detection trajectory and record the detection signal, realizing the automation and standardization of the detection process, reducing the probability of human operation errors, ensuring the consistency and accuracy of the detection results, and providing a reliable basis for tunnel lining quality assessment. The surface adaptive system, self-balancing control system, surface fitting planning system and radar detection control system of the present invention cooperate with each other to form an organic whole. From data acquisition, vehicle stability control, detection trajectory planning to actual detection execution, each system is closely linked to ensure the efficient and accurate implementation of the detection work, so that the entire detection system has stronger adaptability and detection capabilities in complex tunnel environments, providing strong support for the safe monitoring and maintenance of tunnel projects.

[0061] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0062] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0064] Figure 1 This is the structural diagram of the tunnel lining quality inspection system;

[0065] Figure 2 This is the structural diagram of the surface adaptive system of the tunnel lining quality inspection system;

[0066] Figure 3 This is the structural diagram of the self-balancing control system of the tunnel lining quality inspection system;

[0067] Figure 4 This is the structural diagram of the surface fitting planning system for the tunnel lining quality inspection system. DETAILED DESCRIPTION

[0068] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0069] Example 1:

[0070] The present invention provides a tunnel inspection vehicle based on geological radar, comprising: a plurality of inspection arms and a carrying engineering vehicle, a geological radar and a tunnel lining quality inspection system;

[0071] Among them, the bottom ends of several detection arms are connected to the carrying engineering vehicles respectively, and the top ends are equipped with geological radar supporting equipment to support the geological radar to move on the tunnel lining surface;

[0072] The transport engineering vehicle is used to carry the robotic arm and move it on the road;

[0073] Geological radar, used to detect tunnel lining quality based on radar signals;

[0074] Tunnel lining quality detection system, used to obtain lining surface data in real time. Based on the lining surface data, it can adaptively adjust the fitting curvature between the geological radar and the tunnel lining, as well as the boom height;

[0075] Among them, such as Figure 1 As shown, the tunnel lining quality detection system includes:

[0076] The surface adaptive system is used to collect the contour data of the tunnel lining surface using a 3D laser scanner, establish a 3D surface model of the lining, and update the 3D surface model based on the real-time collected contour data;

[0077] The self-balancing control system is used to actually collect the tilt parameters, vibration frequency and acceleration changes of the transport engineering vehicle, generate vehicle operation data, and adaptively adjust the extension and retraction of the hydraulic suspension of the detection arm base based on the vehicle operation data;

[0078] The surface fitting planning system is used to plan the detection trajectory of each detection arm according to the lining three-dimensional surface model, and to adjust the telescopic parameters of the detection arm and the detection angle of the geological radar in real time according to the height change of the detection arm base. The detection planning trajectory is adaptively corrected according to the adjustment results;

[0079] The radar detection control system is used to control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signals.

[0080] The beneficial effects of the above technical solution are as follows: the multiple detection arms of the present invention cooperate with the geological radar supporting equipment, which enables the geological radar to move flexibly on the tunnel lining surface, and the detection arm is carried by the carrying engineering vehicle to move under various road conditions in the tunnel, ensuring that the geological radar can cover the detection areas at different positions and angles, maximizing the integrity of the tunnel lining detection, greatly reducing the probability of missed detection, and the tunnel lining quality detection system can obtain lining surface data in real time, and based on this, adaptively adjust the fitting curvature of the geological radar and the tunnel lining and the arm height, so that the geological radar can always fit the tunnel lining surface in the best state during the detection process, ensuring the stable transmission and reception of the radar signal, and effectively reducing the signal attenuation or distortion caused by poor fit, thereby improving the accuracy and reliability of the detection of internal defects in the tunnel lining (such as voids, looseness, etc.), and reducing the probability of missed detection and false detection. The present invention uses the collaborative operation of an automated detection arm and a transport engineering vehicle to quickly and continuously inspect tunnel linings, reducing the time consumed by manual adjustments and equipment movement. In addition, the adaptive control function of the tunnel lining quality inspection system eliminates the need for frequent manual intervention in the position and angle of the geological radar, further accelerating the inspection process and significantly improving overall inspection efficiency and accuracy.

[0081] The tunnel lining quality inspection system includes a surface adaptive system, a self-balancing control system, a surface fitting planning system, and the surface adaptive system uses a 3D laser scanner to collect tunnel lining surface contour data, which can quickly and accurately establish a 3D surface model of the lining, and continuously update the model based on real-time collected data, so that the system can grasp the actual shape of the tunnel lining in real time, improve the ability to capture subtle changes and complex structures on the lining surface, and provide an accurate data basis for subsequent inspection work; the self-balancing control system generates vehicle operation data by collecting the tilt parameters, vibration frequency and acceleration changes of the carrying engineering vehicle, and adaptively adjusts the extension and contraction amount of the hydraulic suspension of the inspection arm base accordingly. In complex road conditions in the tunnel, such as unevenness, slope changes, etc., the inspection vehicle can be kept stable through real-time dynamic adjustment to avoid the impact of vehicle shaking on inspection accuracy, and ensure that the geological radar is maintained during the inspection process. Maintain stability, reduce detection errors caused by equipment instability, and ensure the reliability of detection work; the surface fitting planning system plans the detection trajectory of the detection arm according to the three-dimensional surface model of the lining, and adjusts the detection arm telescopic parameters and the geological radar detection angle in real time according to the change of the detection arm base height. At the same time, it adaptively corrects the detection planning trajectory to ensure that the geological radar always keeps a close fit to the tunnel lining surface for detection, effectively improving the detection accuracy. Moreover, real-time adjustment and trajectory correction can adapt to the irregular shape of the tunnel lining and slight deviations during vehicle operation, improve the integrity of the detection, and ensure the validity of the detection data; the radar detection control system controls the geological radar to perform fitting detection along the planned detection trajectory and record the detection signal, realizing the automation and standardization of the detection process, reducing the probability of human operation errors, ensuring the consistency and accuracy of the detection results, and providing a reliable basis for tunnel lining quality assessment. The surface adaptive system, self-balancing control system, surface fitting planning system and radar detection control system of the present invention cooperate with each other to form an organic whole. From data acquisition, vehicle stability control, detection trajectory planning to actual detection execution, each system is closely linked to ensure the efficient and accurate implementation of the detection work, so that the entire detection system has stronger adaptability and detection capabilities in complex tunnel environments, providing strong support for the safe monitoring and maintenance of tunnel projects.

[0082] Example 2:

[0083] Based on Example 1, the surface adaptive system, such as Figure 2 Shown, including:

[0084] A contour data acquisition module is used to collect contour data of the tunnel lining surface based on a three-dimensional laser scanner arranged in front of the transport engineering vehicle;

[0085] A three-dimensional model building module is used to adjust the parameters of the preset lining contour model based on the contour data to obtain a three-dimensional surface model of the lining;

[0086] The real-time update module is used to obtain real-time contour data according to the movement of the transport engineering vehicle, and dynamically update the lining three-dimensional surface model based on the real-time contour data.

[0087] In this embodiment, the contour data is the geometric shape and spatial position information of the tunnel lining surface collected by a three-dimensional laser scanner.

[0088] In this embodiment, the preset lining contour model refers to a standard idealized tunnel lining model designed before pouring the tunnel lining.

[0089] The beneficial effects of the above technical solution are as follows: the present invention uses a 3D laser scanner installed in front of a transport engineering vehicle to collect tunnel lining surface contour data, which provides a reliable data basis for subsequent model construction and detection work; thereafter, based on the collected contour data, the parameters of the preset lining contour model are adjusted to obtain a 3D surface model of the lining, fully considering the actual shape and size changes of the tunnel lining, so that the constructed 3D surface model is more consistent with the real shape of the tunnel lining, avoiding the detection deviation caused by the discrepancy between the model and the actual lining, and providing a more accurate reference for subsequent detection trajectory planning, detection equipment adjustment and other work It helps to improve the reliability and effectiveness of the detection results. During the tunnel detection process, the shape of the tunnel lining may change irregularly due to geological conditions, construction factors, etc. The movement of the vehicle will also cause changes in the detection angle and position. By updating the model in real time, the system can promptly reflect the latest status of the tunnel lining, ensuring that the detection process is always based on an accurate model. For example, when encountering local bulges or depressions in the tunnel lining, the dynamically updated model allows the detection equipment to adjust the detection angle and position in time to avoid missed detection or false detection, greatly improving the detection system's adaptability to complex tunnel environments and the comprehensiveness of detection.

[0090] Example 3:

[0091] On the basis of Example 1, the self-balancing control system, such as Figure 3 Shown, including:

[0092] The vehicle data acquisition module is used to collect chassis tilt parameters, vibration frequency, and acceleration changes of engineering vehicles during tunnel lining quality inspection, and generate vehicle operation data after pre-processing.

[0093] The intelligent adaptive analysis module is used to determine the tilt angle and tilt direction of the detection arm based on the chassis tilt parameters, and the tilt height of each point on the detection arm base in combination with the fixed position of the detection arm on the transport engineering vehicle;

[0094] Determine the highest tilt point and the lowest tilt point on the detection arm base in the tilt direction, obtain a tilt height difference, and perform compression adjustment on the hydraulic support device on the side of the highest tilt point based on the tilt height difference;

[0095] The tilt height at the lowest tilt point is sent to the surface fitting control system.

[0096] The beneficial effects of the above technical solution: The present invention collects and pre-processes the chassis tilt parameters, vibration frequency and acceleration changes of the transport engineering vehicle through the vehicle data acquisition module to generate vehicle operation data. Through multi-dimensional data acquisition, it can comprehensively capture the dynamic state of the vehicle during the tunnel detection process, providing a solid data foundation for the stable operation of the entire detection system. Then, through the intelligent adaptive analysis module, based on the chassis tilt parameters and combined with the fixed position of the detection arm on the transport engineering vehicle, the tilt angle, direction and tilt height of each point of the base of the detection arm can be accurately determined. The state of the vehicle chassis can be quickly and accurately converted into the specific posture parameters of the detection arm, providing a key basis for the subsequent adjustment of the detection arm position and ensuring the fit between the geological radar and the tunnel lining surface, effectively improving the intelligence level and accuracy of the posture adjustment of the detection equipment; finally, by determining the highest and lowest tilt points on the base of the detection arm, calculating the tilt height difference, and compressing and adjusting the hydraulic support device on the side of the highest tilt point, the tilt state of the detection arm is quickly balanced. When the vehicle is driving on bumpy roads or complex terrain in tunnels, the mechanism can respond to the tilt changes of the chassis in time, reduce the offset of the detection arm caused by vehicle shaking, and ensure that the geological radar carried by the detection arm remains stable, thereby improving the stability and reliability of the geological radar detection signal and reducing the risk of detection errors and data distortion caused by equipment shaking.

[0097] Example 4:

[0098] Based on Example 1, the surface fitting planning system, such as Figure 4 As shown, including:

[0099] The vehicle path planning subsystem is used to determine the geometric parameters of the tunnel based on the 3D surface model of the lining, and generate a preset vehicle trajectory based on the tunnel's operating data and the maximum arm span of the detection arm;

[0100] Radar inspection movement planning subsystem, used to determine the basic inspection strategy for the current lining inspection based on geometric parameters and vehicle preset running trajectory;

[0101] According to the basic detection strategy and the preset running trajectory of the vehicle, the moving speed and trajectory of each geological radar are determined to obtain the detection planning trajectory;

[0102] The telescopic strategy planning subsystem is used to determine the initial detection position based on the detection planning trajectory, obtain the detection angle corresponding to the initial detection position, and determine the detection angle change of each geological radar on its corresponding detection planning path in combination with the lining three-dimensional surface model and radar antenna position data;

[0103] determining an angle change of the detection arm forearm based on the detected angle change;

[0104] According to the transformation correlation relationship between the large and small arms of the detection arm and the angle transformation of the small arm of the detection arm, combined with the height change data on the radar detection planning path corresponding to each detection arm, the preset extension and retraction strategy of the detection arm corresponding to each radar antenna is determined respectively.

[0105] In this embodiment, the geometric parameters refer to the curvature radius, height, width, etc. of the tunnel.

[0106] In this embodiment, the operational data includes whether the tunnel is currently under construction, whether it has been opened to traffic, and the actual traffic status.

[0107] In this embodiment, the basic detection strategy refers to the areas that several detection arms on the detection vehicle are responsible for during the detection process, determined based on geometric parameters and the preset operating trajectory of the vehicle. For example: when the detection vehicle has five detection arms and the preset operating trajectory is a straight line in the middle of the road, one of the five detection arms is responsible for detecting the semi-circular arc part of the arch, two are responsible for detecting the lower half of the side walls, and the remaining two are responsible for detecting the remaining arch waist part.

[0108] The beneficial effects of the above technical solution: the present invention generates a preset vehicle running trajectory based on the lining three-dimensional surface model, tunnel operation data and the maximum arm span of the detection arm through the vehicle path planning subsystem, avoids the conflict between the detection path and the tunnel facilities, and ensures that the detection arm can cover the entire area, greatly improving the scientificity and integrity of the detection vehicle path planning, reducing invalid mileage, and effectively detecting efficiency; the radar detection movement planning subsystem first determines the basic detection strategy based on geometric parameters and preset trajectory, and then refines the moving speed and trajectory of each geological radar, thereby realizing the dynamic allocation of detection resources; the telescopic strategy planning subsystem accurately determines the detection planning trajectory and the lining surface model according to the detection planning trajectory. Accurately calculate the detection angle changes of the geological radar at different positions and the angle changes of the detection arm and small arm. By matching the curvature of the tunnel surface (such as arch and variable cross-section sections) in real time, ensure that the radar antenna always transmits signals at the optimal incident angle, avoid signal attenuation or reflection interference caused by angle deviation, and effectively improve the consistency of geological radar detection depth. Combined with the linkage relationship between the large and small arms of the detection arm, the path height change and the radar antenna position data, the system dynamically generates a preset extension and retraction strategy for the detection arm, realizing automatic adjustment of the detection arm posture during vehicle driving to compensate for road bumps or undulations of the tunnel surface, ensuring that the radar antenna and the lining surface always remain in contact, and effectively reducing the probability of missed detection and object detection.

[0109] Example 5:

[0110] Based on Example 4, the radar detection movement planning subsystem further includes:

[0111] Radar movement parameter planning unit, used to predict the position change of the detection arm base based on the preset vehicle trajectory;

[0112] According to the position change of the detection arm base, the relative position relationship between each detection arm and its corresponding one-way responsibility area is determined, and based on the relative position relationship, the movement trajectory of each geological radar is determined respectively;

[0113] According to the length of a single detection moving trajectory on the one-way responsibility area of ​​the detection arm corresponding to each geological radar, based on the single-round detection consistent completion rule and combined with the minimum holding time of the geological radar, the moving speed of each geological radar is calculated to determine the corresponding moving speed of each geological radar;

[0114] Based on the moving speed and trajectory of each geological radar, the corresponding detection planning trajectory is generated.

[0115] In this embodiment, the single-round detection consistent completion rule refers to the principle that each detection arm starts detecting its corresponding responsible area at the same time and completes the detection at the same time during the moving detection process of the detection vehicle.

[0116] In this embodiment, the one-way responsible area refers to the lining area that each detection arm is responsible for detecting during a one-way detection process.

[0117] In this embodiment, the minimum holding time of the geological radar refers to the shortest time that the geological radar needs to maintain its position unchanged at the detected position when the geological radar is used to detect the lining surface.

[0118] The beneficial effects of the above technical solution are as follows: the present invention predicts the position change of the detection arm base based on the preset trajectory of the vehicle through the radar movement parameter planning unit, and determines the relative position relationship between each detection arm and its corresponding one-way responsibility area according to the position change of the detection arm base, and then determines the movement trajectory of the geological radar, so that the movement of the geological radar is more in line with the actual situation of the tunnel lining, which can effectively improve the rationality of the detection trajectory. For example, in areas where the tunnel lining surface is uneven or there are special structures, the detection arm can flexibly adjust the movement trajectory according to the relative position relationship, ensuring that the geological radar can accurately detect various parts of the lining, thereby improving the adaptability and effectiveness of the detection trajectory; Then, the moving speed of the geological radar is calculated based on the length of the single detection moving trajectory in the one-way responsibility area and the minimum holding time of the geological radar. This fully considers the actual needs of the detection task and the working characteristics of the geological radar, and can enable the geological radar to move at an appropriate speed, effectively avoiding incomplete data collection due to too fast speed or affecting the detection efficiency due to too slow speed. At the same time, the detection planning trajectory is generated based on the moving speed and moving trajectory of the geological radar, which can organically combine the detection speed and trajectory to form an efficient detection plan, provide clear guidance for the lining quality detection process, effectively avoid invalid movement and repeated detection of the geological radar, and improve detection efficiency.

[0119] Example 6:

[0120] Based on Example 4, the vehicle path planning subsystem includes:

[0121] A real-time determination module is used to determine whether the tunnel lining is not completed based on the tunnel's operational data;

[0122] If the tunnel lining is completed, the geometric parameters of the tunnel are determined based on the 3D surface model of the lining. Combined with the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full surface inspection of the lining in a single pass.

[0123] If possible, a straight running trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory;

[0124] If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel and the maximum arm span of the detection arm. The tunnel surface is segmented based on the optimal number of single-trip detections to determine the single-trip responsibility area corresponding to each single-trip detection.

[0125] Based on the regional center line of the one-way responsible area, multiple straight-line running tracks are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple straight-line running tracks is determined to generate a preset vehicle track;

[0126] If the tunnel lining is not completed, obstacle data is collected inside the tunnel. Based on this obstacle data and the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full curved surface inspection of the lining in a single pass.

[0127] If possible, an obstacle detour trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory;

[0128] If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel, the maximum arm span of the detection arm, and the fact that the obstacle cannot be moved. The tunnel surface is segmented based on the optimal number of single-trip detections, and the single-trip responsibility area corresponding to each single-trip detection is determined.

[0129] Based on the position of the unmovable obstacles in the one-way responsible area, multiple obstacle detour operation trajectories are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple obstacle detour operation trajectories is determined to generate a preset vehicle trajectory;

[0130] The area determination unit is used to determine the responsible area of ​​each detection arm based on the vehicle's preset trajectory and its corresponding one-way responsible area, combined with the basic detection strategy, to obtain the one-way responsible area of ​​each detection arm.

[0131] In this embodiment, a one-way trip is a round trip from the inspection starting point to the end point and then from the inspection end point back to the starting point, wherein both the trip from the inspection starting point to the end point and the trip from the inspection end point back to the starting point are a one-way trip. The inspection starting point and the inspection end point may be the two entrances of the tunnel or not.

[0132] In this embodiment, full-surface detection refers to completing the detection of the entire lining surface in one go.

[0133] The beneficial effects of the above technical solution are as follows: The present invention adopts different inspection planning strategies depending on whether the tunnel is completed. For completed tunnels, it determines whether the entire curved surface can be inspected in a single pass. If not, it determines the optimal number of single passes and segments the tunnel surface. For unfinished tunnels, the vehicle trajectory is planned based on obstacle data, maximizing coverage of the tunnel lining surface, ensuring comprehensiveness and accuracy of inspection and avoiding omissions of important areas. The vehicle's preset trajectory and round-trip sequence are rationally determined based on information such as the tunnel's geometric parameters, the maximum arm span of the inspection arm, and obstacle data. For example, for tunnels that can complete inspections in a single trip, a straight running trajectory is directly generated; for tunnels that require multiple inspections, the responsible area and running trajectory of each single trip are scientifically planned, which can avoid invalid driving and repeated inspections of the inspection vehicle, reduce unnecessary trips, improve inspection efficiency, and save inspection time and costs; when the tunnel lining is not completed and there are obstacles, obstacle data can be collected and the obstacle detour running trajectory can be planned accordingly to ensure that the inspection vehicle can adapt to the complex working conditions in the tunnel, avoid obstacles, and ensure the smooth progress of the inspection work, thereby enhancing the adaptability of the inspection system to different tunnel environments. The area determination unit is based on the vehicle's preset trajectory and one-way responsible area, combined with the basic inspection strategy to determine the responsible area of ​​each inspection arm, which helps to reasonably allocate the inspection tasks of each inspection arm, so that each inspection arm can efficiently complete the inspection work in its responsible area, effectively improving the coordination and overall efficiency of the inspection work.

[0134] Example 7:

[0135] Based on Example 4, the surface fitting planning system further includes:

[0136] The posture adaptive subsystem is used to obtain the real-time running trajectory of the transport engineering vehicle, compare the real-time running trajectory with the vehicle's preset running trajectory, obtain the trajectory difference, and determine the position error of the detection arm base based on the trajectory difference;

[0137] Based on the three-dimensional surface model of the lining, the position coordinates of the next lining detection point of each detection arm are determined respectively. Based on the position difference of the detection arm base and the position coordinates of each detection arm at the next lining detection point, the posture defect of the preset arm span posture is determined, and the detection angle of the detection arm holding the geological radar at the next lining detection point is kept unchanged. Based on the posture defect and the transformation association relationship between the large and small arms of the detection arm, the adjustment strategy of the large and small arms of each detection arm is determined respectively.

[0138] Based on the adjustment strategy, the preset telescopic strategy of the corresponding detection arm is synchronously corrected and updated.

[0139] In this embodiment, the preset arm extension posture refers to the extension posture of each detection arm at the next lining detection point according to the preset running trajectory of the vehicle.

[0140] In this embodiment, the transformation association relationship between the upper and lower arms refers to the coordination association relationship between the upper and lower arms of the detection arm during the extension and retraction process.

[0141] The beneficial effects of the above technical solution: The present invention obtains the running trajectory of the transport engineering vehicle in real time and compares it with the preset trajectory, which can quickly and accurately determine the position error of the detection arm base, provide a basis for timely adjustment of the detection position of the detection arm, effectively reduce the detection error caused by vehicle driving deviation, and improve the accuracy and reliability of detection. For example, when driving in a tunnel, a vehicle may deviate from the preset trajectory due to factors such as uneven road surface and curves. The posture adaptive subsystem can detect and correct such deviations in a timely manner to ensure the smooth progress of the detection work. Subsequently, the position coordinates of the next lining detection point are determined based on the lining three-dimensional surface model, and combined with the position difference of the detection arm base, the posture defect of the preset arm span posture can be accurately determined. Then, based on the posture defect and the transformation correlation relationship between the large and small arms of the detection arm, the adjustment strategy of the large and small arms is determined. While keeping the geological radar detection angle unchanged, the arm span posture is adjusted so that the detection arm can accurately reach the next detection point and maintain the optimal detection posture, effectively ensuring that the geological radar and the lining surface are always in contact during the re-detection process, so that the geological radar can accurately obtain the lining detection data, and based on the adjustment strategy, the preset telescopic strategy is synchronously corrected and updated to ensure that when the detection arm adjusts its posture, its telescopic action can also match the posture adjustment, ensuring the coordinated and consistent movement of the detection arm and effectively improving the overall performance of the detection arm.

[0142] Example 8:

[0143] Based on Example 7, the surface fitting planning system further includes:

[0144] The bump adaptive subsystem is used to obtain the height of the lowest tilt point when the transport vehicle tilts or the detection arm base sends vibrations. Based on the height of the maximum tilt point and the original height of the transport vehicle chassis, the detection arm base height error is obtained. The detection arm base height error is sent to the attitude adaptive subsystem for adaptive adjustment of the detection arm extension and retraction strategy.

[0145] According to the vibration frequency and vertical acceleration changes of the transport engineering vehicle, the bumpy vibration pattern of the transport engineering vehicle is predicted. Based on the bumpy vibration pattern and combined with the adjustment strategy of the detection arm, the preset telescopic strategy of the detection arm is adaptively corrected.

[0146] The beneficial effects of the above technical solution are as follows: When the transport vehicle tilts or the detection arm base shakes, the present invention's bump adaptive subsystem can promptly obtain the height of the lowest tilt point, calculate the detection arm base height error, and send this error to the posture adaptive subsystem for adjustment of the telescopic strategy. This effectively reduces the shaking of the detection arm caused by vehicle bumps, ensuring that the detection equipment remains stable under complex road conditions, and effectively improving the accuracy and reliability of detection data. Then, based on the vibration frequency and vertical acceleration changes of the transport vehicle, the vehicle's pitch and vibration patterns are predicted. Combined with the detection arm's adjustment strategy, the preset telescopic strategy is adaptively modified, allowing the detection arm to better adapt to vehicle pitch and vibration. When the detection vehicle traverses bumpy roads, the detection arm can dynamically adjust its telescopic range to maintain a stable detection posture. For example, in tunnel construction sections or areas with undulating roads, the detection arm can make real-time adjustments based on the pitch and vibration patterns, ensuring that detection work is not affected by road conditions. This effectively improves the adaptability and efficiency of the detection system under complex road conditions, providing a more reliable basis for tunnel maintenance and management.

[0147] Example 9:

[0148] The present invention provides a tunnel lining quality detection method, comprising:

[0149] Using a 3D laser scanner to collect contour data of the tunnel lining surface, a 3D surface model of the lining is established, and the 3D surface model of the lining is updated based on the real-time collected contour data;

[0150] The tilt parameters, vibration frequency, and acceleration changes of the transport engineering vehicle are actually collected to generate vehicle operation data. Based on the vehicle operation data, the extension and retraction of the hydraulic suspension of the detection arm base are adaptively adjusted;

[0151] According to the 3D surface model of the lining, the detection trajectory of each detection arm is planned, and the telescopic parameters of the detection arm and the detection angle of the geological radar are adjusted in real time according to the height change of the detection arm base. According to the adjustment results, the detection planning trajectory is adaptively corrected;

[0152] Control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signal.

[0153] The beneficial effects of the above technical solution are as follows: the present invention first uses a 3D laser scanner to collect the surface contour data of the tunnel lining, which can quickly and accurately establish a 3D surface model of the lining, and continuously update the model based on the real-time collected data, so that the system can grasp the actual shape of the tunnel lining in real time, improve the ability to capture subtle changes and complex structures on the lining surface, and provide an accurate data basis for subsequent detection work; then, the vehicle operation data is generated by collecting the tilt parameters, vibration frequency and acceleration changes of the carrying engineering vehicle, and the extension and contraction amount of the hydraulic suspension of the detection arm base is adaptively adjusted accordingly. In the case of complex road surfaces in the tunnel, such as unevenness, slope changes, etc., the detection vehicle can be kept stable through real-time dynamic adjustment to avoid the impact of vehicle shaking on detection accuracy, ensure that the geological radar remains stable during the detection process, and reduce the risk of equipment instability. The detection error is minimized to ensure the reliability of the detection work; then the detection trajectory of the detection arm is planned according to the three-dimensional curved surface model of the lining, and the detection arm telescopic parameters and the geological radar detection angle are adjusted in real time according to the change of the detection arm base height. At the same time, the detection planning trajectory is adaptively corrected to ensure that the geological radar always keeps a close fit to the tunnel lining surface for detection, effectively improving the detection accuracy. Moreover, real-time adjustment and trajectory correction can adapt to the irregular shape of the tunnel lining and slight deviations during vehicle operation, improve the integrity of the detection, and ensure the validity of the detection data; finally, the geological radar is controlled to perform fit detection along the planned detection trajectory and record the detection signal, realizing the automation and standardization of the detection process, reducing the probability of human operation errors, ensuring the consistency and accuracy of the detection results, and providing a reliable basis for tunnel lining quality assessment.

[0154] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A tunnel lining quality inspection system based on a tunnel inspection vehicle using geological radar, characterized in that: include: The surface adaptive system is used to collect the contour data of the tunnel lining surface using a 3D laser scanner, establish a 3D surface model of the lining, and update the 3D surface model based on the real-time collected contour data; The self-balancing control system is used to actually collect the tilt parameters, vibration frequency and acceleration changes of the transport engineering vehicle, generate vehicle operation data, and adaptively adjust the extension and retraction of the hydraulic suspension of the detection arm base based on the vehicle operation data; The surface fitting planning system is used to plan the detection trajectory of each detection arm according to the lining three-dimensional surface model, and to adjust the telescopic parameters of the detection arm and the detection angle of the geological radar in real time according to the height change of the detection arm base. The detection planning trajectory is adaptively corrected according to the adjustment results; Radar detection control system, used to control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signals; Among them, the tunnel inspection vehicle based on geological radar includes: several inspection arms and carrying engineering vehicles, multiple geological radars and tunnel lining quality inspection system; Among them, the bottom ends of several detection arms are connected to the carrying engineering vehicles respectively, and the top ends are equipped with geological radar supporting equipment to support the geological radar to move on the tunnel lining surface; The transport engineering vehicle is used to carry the robotic arm and move it on the road; Multiple geological radars for detecting tunnel lining quality based on radar signals; The tunnel lining quality inspection system is used to obtain real-time lining surface data and the trajectory data of the carrying engineering vehicle. Based on the lining surface data and trajectory data, the telescopic parameters of the inspection arm and the supporting angle of the geological radar are adaptively controlled.

2. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 1 is characterized in that: Surface adaptive system, including: A contour data acquisition module is used to collect contour data of the tunnel lining surface based on a three-dimensional laser scanner arranged in front of the transport engineering vehicle; A three-dimensional model building module is used to adjust the parameters of the preset lining contour model based on the contour data to obtain a three-dimensional surface model of the lining; The real-time update module is used to obtain real-time contour data according to the movement of the transport engineering vehicle, and dynamically update the lining three-dimensional surface model based on the real-time contour data.

3. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 1 is characterized in that: Self-balancing control system, including: The vehicle data acquisition module is used to collect chassis tilt parameters, vibration frequency, and acceleration changes of engineering vehicles during tunnel lining quality inspection, and generate vehicle operation data after pre-processing. The intelligent adaptive analysis module is used to determine the tilt angle and tilt direction of the detection arm based on the chassis tilt parameters, and the tilt height of each point on the detection arm base in combination with the fixed position of the detection arm on the transport engineering vehicle; Determine the highest tilt point and the lowest tilt point on the detection arm base in the tilt direction, obtain a tilt height difference, and perform compression adjustment on the hydraulic support device on the side of the highest tilt point based on the tilt height difference; The tilt height at the lowest tilt point is sent to the surface fitting planning system.

4. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 1 is characterized in that: Surface fitting planning system, including: The vehicle path planning subsystem is used to determine the geometric parameters of the tunnel based on the 3D surface model of the lining, and generate a preset vehicle trajectory based on the tunnel's operating data and the maximum arm span of the detection arm; Radar inspection movement planning subsystem, used to determine the basic inspection strategy for the current lining inspection based on geometric parameters and vehicle preset running trajectory; According to the basic detection strategy and the preset running trajectory of the vehicle, the moving speed and trajectory of each geological radar are determined to obtain the detection planning trajectory; The telescopic strategy planning subsystem is used to determine the initial detection position based on the detection planning trajectory, obtain the detection angle corresponding to the initial detection position, and determine the detection angle change of each geological radar on its corresponding detection planning path in combination with the lining three-dimensional surface model and radar antenna position data; determining an angle change of the detection arm forearm based on the detected angle change; According to the transformation correlation relationship between the large and small arms of the detection arm and the angle transformation of the small arm of the detection arm, combined with the height change data on the radar detection planning path corresponding to each detection arm, the preset extension and retraction strategy of the detection arm corresponding to each radar antenna is determined respectively.

5. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 4 is characterized in that: The radar detection movement planning subsystem also includes: Radar movement parameter planning unit, used to predict the position change of the detection arm base based on the preset vehicle trajectory; According to the position change of the detection arm base, the relative position relationship between each detection arm and its corresponding one-way responsibility area is determined, and based on the relative position relationship, the movement trajectory of each geological radar is determined respectively; According to the length of a single detection moving trajectory on the one-way responsibility area of ​​the detection arm corresponding to each geological radar, based on the single-round detection consistent completion rule and combined with the minimum holding time of the geological radar, the moving speed of each geological radar is calculated to determine the corresponding moving speed of each geological radar; Based on the moving speed and trajectory of each geological radar, the corresponding detection planning trajectory is generated.

6. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 4 is characterized in that: Vehicle path planning subsystem, including: A real-time determination module is used to determine whether the tunnel lining is not completed based on the tunnel's operational data; If the tunnel lining is completed, the geometric parameters of the tunnel are determined based on the 3D surface model of the lining. Combined with the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full surface inspection of the lining in a single pass. If possible, a straight running trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory; If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel and the maximum arm span of the detection arm. The tunnel surface is segmented based on the optimal number of single-trip detections to determine the single-trip responsibility area corresponding to each single-trip detection. Based on the regional center line of the one-way responsible area, multiple straight-line running tracks are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple straight-line running tracks is determined to generate a preset vehicle track; If the tunnel lining is not completed, obstacle data is collected inside the tunnel. Based on this obstacle data and the maximum arm span of the inspection arm, it is determined whether the inspection vehicle can complete the full curved surface inspection of the lining in a single pass. If possible, an obstacle detour trajectory is generated based on the middle position of the tunnel as the vehicle preset trajectory; If not, the optimal number of single-trip detections is determined based on the geometric parameters of the tunnel, the maximum arm span of the detection arm, and the fact that the obstacle cannot be moved. The tunnel surface is segmented based on the optimal number of single-trip detections, and the single-trip responsibility area corresponding to each single-trip detection is determined. Based on the position of the unmovable obstacles in the one-way responsible area, multiple obstacle detour operation trajectories are generated. Based on the starting position of the inspection vehicle, the round-trip order of the multiple obstacle detour operation trajectories is determined to generate a preset vehicle trajectory; The area determination unit is used to determine the responsible area of ​​each detection arm based on the vehicle's preset trajectory and its corresponding one-way responsible area, combined with the basic detection strategy, to obtain the one-way responsible area of ​​each detection arm.

7. The tunnel lining quality inspection system based on a tunnel inspection vehicle using geological radar according to claim 4, characterized in that: The surface fitting planning system also includes: The posture adaptive subsystem is used to obtain the real-time running trajectory of the transport engineering vehicle, compare the real-time running trajectory with the vehicle's preset running trajectory, obtain the trajectory difference, and determine the position error of the detection arm base based on the trajectory difference; Based on the three-dimensional surface model of the lining, the position coordinates of the next lining detection point of each detection arm are determined respectively. Based on the position difference of the detection arm base and the position coordinates of each detection arm at the next lining detection point, the posture defect of the preset arm span posture is determined, and the detection angle of the detection arm holding the geological radar at the next lining detection point is kept unchanged. Based on the posture defect and the transformation association relationship between the large and small arms of the detection arm, the adjustment strategy of the large and small arms of each detection arm is determined respectively. Based on the adjustment strategy, the preset telescopic strategy of the corresponding detection arm is synchronously corrected and updated.

8. The tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to claim 7, characterized in that: The surface fitting planning system also includes: The bump adaptive subsystem is used to obtain the height of the lowest tilt point when the transport vehicle tilts or the detection arm base sends vibrations. Based on the height of the maximum tilt point and the original height of the transport vehicle chassis, the detection arm base height error is obtained. The detection arm base height error is sent to the attitude adaptive subsystem for adaptive adjustment of the detection arm extension and retraction strategy. According to the vibration frequency and vertical acceleration changes of the transport engineering vehicle, the bumpy vibration pattern of the transport engineering vehicle is predicted. Based on the bumpy vibration pattern and combined with the adjustment strategy of the detection arm, the preset telescopic strategy of the detection arm is adaptively corrected.

9. A tunnel lining quality inspection method, applied to a tunnel lining quality inspection system of a tunnel inspection vehicle based on geological radar according to any one of claims 1 to 8, characterized in that: include: Using a 3D laser scanner to collect contour data of the tunnel lining surface, a 3D surface model of the lining is established, and the 3D surface model of the lining is updated based on the real-time collected contour data; The tilt parameters, vibration frequency, and acceleration changes of the transport engineering vehicle are actually collected to generate vehicle operation data. Based on the vehicle operation data, the extension and retraction of the hydraulic suspension of the detection arm base are adaptively adjusted; According to the 3D surface model of the lining, the detection trajectory of each detection arm is planned, and the telescopic parameters of the detection arm and the detection angle of the geological radar are adjusted in real time according to the height change of the detection arm base. According to the adjustment results, the detection planning trajectory is adaptively corrected; Control the geological radar to perform lining fit detection along its corresponding detection planning trajectory and record the corresponding geological radar detection signal.

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