A hanging rail type tunnel intelligent inspection robot

Abstract

This invention relates to a track-mounted intelligent tunnel inspection robot. It primarily addresses the technical problems of existing inspection equipment, such as low speed, poor positioning accuracy, and relatively limited functionality. The intelligent inspection robot consists of five main parts: the robot body, the robot inspection chamber, the robot auxiliary system, the robot data processing system, and the robot management platform. The robot body includes the robot body, control system, positioning system, power system, and communication system. The robot inspection chamber includes the inspection chamber body, inspection equipment, and backup battery. The robot auxiliary system includes the track, track support brackets, wireless network system, RFID positioning system, and wireless charging system. The robot data processing system includes a front-end data processing system and a back-end data processing system. The robot management platform is used for remote digital management of the data collected and analyzed by the inspection robot.

Description

Technical Field

[0001] This invention relates to an inspection robot, and in particular discloses a rail-mounted intelligent tunnel inspection robot for highways, subways, municipal tunnels, etc., which is applied to the field of underground infrastructure inspection. Background Technology

[0002] With the development of technologies such as motion control, machine vision, environmental perception, and structural inspection, we have integrated and developed intelligent inspection robots equipped with high-precision equipment such as machine vision, infrared thermal imaging, and laser scanning to promptly detect foreign objects, fires, structural defects, etc. in tunnels, thus safeguarding the operational safety of tunnels.

[0003] Currently, there are intelligent inspection robots on the market, but their functions are limited and their accuracy is low, making it difficult to achieve real-time and rapid detection of multiple defects in tunnels. Patent CN201610578468.8 discloses an intelligent inspection robot for power tunnels, including its track-walking mechanism, bottom-mounted chassis, communication system, smoke detector, and wireless transceiver system, enabling automatic fire alarm, video and environmental monitoring of the entire tunnel, and its supporting communication facilities. Patent CN202111525635.X discloses an intelligent inspection robot for highway tunnels and its control system, including load-bearing components and transmission components, capable of simple video recording and querying for illegally parked vehicles. Patent CN201420557938.9 discloses an intelligent tunnel inspection robot, including an external information acquisition system, power and transmission system, shell, and lithium battery, capable of reporting the concentration of harmful gases in the tunnel and promptly detecting hidden fires. However, none of these can detect tunnel structural defects, and their detection speed is slow and their functions are relatively limited, making it difficult to meet the needs of daily and periodic inspections of tunnel structures and environments.

[0004] In summary, there is an urgent need for a tunnel intelligent inspection robot with high inspection speed, accurate positioning, diverse functions, and high protection level. Summary of the Invention

[0005] The purpose of this invention is to design a rail-mounted intelligent tunnel inspection robot, which mainly solves the technical problems of existing inspection equipment such as low speed, poor positioning accuracy, and relatively limited functions.

[0006] The objective of this invention can be achieved through the following technical solution: a track-mounted intelligent tunnel inspection robot, comprising five main parts: robot body, robot inspection chamber, robot auxiliary system, robot data processing system, and robot management platform; the robot body includes a robot body, control system, positioning system, power system, and communication system; the robot body is the supporting structure for the control system, positioning system, power system, and communication system; the positioning system transmits position signals to the control system via data lines; the communication system interacts with the control system via a router; the control system can integrate and control the positioning system, power system, and communication system; the power system provides power to the control system, positioning system, and communication system; the robot inspection chamber includes an inspection chamber body, inspection equipment, and a backup battery; the robot auxiliary system includes a track, track suspension brackets, wireless network system, RFID positioning system, and wireless charging system; the robot data processing system includes a front-end data processing system and a back-end data processing system; the robot management platform is used for remote digital management of the data collected and analysis results of the inspection robot.

[0007] The robot inspection chamber is connected to the robot body via a transfer mechanism, which connects mechanical, communication, and electrical components. Both the robot body and the inspection chamber are suspended from the track by two pairs of load-bearing wheels, ensuring stable operation. The robot body's built-in battery is charged via a wireless charging system on the track and communicates with the outside world via a wireless network. The robot's auxiliary system is mounted on the tunnel structure via a bracket, including an RFID positioning system and a wireless charging system mounted on the track. A wireless access point (AP) is used to establish a network communication system for the robot within the tunnel. Data collected by the robot body is analyzed by a robot data processing system and interfaces with the robot management platform via a wireless network, allowing it to receive task instructions from the platform.

[0008] The robot body includes a load-bearing structural base plate, which is suspended on the track by two pairs of four load-bearing wheels. The lateral spacing between each pair of load-bearing wheels is less than one-third of the track width, which ensures that the robot will not slide off the track. The load-bearing wheels are made of high-elastic PU material, and their bearings are professional high-speed sliding bearings, which can meet the requirements of high speed, no noise, wear resistance, and no axle bursting.

[0009] Furthermore, a guide wheel is installed on the side below each load-bearing wheel. The guide wheel slides along the bottom side of the track to guide the robot to run smoothly on the track and further ensure that the robot will not slide off the track.

[0010] Furthermore, a load-bearing wheel is selected as the ranging wheel, and the selected load-bearing wheel is connected to the encoder support. The encoder support has a built-in encoder for measuring the robot's travel distance. Furthermore, the four load-bearing wheels are connected by a square steel plate, which serves as the main structure supporting the robot. The main structure is made of aluminum alloy. A device pod is fixed to the bottom of the square steel plate with bolts. The device pod houses the battery, PLC, microcomputer, router, and other equipment. The device pod is made of aluminum alloy block laser-cut into one piece and equipped with heat sinks. The cable communication interface uses aviation waterproof connectors to ensure that the device pod's protection level reaches IP65.

[0011] The control system of the robot body includes a micro industrial computer and a PLC. The micro industrial computer is used to process various instructions, and the PLC is used to integrate and control various devices and communicate with the micro industrial computer via protocol.

[0012] Furthermore, the robot's control system also includes a motion control system, which comprises a control unit, a drive unit, an execution unit, and a position feedback loop. The motion control execution process is as follows:

[0013] (1) After receiving the motion command, the PLC sends the desired position value to the control unit;

[0014] (2) After receiving the instruction, the control unit sends a drive instruction to the drive unit, and the drive unit receives the instruction and transmits it to the execution unit;

[0015] (3) The execution unit performs the task and sends the location information back to the control unit;

[0016] (4) The control unit determines the deviation between the execution position and the desired position, and issues a correction command based on the analysis. Steps (1), (2), (3), and (4) are repeated until the robot moves precisely to the desired position.

[0017] Furthermore, the control unit mainly includes positioning algorithms, reset algorithms, S-shaped acceleration / deceleration algorithms, and interpolation algorithms, etc.

[0018] The further drive unit mainly includes a servo driver and two drive wheels. The servo driver is installed in the equipment pod, and the two drive wheels are clamped on both sides of the track cross section. The drive wheel shafts are fixed to square steel plates. Each pair of drive wheels is connected by an elastic link to adjust the clamping force of the drive wheels. The rotation of the drive wheels drives the robot to travel in a straight line along the track at a speed greater than 3.5 meters per second and a braking distance of less than 0.5 meters.

[0019] The robot's positioning system includes a ranging wheel, RFID, LiDAR, and an image feature recognition module. The ranging wheel is used for coarse positioning, while the RFID and image feature recognition module are used to correct long-distance measurement errors. The LiDAR is used for obstacle avoidance, ensuring centimeter-level absolute accuracy over long distances and millimeter-level positioning for important local locations.

[0020] Furthermore, RFID tags can be deployed at intervals of 20 to 50 meters, depending on the actual linearity of the tunnel.

[0021] The power system of the robot body includes a battery and a wireless charging transmission module. The wireless charging module includes a controller, a transmitter, and a receiver. The controller and transmitter are integrated into an external charging pile, which is installed above the track and connected to an external power source. The receiver is installed on the outside of the robot body structure. When the transmitter and receiver are close to each other and stationary, the battery will be wirelessly charged. To prevent the battery from being charged too frequently, a charging threshold can be set through the control system, such as charging only when the battery power is below 80%.

[0022] Furthermore, when the robot is powered by its built-in battery during inspections, the remaining battery power should be monitored in real time. When the remaining power is lower than the set minimum protection level, the robot will stop the detection system to ensure longer battery life and autonomously move to the nearest charging station to recharge. The minimum protection level can be set to 20-30% of the battery's full power.

[0023] Furthermore, the installation spacing of charging piles is set according to the power consumption of the inspection robot, which can generally be set at 1.6 times the no-load travel distance of the inspection robot with the lowest protection power.

[0024] The structure of the detection chamber is basically the same as that of the robot.

[0025] The robotic inspection chamber's inspection equipment includes environmental monitoring sensors, a lining camera, an infrared thermal imager, a microphone, a laser rangefinder, and a two-dimensional laser profiler. These components are integrated and controlled by the robot's PLC. The lining camera and infrared thermal imager are mounted on a 360° rotating platform, which is installed at the rear of the inspection chamber's load-bearing structural base plate. This platform is used to capture images of the tunnel lining structure and the tunnel environment. The two-dimensional laser profiler is suspended at the front of the inspection chamber for 360° scanning of the tunnel's outline. The environmental monitoring sensors, microphone, and laser rangefinder are installed inside the equipment compartment of the inspection chamber.

[0026] Furthermore, the lining camera adopts an automatic zoom camera, which can achieve full-section coverage of the tunnel lining structure by adjusting the rotation of the pan-tilt head. The acquired image resolution is 0.3mm. Through the sub-pixel segmentation algorithm, it can accurately identify cracks larger than 0.2mm in the lining structure, and the detection requirements meet the engineering needs.

[0027] The robot-assisted system described above uses an I-shaped track with a high-strength aluminum alloy profile. The track is anodized, resulting in high strength, light weight, wear resistance, and corrosion resistance. The straight section of a single track is 3-4 meters long, while the turning sections are designed separately. The turning radius is determined by combining the robot's minimum turning radius with the tunnel equipment clearance.

[0028] The robot track support is made of stainless steel, which is high in strength and corrosion resistant. The support is fixed to the tunnel lining structure by chemical anchors, and has strong load capacity and vibration resistance.

[0029] Furthermore, the hanging bracket uses clamps to fix the rails. Holes are drilled on site, and the clamps are fixed to the rails with bolts. The rails are fixed to each other with connecting plates and bolts.

[0030] The robot wireless network system adopts AP networking, and the network topology adopts a fiber optic ring network linear link structure. Each base station communication control box is equipped with one optical ring network switch. Through the reserved dedicated single-mode 4-core optical fiber, it forms a ring network with the optical switch in the equipment room. The standard installation spacing of the communication base station is 180 meters / set. The installation spacing can be shortened when there is severe interference or obstruction in the tunnel.

[0031] The robot's RFID and wireless AP can be purchased commercially.

[0032] The robot data processing system mainly includes a high-performance computer and data processing software. The data processing system receives the collected data transmitted from the robot, analyzes the collected data according to the instructions issued by the control system, and feeds back the analysis results to the robot management platform or the robot itself.

[0033] Furthermore, based on the surface images of the tunnel lining structure collected by the robot, machine learning, image recognition and other methods are used, and the robot's data processing system can perform image detection on cracks, water leakage, spalling, steel corrosion and equipment damage in the tunnel lining structure, quickly generate detection and analysis reports and provide graded early warnings.

[0034] Furthermore, based on the infrared thermal imaging images collected by the robot, and using machine learning, image recognition and other methods, the robot's data processing system can assist in the accurate identification of structural water leakage and remote monitoring of vehicle wheel temperature, and provide timely warnings for vehicles with abnormal wheel heat or vehicle body temperature.

[0035] Furthermore, based on the laser point cloud data collected by the robot, through algorithms such as point cloud noise removal, point cloud 3D reconstruction and cutting extraction, and point cloud curve fitting, it can be used for deformation and encroachment analysis of tunnel lining structures.

[0036] Furthermore, based on the tunnel environment image data collected by the robot, AI intelligent analysis can be used to quickly perceive and warn of environmental events such as tunnel traffic flow, vehicle distribution, vehicle speed, and foreign object intrusion.

[0037] Furthermore, based on the environmental sensor data collected by the robot, data analysis can be performed to achieve full-process perception of light, temperature, humidity, and gas in each section of the tunnel.

[0038] The robot management platform is used for remote digital management of the data and analysis results collected by the inspection robot. It communicates with the robot body and the inspection chamber through a communication system. The management platform includes the following functional modules: platform homepage, real-time monitoring module, data center, inspection management, equipment center, and system settings. The robot management platform adopts a B / S architecture design, allowing maintenance personnel to remotely control robot movement, view equipment operating status, access historical monitoring records, adjust inspection paths, add inspection tasks, and remotely digitally manage inspection and analysis data through a web interface.

[0039] Furthermore, inspection management includes daily inspections, periodic inspections, key inspections, and emergency guidance, to meet various differentiated requirements of tunnel inspections.

[0040] (1) Routine inspection: Daily or frequent inspection of single or all items such as tunnel structure appearance defects, contour deformation, contour limits, environment, etc.

[0041] (2) Regular inspection: Periodic inspection of single or all items such as tunnel structure appearance defects, outline deformation, outline limit, environment, etc. The inspection frequency is generally 2 to 4 times a year;

[0042] (3) Key inspection: Key inspections are carried out using inspection robots for major defects found in ordinary inspections or for a specific key area of ​​the tunnel;

[0043] (4) Emergency guidance: In case of emergency, the robot can be guided to a designated location through the manual control module for emergency rescue guidance.

[0044] The beneficial effects of this invention are:

[0045] (1) This invention is a rail-mounted intelligent tunnel inspection robot, consisting of a main body and an inspection compartment. It adopts a separate and modular design, which facilitates the assembly, functional expansion and maintenance of the robot.

[0046] (2) The robot positioning of the present invention adopts a multi-dimensional integrated positioning system including ranging wheel, RFID, lidar, and image feature recognition, with centimeter-level absolute accuracy over long distances and millimeter-level precise positioning at important local locations;

[0047] (3) The technology of this invention adopts a distributed detection chamber design, with multiple sensors built in. Through the supporting data processing system and management platform, it can realize the detection of multiple items such as tunnel environment, structural appearance defects, structural contour deformation limit, and facility defects.

[0048] (4) The pod of the equipment of the present invention is formed by laser chiseling of aluminum alloy block and is equipped with heat sink. The cable communication interface is connected by aviation waterproof connector, and the protection level reaches IP65. It has a high protection level and strong environmental applicability. Attached Figure Description

[0049] Figure 1 This is a system composition diagram of the present invention;

[0050] Figure 2 This is a three-dimensional structural diagram of the robot body of the present invention;

[0051] Figure 3 This is a schematic diagram of the front view structure of the robot body of the present invention;

[0052] Figure 4 This is a schematic diagram of the right-side structure of the robot body of the present invention;

[0053] Figure 5 This is a schematic diagram of the invention installed inside a tunnel;

[0054] Figure 6 This is a flowchart of the motion control process of the present invention.

[0055] In the diagram: 1-Robot body, 2-Robot inspection chamber, 3-Equipment pod, 4-Bearing structure base plate, 5-Support, 6-Adaptive support, 7-Screw, 8-Spring, 9-Padded block, 10-Load-bearing wheel support, 11-Load-bearing wheel, 12-Encoder support, 13-Drive wheel, 14-Brake module, 15-Cooling fan, 16-Receiver, 17-M8 main bolt, 19-LiDAR, 20-Railway, 21-Railway hanger, 22-RFID, 23-360° rotating pan-tilt unit, 24-Lined camera, 25-Infrared thermal imager, 26-2D laser profiler, 27-Microphone, 28-Laser rangefinder, 29-Environmental monitoring sensor, 30-Adapter mechanism, 31-Guide wheel. Detailed Implementation

[0056] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0057] like Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 As shown, a track-mounted intelligent tunnel inspection robot consists of five main parts: the robot body 1, the robot inspection chamber 2, the robot auxiliary system, the robot data processing system, and the robot management platform. The robot body includes the robot body, control system, positioning system, power system, and communication system. The robot body is the supporting structure for the control system, positioning system, power system, and communication system. The positioning system transmits position signals to the control system via data lines. The communication system interacts with the control system via a router. The control system can integrate and control the positioning system, power system, and communication system. The power system provides power to the control system, positioning system, and communication system. The robot inspection chamber 2 includes the inspection chamber body, inspection equipment, and backup battery. The robot auxiliary system includes the track 20, the track support 21, the wireless network system, the RFID positioning system, and the wireless charging system. The robot data processing system includes a front-end data processing system and a back-end data processing system. The robot management platform is used for remote digital management of the data collected and analyzed by the inspection robot.

[0058] The robot inspection chamber 2 is connected to the robot body via a transfer mechanism 30, which connects mechanical, communication, and electrical components. Both the robot body and the robot inspection chamber 2 are suspended from the track 20 by two pairs of load-bearing wheels 9, ensuring stable operation of the robot on the track 20. The robot's built-in battery is charged via a wireless charging system on the track 20 and communicates with the outside world via a wireless network system. The robot auxiliary system is installed on the tunnel structure via a hanging bracket, including an RFID positioning system and a wireless charging system installed on the track 20. A wireless access point (AP) is used to establish a network communication system for the robot within the tunnel. The data collected by the robot is analyzed by the robot data processing system and interfaces with the robot management platform via a wireless network system, allowing it to receive task instructions from the robot management platform.

[0059] The robot body structure includes a load-bearing base plate 4, which is suspended from the track 20 by two pairs of four load-bearing wheels 11 via load-bearing wheel supports 10. The lateral spacing of each pair of load-bearing wheels 11 is less than one-third of the width of the track 20, ensuring that the robot will not slip off the track 20. The load-bearing wheels 11 are made of high-elastic PU material, and their bearings are professional high-speed sliding bearings, which can meet the requirements of high speed, no noise, wear resistance, and no shaft breakage. The supports 5 on the left and right sides are connected by a pair of screws 7, and a spring 8 is set between the screws 7. By adjusting the spring 8 between the screws 7, the clamping force between the supports 5 can be adjusted, thereby ensuring that the power wheel 13 is tightly attached to the side of the track 20. The pair of screws 7 are connected to the base plate through adaptive supports 6. The equipment cabin 3 is fixed to the load-bearing base plate 4 by four M8 main bolts 17, and a pad 9 is set between the four M8 main bolts 17 for main cabin plane adjustment.

[0060] High-elastic PU material: hardness of 84BN, adopts exclusive hexagonal core structure, which is more robust; load-bearing wheels 11 with an outer diameter of 52mm and a width of 31mm;

[0061] Furthermore, a guide wheel 31 is provided on the side below each load-bearing wheel 11. The guide wheel 31 slides along the bottom side of the track 20 to guide the robot to run smoothly on the track 20 and further ensure that the robot will not slide off the track 20.

[0062] Furthermore, a load-bearing wheel is selected as the ranging wheel 18. The selected load-bearing wheel is connected to the encoder support 12. The encoder support 12 has an encoder built in it for measuring the robot's travel distance.

[0063] Furthermore, four load-bearing wheels 11 are connected by a square steel plate, which serves as the main structure for the robot. A device pod 3 is fixed to the bottom of the square steel plate with bolts. The device pod 3 contains a battery, PLC, microcomputer, and router. The device pod 3 is made of aluminum alloy block laser-cut into one piece and is equipped with heat sinks. The cable communication interface is connected with aviation waterproof connectors to ensure that the protection level of the device pod reaches IP65.

[0064] PLC selection: Siemens CPU1212C main unit, model 6ES7212; Siemens CB1241 communication board, model 6ES7241; Siemens SB1222 expansion board, model 6ES7222.

[0065] Aviation waterproof connector selection: Fisher SS connectors are selected, with specifications including 0F102 opening M9, 1F103 opening M14, and 15F1031 opening M14.

[0066] The control system of the robot body includes a micro industrial computer and a PLC. The micro industrial computer is used to process various instructions, and the PLC is used to integrate and control various devices and communicate with the micro industrial computer via protocol.

[0067] Furthermore, the robot's control system also includes a motion control system, which comprises a control unit, a drive unit, an execution unit, and a position feedback loop. The motion control execution process is as follows:

[0068] (1) After receiving the motion command, the PLC sends the desired position value to the control unit;

[0069] (2) After receiving the instruction, the control unit sends a drive instruction to the drive unit, and the drive unit receives the instruction and transmits it to the execution unit;

[0070] (3) The execution unit performs the task and sends the location information back to the control unit;

[0071] (4) The control unit determines the deviation between the execution position and the desired position, and issues a correction command based on the analysis. Steps (1), (2), (3), and (4) are repeated until the robot moves precisely to the desired position.

[0072] Furthermore, the control unit mainly includes positioning algorithms, reset algorithms, S-shaped acceleration / deceleration algorithms, and interpolation algorithms, etc.

[0073] Positioning Algorithm Overview: The positioning system is completed by a closed-loop positioning system consisting of a controller and an encoder, along with an absolute positioning tag system. The controller, upon receiving a motion control signal, sends pulses of a fixed frequency to the driver based on the positioning mileage. The driver then analyzes the pulse train to control the angular displacement of the motor, which in turn controls the movement of the transmission mechanism. During operation, the encoder performs pulse detection (mileage measurement) on the transmission mechanism, which is then fed back to the system as feedback. The controller compares the number of pulses sent with the feedback pulses to correct the actual output pulse count.

[0074] RFID29 tag positioning serves as an absolute correction variable for the system. It is used as the raw data from the start to the end of the process. There are a certain number of tags within the positioning mileage range. After traveling to a certain range, the system receives the mileage point information written by the positioning tag, which is used as a forced perturbation variable to perform absolute positioning calibration on the system, thereby ensuring absolute consistency with the actual environment.

[0075] Reset Algorithm Overview: Relying on obstacle avoidance algorithms, this algorithm uses a two-dimensional Cartesian histogram grid to represent the obstacle environment. Each grid cell stores a confidence value, representing the algorithm's confidence in the presence of an obstacle at that location. When the robot moves, an active window is established centered on the robot's center point.

[0076] Introduction to S-Curve Acceleration / Deceleration Algorithm: The S-curve acceleration / deceleration algorithm features a smooth velocity curve, reducing impact on the control process and making the interpolation process more flexible. Since the acceleration changes during acceleration / deceleration, a new variable, jerk, is introduced. Three fundamental system parameters determine the entire operation: maximum system speed, maximum acceleration a_{max}, and jerk.

[0077] 1) Velocity-time relationship equation

[0078] By combining the acceleration-time relationship, the velocity curve relationship can be obtained, as follows;

[0079]

[0080] Further simplification yields:

[0081]

[0082] 2) Displacement-time relationship equation

[0083] The equation for the final displacement is derived from the displacement and jerk, as shown below.

[0084]

[0085] Interpolation Algorithm Introduction: It uses linear interpolation, which approximates the two points by using the interpolation between them along a straight line.

[0086] Suppose that at the starting point of the actual contour, a small segment is moved along the X direction (a fixed distance is moved by the pulse equivalent axis), and the endpoint is found to be below the actual contour, then the next line segment moves a small segment along the Y direction.

[0087] If the endpoint of the line segment is still below the actual contour, continue moving a short distance along the Y direction until it is above the actual contour, then move a short distance along the X direction, and so on, until the endpoint of the contour is reached.

[0088] The actual outline is composed of segments of broken lines. Although they are broken lines, each interpolation segment is very small within the allowable range of precision. Therefore, this broken line segment can still be approximated as a straight line segment. This is called linear interpolation.

[0089] The further drive unit includes a servo driver and two drive wheels 13. The servo driver is installed in the equipment pod 3. The two drive wheels 13 are clamped on both sides of the cross section of the track 20. The drive wheel shafts are fixed to the square steel plate. Each pair of drive wheels 13 is connected by an elastic link 7, which is used to adjust the clamping force of the drive wheels 13. The rotation of the drive wheels 13 drives the robot to travel in a straight line along the track. The travel speed is greater than 3.5 meters per second, and the braking distance is less than 0.5 meters.

[0090] The robot's braking module 14 is installed in front of the equipment pod 3. It controls whether the brake pads contact the rail surface of the track 20 through an electromagnetic device. When they contact, it brakes suddenly.

[0091] Furthermore, a cooling fan 15 is installed below the brake module 14 to dissipate heat from the equipment inside the equipment pod 3;

[0092] The positioning system of the robot body includes a multi-dimensional integrated positioning system such as a ranging wheel 18, RFID 22, lidar 19, and image feature recognition. The ranging wheel 18 is used for coarse positioning, RFID 22 and image feature recognition are used for long-distance measurement error correction of the ranging wheel 18, and lidar 19 is used for obstacle avoidance. It can ensure centimeter-level absolute accuracy over long distances and millimeter-level positioning for important local locations.

[0093] RFID22 equipment selection: We selected Woji Technology's RFID22 and anti-metal tags. The RFID22 model is TR-H620, and the anti-metal tag model is TG-H50R.

[0094] Furthermore, depending on the actual linearity of the tunnel, the RFID22 units can be arranged at intervals of 20 to 50 meters.

[0095] The power system of the robot body includes a battery and a wireless charging transmission module. The wireless charging transmission module includes a controller, a transmitter, and a receiver 16. The controller and transmitter are integrated into an external charging pile, which is installed above the track 20 and connected to an external power source. The receiver 16 is installed on the outside of the robot body structure. When the transmitter and receiver 16 are close to each other and stationary, the battery will be wirelessly charged. To prevent the battery from being charged frequently, a charging threshold can be set through the control system, such as charging only when the battery power is below 80%.

[0096] Furthermore, when the robot is powered by its built-in battery during inspections, the remaining battery power should be monitored in real time. When the remaining power is lower than the set minimum protection level, the robot will stop the detection system to ensure longer battery life and autonomously move to the nearest charging station to recharge. The minimum protection level can be set to 20-30% of the battery's full power.

[0097] Furthermore, the installation spacing of charging piles is set according to the power consumption of the inspection robot, which can generally be set at 1.6 times the no-load travel distance of the inspection robot at the minimum protection power level.

[0098] The structure of the detection chamber is basically the same as that of the robot.

[0099] The detection equipment in the robot inspection chamber 2 includes an environmental monitoring sensor 29, a lining camera 24, an infrared thermal imager 25, a microphone 27, a laser rangefinder 28, and a two-dimensional laser profiler 26. The environmental monitoring sensor, lining camera 24, infrared thermal imager 25, microphone 27, laser rangefinder 28, and two-dimensional laser profiler 26 are integrated and controlled by the robot's PLC. The lining camera and infrared thermal imager 25 are integrated and mounted on a 360° rotating pan-tilt unit 23, which is installed at the rear of the robot inspection chamber 2's support base plate for capturing images of the tunnel lining structure and the tunnel environment. The two-dimensional laser profiler 26 is suspended at the front of the robot inspection chamber 2 for 360° scanning of the tunnel's outline structure. The environmental monitoring sensor 29, microphone 27, and laser rangefinder 28 are installed inside the robot equipment hanging chamber 3.

[0100] Infrared thermal imaging equipment selection: The Gewu Youxin Infrared Thermal Imager 25 is selected, with a resolution of 640-480, a maximum frequency of 30Hz, and a thermal sensitivity of ≤50mK@25℃. It also adopts a fixed-focus lens.

[0101] Furthermore, the lining camera 24 adopts an automatic zoom camera. Based on the rotation adjustment of the rotating pan-tilt head, it can achieve full-section coverage of the tunnel lining structure and acquire images with a resolution of 0.3mm. Through the sub-pixel segmentation algorithm, it can accurately identify cracks larger than 0.2mm in the lining structure, and the detection requirements meet the engineering needs.

[0102] The robot-assisted system described above uses an I-shaped track for track 20. Track 20 is made of high-strength aluminum alloy profile with anodized surface, resulting in high strength, light weight, wear resistance, and corrosion resistance. The straight section of a single track 20 is 3-4 meters long, and the turning section is designed separately. The turning radius is determined based on the robot's minimum turning radius and the tunnel equipment clearance.

[0103] The dimensions of the 20mm I-beam for the rail are: I-shaped, with a top surface width of 60mm, a bottom surface width of 90mm, a total height of 110mm, and a wall thickness of 5mm.

[0104] The robot track support 21 is made of stainless steel, which is high in strength and corrosion resistant. The support is fixed to the tunnel lining structure by chemical anchors, which has strong load capacity and vibration resistance.

[0105] Chemical anchor selection: M8X110mm, drilling diameter 10mm, drilling depth 80mm, anchoring length 75mm;

[0106] Furthermore, the hanging bracket uses a clamp to fix the rail 20. Holes are drilled on site, and the clamp is fixed to the rail 20 with bolts. The rails 20 are fixed to each other with connecting pieces and bolts.

[0107] The robot wireless network system adopts AP networking, and the network topology adopts a fiber optic ring network linear link structure. Each base station communication control box is equipped with one optical ring network switch. Through the reserved dedicated single-mode 4-core optical fiber, it forms a ring network with the optical switch in the equipment room. The standard installation spacing of the communication base station is 180 meters / set. The installation spacing can be shortened when there is severe interference or obstruction in the tunnel.

[0108] The robot RFID20 and wireless AP mentioned above can be purchased commercially.

[0109] The robot data processing system includes a high-performance computer and data processing software. The data processing system receives the collected data transmitted from the robot, analyzes the collected data according to the instructions issued by the control system, and feeds back the analysis results to the robot management platform or the robot itself.

[0110] Furthermore, based on the surface images of the tunnel lining structure collected by the robot, machine learning, image recognition and other methods are used, and the robot's data processing system can perform image detection on cracks, water leakage, spalling, steel corrosion and equipment damage in the tunnel lining structure, quickly generate detection and analysis reports and provide graded early warnings.

[0111] Furthermore, based on the infrared thermal imaging images collected by the robot, and using machine learning, image recognition and other methods, the robot's data processing system can assist in the accurate identification of structural water leakage and remote monitoring of vehicle wheel temperature, and provide timely warnings for vehicles with abnormal wheel heat or vehicle body temperature.

[0112] Furthermore, based on the laser point cloud data collected by the robot, through algorithms such as point cloud noise removal, point cloud 3D reconstruction and cutting extraction, and point cloud curve fitting, it can be used for deformation and encroachment analysis of tunnel lining structures.

[0113] Furthermore, based on the tunnel environment image data collected by the robot, AI intelligent analysis can be used to quickly perceive and warn of environmental events such as tunnel traffic flow, vehicle distribution, vehicle speed, and foreign object intrusion.

[0114] Furthermore, based on the environmental sensing data collected by the robot, through data analysis, it is possible to achieve full-process perception of light, temperature, humidity, and gas in each section of the tunnel.

[0115] The robot management platform includes the following functional modules: platform homepage, real-time monitoring module, data center, inspection management, equipment center, system settings, etc. The platform adopts a B / S architecture design, and maintenance personnel can remotely control robot movement, view equipment operating status, access equipment historical monitoring records, adjust inspection paths, add inspection tasks, and remotely digitally manage inspection and analysis data through the web interface.

[0116] Furthermore, inspection management includes daily inspections, periodic inspections, key inspections, and emergency guidance, to meet various differentiated requirements of tunnel inspections.

[0117] (1) Routine inspection: Daily or frequent inspection of single or all items such as tunnel structure appearance defects, contour deformation, contour limits, environment, etc.

[0118] (2) Regular inspection: Periodic inspection of single or all items such as tunnel structure appearance defects, contour deformation, contour limit, environment, etc. The inspection frequency is generally 2 to 4 times a year;

[0119] (3) Key inspection: Key inspections are carried out using inspection robots for major defects found in ordinary inspections or for a specific key area of ​​the tunnel;

[0120] (4) Emergency guidance: In case of emergency, the robot can be guided to a designated location through the manual control module for emergency rescue guidance.

[0121] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection claimed by the claims of the present invention.

Claims

1. A rail-mounted intelligent tunnel inspection robot, characterized in that: The system comprises five main parts: the robot body, the robot inspection chamber, the robot auxiliary system, the robot data processing system, and the robot management platform. The robot inspection chamber is connected to the robot body via a transfer mechanism, which connects mechanical, communication, and electrical components. Both the robot body and the robot inspection chamber are suspended from a track by two pairs of load-bearing wheels. The robot body's built-in battery is charged via a wireless charging system on the track and communicates with the outside world using a wireless network system. The robot auxiliary system is mounted on the tunnel structure via a hanger and uses a wireless access point (AP) to establish a network communication system for the robot within the tunnel. Data collected by the robot body is analyzed by the robot data processing system and interfaces with the robot management platform via the wireless network system, allowing it to receive task commands from the robot management platform. The robot body includes a robot frame, a control system, a positioning system, a power system, and a communication system. The robot frame serves as the supporting structure for the control system, positioning system, power system, and communication system. The positioning system communicates with the robot body via a data cable. The control system transmits position signals, and the communication system interacts with the control system through a router. The control system can integrate and control the positioning system, power system, and communication system. The power system provides power to the control system, positioning system, and communication system. The robot body includes a load-bearing structural base plate, which is suspended from a track by two pairs of four load-bearing wheels. Each load-bearing wheel has a guide wheel on its side below it, which slides along the bottom side of the track. The four load-bearing wheels are connected by a square steel plate, and a device pod is bolted to the bottom of the square steel plate. The device pod houses a battery, PLC, microcomputer, and router, and is equipped with heat sinks. The robot body's control system includes a micro industrial computer and a PLC. The micro industrial computer processes various instructions, and the PLC integrates and controls the various devices and communicates with the micro industrial computer via a protocol. The robot body's control system also includes a motion control system, which includes a control unit, a drive unit, an execution unit, and a position feedback loop. The motion control execution process is as follows: (1) After receiving the motion command, the PLC sends the desired position value to the control unit; (2) After receiving the instruction, the control unit sends a drive instruction to the drive unit, and the drive unit receives the instruction and transmits it to the execution unit; (3) The execution unit performs the task and sends the location information back to the control unit; (4) The control unit determines the deviation between the execution position and the desired position, and issues a correction command based on the analysis. Steps (1), (2), (3), and (4) are repeated until the robot moves precisely to the desired position. The robot's positioning system includes a ranging wheel, RFID, lidar, and an image feature recognition module. The ranging wheel is used for coarse positioning, the RFID and image feature recognition module are used for long-distance measurement error correction of the ranging wheel, and the lidar is used for obstacle avoidance. The power system of the robot body includes a battery and a wireless charging transmission module. The wireless charging module includes a controller, a transmitter, and a receiver. The controller and transmitter are integrated into an external charging pile, which is installed above the track and connected to an external power source. The receiver is installed on the outside of the robot body structure. When the transmitter and receiver are close to each other and stationary, the battery will be wirelessly charged.

2. The intelligent tunnel inspection robot according to claim 1, characterized in that, The control unit includes a positioning algorithm module, a reset algorithm module, an S-shaped acceleration / deceleration algorithm module, and an interpolation algorithm module; the drive unit mainly includes a servo driver and two drive wheels. The servo driver is installed in the equipment pod, and the two drive wheels are clamped on both sides of the track cross section. The drive wheel shafts are fixed to a square steel plate. Each pair of drive wheels is connected by an elastic link to adjust the clamping force of the drive wheels. The rotation of the drive wheels drives the robot to travel in a straight line along the track.

3. The intelligent tunnel inspection robot according to claim 1, characterized in that, The robotic inspection chamber includes an inspection chamber body, inspection equipment, and a backup battery. The inspection equipment includes an environmental monitoring sensor, a lining camera, an infrared thermal imager, a microphone, a laser rangefinder, and a two-dimensional laser profiler. These components are integrated and controlled by a PLC integrated into the robot body. The lining camera and infrared thermal imager are integrated and mounted on a 360° rotating pan-tilt unit, which is installed at the rear of the load-bearing structural base plate of the inspection chamber body. This unit is used to capture images of the tunnel lining structure and the tunnel environment. The two-dimensional laser profiler is suspended at the front of the inspection chamber body for 360° scanning of the tunnel's outline structure. The environmental monitoring sensor, microphone, and laser rangefinder are installed inside the equipment compartment of the inspection chamber body.

4. The intelligent tunnel inspection robot according to claim 1, characterized in that, The robot-assisted system includes a track, a track support bracket, a wireless network system, an RFID positioning system, and a wireless charging system. The RFID positioning system and the wireless charging system are installed on the track. The wireless network system adopts an AP network, and the network topology adopts a fiber optic ring network linear link structure. Each base station communication control box is equipped with one optical ring network switch, which forms a ring network with the optical switch in the computer room through a reserved dedicated single-mode 4-core optical fiber.

5. The intelligent tunnel inspection robot according to claim 1, characterized in that, The robot data processing system includes a high-performance computer and data processing software, and includes a front-end data processing system and a back-end data processing system. The data processing system receives the collected data transmitted from the robot, analyzes the collected data according to the instructions issued by the control system, and feeds back the analysis results to the robot management platform or the robot body. Based on the surface images of the tunnel lining structure collected by the robot, machine learning and image recognition methods are used, and the robot's data processing system can perform image detection on cracks, water leakage, spalling, steel corrosion and equipment damage in the tunnel lining structure, quickly generate detection and analysis reports, and provide graded early warnings. Based on the infrared thermal imaging images collected by the robot, and using machine learning and image recognition methods, the robot's data processing system can assist in the accurate identification of structural water leakage and remote monitoring of vehicle wheel temperature, and provide timely warnings for vehicles with abnormal wheel or body temperature. Based on the laser point cloud data collected by the robot, through point cloud noise removal, point cloud 3D reconstruction and cutting extraction, and point cloud curve fitting algorithm processing, it can be used for deformation and encroachment analysis of tunnel lining structure; Based on tunnel environment image data collected by the robot, AI intelligent analysis can be used to quickly perceive and warn of environmental events such as tunnel traffic flow, vehicle distribution, vehicle speed, and foreign object intrusion. Based on the environmental sensor data collected by the robot, the system can analyze the data to achieve full-process perception of light, temperature, humidity, and gas in each section of the tunnel.

6. The intelligent tunnel inspection robot according to claim 1, characterized in that, The robot management platform includes a platform homepage, a data center, an inspection management module, and an equipment center module; it is used for remote digital management of the data and analysis results collected by the inspection robots.

7. The intelligent tunnel inspection robot according to claim 1, characterized in that, When the robot is using its built-in battery for inspection, the remaining battery power should be monitored in real time. When the remaining power is lower than the set minimum protection power, the robot will stop the detection system to ensure longer battery life and will autonomously move to the nearest charging station to charge. The minimum protection power can be set to 20-30% of the battery's full power. The installation spacing of the charging stations should be set according to the power consumption of the inspection robot, and should be set at 1.6 times the no-load travel distance of the inspection robot at the minimum protection power.

8. The intelligent tunnel inspection robot according to claim 1, characterized in that, The robot management platform includes the following functional modules: platform homepage, real-time monitoring module, data center, inspection management, equipment center, and system settings. The robot management platform adopts a B / S architecture design, allowing maintenance personnel to remotely control robot movement, view equipment operating status, access historical monitoring records, adjust inspection paths, add inspection tasks, and perform remote digital management of inspection and analysis data through a web interface. Inspection management includes daily inspections, periodic inspections, key inspections, and emergency guidance.

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