Rail-suspended intelligent tunnel inspection robot

Abstract

The present invention relates to a rail-suspended intelligent tunnel inspection robot, which mainly solves the technical problems, such as low speed, poor positioning accuracy, and relatively simple functionality, of existing inspection equipment. The intelligent inspection robot comprises a robot body, an inspection chamber, an auxiliary system, a data processing system and a robot management platform; the robot body comprises, for the robot body, a body structure, a control system, a positioning system, a power system and a communication system; the inspection chamber comprises, for the inspection chamber, a body structure, an inspection device and a standby battery; the auxiliary system comprises a rail, rail hangers, a wireless network system, an RFID positioning system and a wireless charging system; the data processing system comprises a front-end data processing system and a back-end data processing system; the robot management platform is used for carrying out remote digital management on data collected by the inspection robot and an analysis result.

Description

A rail-mounted intelligent tunnel inspection robot Technical Field

[0001] The present invention relates to an inspection robot, and in particular discloses a track-mounted intelligent tunnel inspection robot for highway, subway, municipal and other tunnels, which is applied to the field of underground infrastructure inspection. Background Art

[0002] With the development of technologies such as motion control, machine vision, environmental perception, and structural detection, 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, thereby ensuring the safe operation 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 tunnel defects. Patent CN201610578468.8 discloses an intelligent inspection robot for power tunnels, including a track-based running mechanism, a bottom-mounted chassis, a communication system, a smoke detector, a wireless transceiver system, and other equipment. This robot can provide automatic fire alarms, video and environmental monitoring, and supporting communication facilities for the entire tunnel. Patent CN202111525635.X discloses an intelligent inspection robot for highway tunnels and its control system, including a load-bearing component and a transmission component, which can easily record videos and query illegal vehicles. Patent CN201420557938.9 discloses an intelligent inspection robot for tunnels, including an external information collection system, a power and transmission system, a housing, and a lithium battery. This robot can provide feedback on the concentration of harmful gases in the tunnel and promptly detect hidden fires. However, these robots are unable to detect tunnel structural defects. Furthermore, their slow detection speed and limited functionality make them difficult to meet the requirements of daily and regular inspections of tunnel structures and environments.

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

[0005] Summary of the Invention

[0006] The purpose of the present 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 single function.

[0007] The objectives of the present invention can be achieved through the following technical solutions: a rail-mounted tunnel intelligent inspection robot, characterized in that it includes a robot body, a detection chamber, an auxiliary system, a data processing system and a robot management platform; the detection chamber is connected to the robot body through a switching mechanism; the robot body and the detection chamber are each suspended on the track through load-bearing wheels, and the built-in battery of the robot body is charged through the wireless charging system on the track, and uses a wireless network system to communicate data with the outside world; the auxiliary system is installed on the tunnel structure through a hanging bracket, and a network communication system is set up in the tunnel for the rail-mounted tunnel intelligent inspection robot using a wireless AP; the data collected by the robot body is analyzed by the data processing system, and data is connected to the robot management platform through the wireless network system, so that the robot body can accept task instructions from the robot management platform.

[0008] Optionally, the robot body includes a body structure, a control system, a positioning system, a power system and a communication system for the robot body; the body structure for the robot body is used to carry the control system, the positioning system, the power system and the communication system, the positioning system transmits a position signal to the control system through a data line, the communication system interacts with the control system through a router, the control system is used to perform integrated control of the positioning system, the power system and the communication system, and the power system is used to provide power for the control system, the positioning system and the communication system; the body structure for the robot body includes a load-bearing structure substrate, the load-bearing structure substrate is connected to the load-bearing The wheel is suspended on the track, and a guide wheel is provided on each side below the load-bearing wheel. The guide wheel slides along the side of the bottom of the track. The equipment pod is fixedly connected to the bottom of the load-bearing structure base plate. The battery, PLC, microcomputer, and router are provided in the equipment pod, and a heat sink is provided on the equipment pod. The control system includes a micro industrial computer and a PLC. The micro industrial computer is used to process various instructions. The PLC is used to perform integrated control of the positioning system, the power system, and the communication system, and perform protocol communication with the micro industrial computer. The control system also includes a motion control system. The motion control system includes a control unit, a drive unit, an execution unit, and a position feedback loop. The control system is used to perform the following motion control process:

[0009] Step (1) After receiving the motion instruction, the PLC provides the desired position information to the control unit;

[0010] Step (2) the control unit sends a corresponding driving instruction to the driving unit after receiving the expected position information, and the driving unit transmits the driving instruction to the execution unit after receiving the driving instruction;

[0011] In step (3), the execution unit executes the task based on the driving instruction and feeds back the current position information to the control unit;

[0012] In step (4), the control unit determines the deviation between the current position and the desired position, and issues a correction instruction based on the analysis result, and repeats steps (1), (2), (3), and (4) until the rail-mounted tunnel intelligent inspection robot accurately moves to the desired position;

[0013] The positioning system includes a distance measuring wheel, a laser radar, and an image feature recognition module. The distance measuring wheel is used for rough positioning, the image feature recognition module is used to correct long-distance measurement errors of the distance measuring wheel, and the laser radar is used for obstacle avoidance.

[0014] The power system includes the battery and a wireless charging sending module. The wireless charging module includes a controller, a transmitter and a receiver. The controller and the transmitter are integrated into an external charging pile. The charging pile is installed above the track and connected to an external power supply. The receiver is installed on the outside of the body structure for the robot body. When the transmitter and the receiver are close to each other and stationary, the battery is wirelessly charged.

[0015] Optionally, the control unit includes a positioning algorithm module, a reset algorithm module, an S-type acceleration and deceleration algorithm module, and an interpolation algorithm module; the drive unit includes a servo drive and two power wheels, the servo drive is installed in the equipment pod, the two power wheels are clamped on both sides of the middle section of the track, the axle of each power wheel is fixed to the supporting structure base plate by a screw, the distance between the axles is adjusted by the screw, and the rotation of the power wheel drives the rail-mounted tunnel intelligent inspection robot to travel in a straight line along the track.

[0016] Optionally, the inspection chamber includes a body structure for the inspection chamber, 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, and the environmental monitoring sensor, lining camera, infrared thermal imager, microphone, laser rangefinder, and two-dimensional laser profiler are integrated and controlled by the PLC of the robot body; the lining camera and the infrared thermal imager are integrated and installed on a flat 360° rotating pan-tilt platform, and the flat 360° rotating pan-tilt platform is installed below the robot body for shooting the surface image of the tunnel lining structure and the tunnel environment; the two-dimensional laser profiler is suspended on the front of the body structure for the inspection chamber for performing a 360° scan of the tunnel contour structure; the environmental monitoring sensor, the microphone, and the laser rangefinder are installed in the equipment pod of the body structure for the inspection chamber.

[0017] Optionally, the auxiliary system includes the track, the track hanging bracket, the wireless network system, the RFID positioning system, and the wireless charging system; wherein the RFID positioning system and the wireless charging system are installed on the track, the wireless network system adopts AP networking, and the network topology adopts a fiber optic ring network linear link structure. An optical ring network switch is installed in each base station communication control box, and a ring network is formed with the optical switch in the computer room through a reserved dedicated single-mode four-core optical fiber.

[0018] Optionally, the data processing system includes a front-end data processing system and a back-end data processing system, both of which include high-performance computers and data processing software. The data processing system receives the collected data transmitted by the robot body, 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;

[0019] The collected data includes tunnel lining structure surface images, infrared thermal imaging images, laser point cloud data, tunnel environment image data, and environmental sensor data;

[0020] The data processing system is used to perform image detection of cracks, water leakage, spalling, steel corrosion, and damage to facilities and equipment in the tunnel lining structure based on the surface image of the tunnel lining structure, using machine learning and image recognition methods, generate a detection analysis report, and provide graded warnings;

[0021] The data processing system is also used to assist in accurately identifying structural water leakage and remotely monitoring the wheel temperature of moving vehicles based on the infrared thermal imaging images using machine learning and image recognition methods, and to promptly issue warnings to vehicles with abnormal wheel heat or body temperature;

[0022] The data processing system is also used to analyze the deformation and intrusion of the tunnel lining structure based on the laser point cloud data through point cloud noise removal, point cloud three-dimensional reconstruction and cutting extraction, and point cloud curve fitting algorithm processing;

[0023] The data processing system is also used to quickly perceive and issue early warnings of environmental events such as tunnel traffic volume, vehicle distribution, vehicle speed, and foreign object intrusion based on the tunnel environment image data through AI intelligent analysis;

[0024] The data processing system is also used to perceive the entire process of light, temperature, humidity and gas in each section of the tunnel through data analysis based on the environmental sensing data.

[0025] Optionally, the robot management platform includes a platform homepage, a data center, an inspection management module and an equipment center module; the robot management platform is used to remotely digitally manage the data collected by the inspection robot and the analysis results.

[0026] Optionally, the battery is used to power the rail-mounted tunnel intelligent patrol robot, and the remaining power of the battery is monitored in real time. When the remaining power is lower than the set minimum protection power, the detection system stops working, and the rail-mounted tunnel intelligent patrol robot moves autonomously to the nearest charging pile for charging. The installation spacing of the charging piles is set according to the power consumption of the rail-mounted tunnel intelligent patrol robot.

[0027] Optionally, 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, and operation and maintenance personnel can remotely control robot movement, view equipment operation status, review equipment historical monitoring records, adjust inspection paths, add inspection tasks, and perform remote digital management operations of inspection and analysis data through a web interface; the inspection management includes daily inspections, regular inspections, key inspections, and emergency guidance.

[0028] (1) Daily inspection: daily or regular inspection of single or all items such as tunnel structure surface defects, contour deformation, contour limits, and environment;

[0029] (2) Regular inspection: Periodic inspection of single or all items such as tunnel structure surface defects, contour deformation, contour limits, and environment. The inspection frequency is generally 2 to 4 times a year.

[0030] (3) Key inspection: Use inspection robots to conduct key inspections on major defects found during routine inspections or on a designated key area in the tunnel.

[0031] (4) Emergency guidance: In case of emergency, the robot is guided to the designated location through the manual control module for emergency rescue guidance.

[0032] Optionally, the minimum protection power is 20-30% of the full power of the battery; the installation spacing of the charging piles is 1.6 times the no-load driving distance of the rail-mounted tunnel intelligent inspection robot at the minimum protection power.

[0033] Optionally, the robot body and the inspection chamber are each suspended on the track through two pairs of load-bearing wheels.

[0034] Optionally, the bearing structure base plate is suspended on the track via two pairs of load-bearing wheels.

[0035] The beneficial effects of the present invention are:

[0036] (1) The present invention is a rail-mounted intelligent tunnel inspection robot, which is divided into a main body and an inspection chamber. It adopts a separate and modular design to facilitate the assembly, function expansion and maintenance of the robot;

[0037] (2) The robot positioning of the present invention adopts a multi-integrated positioning system including distance measuring wheels, RFID, laser radar, image feature recognition, etc., with centimeter-level absolute accuracy over long distances and millimeter-level precise positioning of local important positions;

[0038] (3) The technology of the present invention adopts a distributed detection chamber design with multiple built-in sensors. Through the supporting data processing system and management platform, it can realize the detection of multiple items such as tunnel environment, structural surface defects, structural contour deformation and intrusion, and facility defects;

[0039] (4) The equipment pod of the present invention is formed as a whole by laser chiseling an aluminum alloy block and is provided with a heat sink. The cable communication interface is connected with an aviation waterproof connector. The protection level reaches IP65, which has a high protection level and strong environmental applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] FIG1 is a system composition diagram of the present invention;

[0041] FIG2 is a schematic diagram of the three-dimensional structure of the robot body of the present invention;

[0042] FIG3 is a schematic diagram of the main structure of the robot body of the present invention;

[0043] FIG4 is a schematic diagram of the right side structure of the robot body of the present invention;

[0044] FIG5 is a schematic diagram of the present invention installed in a tunnel;

[0045] FIG6 is a motion control flow chart of the present invention.

[0046] In the figure: 1-robot body, 2-inspection chamber, 3-equipment pod, 4-bearing structure base plate, 5-support, 6-adaptive support, 7-screw, 8-spring, 9-pad, 10-load-bearing wheel support, 11-load-bearing wheel, 12-encoder support, 13-power wheel, 14-brake module, 15-cooling fan, 16-receiving end, 17-M8 main bolt, 19-lidar, 20-track, 21-track hanging bracket, 22-RFID, 23-planar 360° rotating pan / tilt head, 26-2D laser profiler, 30-adapter mechanism, 31-guide wheel. DETAILED DESCRIPTION

[0047] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] As shown in Figures 1, 2, 3, 4, 5 and 6, a rail-mounted intelligent tunnel inspection robot includes five major parts: a robot body 1, an inspection chamber 2, an auxiliary system, a data processing system and a robot management platform; the robot body includes a body structure for the robot body, a control system, a positioning system, a power system and a communication system; the body structure for the robot body is used to carry the control system, positioning system, power system and communication system, the positioning system transmits a position signal to the control system through a data line, the communication system interacts with the control system through a router, the control system can integrate the positioning system, power system and communication system, and the power system provides power for the control system, positioning system and communication system; the inspection chamber 2 includes a body structure for the inspection chamber, inspection equipment and a backup battery; the auxiliary system includes a track 20, a track hanging bracket 21, a wireless network system, an RFID positioning system and a wireless charging system; the data processing system includes a front-end data processing system and a back-end data processing system; the robot management platform is used to remotely digitally manage the data collected by the inspection robot and the analysis results.

[0049] The inspection chamber 2 is connected to the robot body 1 through a transfer mechanism 30, and the connection includes mechanical connection, communication connection, and electrical connection; the robot body 1 and the inspection chamber 2 are each suspended on the track 20 through two pairs of load-bearing wheels 9 to ensure that the robot runs stably on the track 20; the robot's built-in battery is charged through the wireless charging system on the track 20, and uses the wireless network system to communicate data with the outside world; the auxiliary system is installed on the tunnel structure, wherein the track hanger 21 is used to connect the tunnel structure and the track 20, the RFID positioning system and the wireless charging system are installed on the track 20, and a wireless AP is used to set up a network communication system for the robot in the tunnel; the data collected by the robot is analyzed by the data processing system, and data is connected to the robot management platform through the wireless network system, and can accept task instructions from the robot management platform.

[0050] 2-4 show an example structure of the robot body 1 in the rail-mounted tunnel intelligent inspection robot of the present invention. As shown in Figures 2-4, the body structure of the robot body 1 includes a load-bearing structure base plate 4, which is suspended on the track 20 through two pairs of four load-bearing wheels 11 on the 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, which can ensure that the robot will not slide out from the track 20. The load-bearing wheels 11 are made of highly elastic PU material, and their bearings are ceramic waterproof bearings, which can meet high speed, no noise, wear resistance, and no shaft explosion. 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; a pair of screws 7 are connected to the load-bearing structure base plate 4 through an adaptive support 6; the equipment pod 3 is fixed to the load-bearing structure base plate 4 by bolts, preferably, it is fixed to the load-bearing structure base plate 4 by four M8 main bolts 17, and each M8 main bolt 17 is equipped with a pad 9 for main warehouse plane adjustment.

[0051] Furthermore, the hardness of the above-mentioned high-elastic PU material is 84BN, and the load-bearing wheel 11 adopts a dedicated hexagonal core structure, which is more solid; the outer diameter of the load-bearing wheel 11 is 52mm and the width is 31mm.

[0052] Furthermore, a guide wheel 31 is provided laterally below each load-bearing wheel 11 , and the guide wheel 31 slides along the bottom side of the track 20 to guide the robot laterally to run smoothly on the track 20 and further ensure that the robot does not slide out of the track 20 .

[0053] Furthermore, a load-bearing wheel is selected as a distance measuring wheel 18, and 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 travel distance of the robot;

[0054] Furthermore, the four load-bearing wheels 11 are connected through a load-bearing structure substrate 4. Optionally, the load-bearing structure substrate 4 is a square steel plate, which serves as the main structure of the robot. An equipment pod 3 is fixed under the square steel plate by bolts. Batteries, programmable logic controllers (PLCs), microcomputers, and routers are placed in the equipment pod 3. The equipment pod 3 is formed as one piece by laser chiseling from an aluminum alloy block and is provided with a heat sink. The cable communication interface is connected with an aviation waterproof connector to ensure that the protection level of the equipment pod reaches IP65.

[0055] Furthermore, the above-mentioned PLC can select at least one of the following: Siemens brand CPU1212C host, its model is 6ES7212; Siemens brand CB1241 communication board, its model is 6ES7241; Siemens brand SB1222 expansion board, its model is 6ES7222.

[0056] Furthermore, the above-mentioned aviation waterproof connector can use Fisher SS plugs. The specifications of Fisher SS plugs include 0F102 opening M9, 1F103 opening M14, and 15F1031 opening M14.

[0057] The control system of the robot body 1 includes a micro industrial computer and a PLC. The micro industrial computer is used to process various instructions, and the PLC is used to perform integrated control of various devices and perform protocol communication with the micro industrial computer.

[0058] Furthermore, the control system of the robot body 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:

[0059] (1) After receiving the motion command, the PLC provides the desired position information to the control unit;

[0060] (2) After receiving the expected position information, the control unit sends a corresponding driving instruction to the driving unit, and the driving unit transmits the driving instruction to the execution unit after receiving the driving instruction;

[0061] (3) The execution unit executes the task based on the driving instruction and feeds back the current position information to the control unit;

[0062] (4) The control unit determines the deviation between the current position and the desired position, and issues a correction instruction based on the analysis results, repeating steps (1), (2), (3), and (4) until the robot moves accurately to the desired position;

[0063] Furthermore, the control unit includes a positioning algorithm module, a reset algorithm module, an S-type acceleration and deceleration algorithm module, and an interpolation algorithm module;

[0064] Introduction to the positioning algorithm: It is completed by a closed-loop positioning system consisting of a controller and an encoder, and an absolute positioning tag system. After receiving the motion control signal, the controller is responsible for sending fixed-frequency pulses to the driver based on the positioning mileage. The driver then analyzes the pulse train to control the angular displacement of the motor, and then controls the movement of the transmission mechanism. During operation, the encoder performs pulse detection (mileage measurement) on the transmission mechanism and feeds this back to the system as system feedback. The controller compares the number of sent pulses with the feedback pulses and then corrects the actual output pulse number.

[0065] RFID tag positioning serves as an absolute correction variable assisted by the system. From the start to the end, it is used as the raw data amount. There is a certain interval of tags in the positioning mileage interval. After traveling to a certain interval, the system receives the mileage point information written by the positioning tag and uses it as a forced disturbance variable to perform absolute positioning calibration on the system to ensure absolute consistency with the actual environment.

[0066] The Reset Algorithm Overview: This algorithm relies on an obstacle avoidance algorithm and uses a two-dimensional Cartesian histogram grid to represent the obstacle environment. Each grid cell stores a confidence value, indicating the algorithm's confidence in the presence of an obstacle at that location. As the robot moves, an active window is established centered around the robot's center point.

[0067] S-shaped acceleration and deceleration algorithm overview: S-shaped acceleration and deceleration have a smooth velocity curve, which reduces impact on the control process and makes the interpolation process flexible. Because the acceleration of the S-curve varies during acceleration and deceleration, a new variable, jerk, is introduced. Three fundamental system parameters: maximum system velocity, maximum acceleration a_{max}, and jerk determine the entire operation process.

[0068] 1) Speed-time relationship equation

[0069] Combining the acceleration-time relationship, the velocity curve relationship can be obtained. The specific relationship is as follows;

[0070] Further simplification can be obtained:

[0071] 2) Displacement-time relationship equation

[0072] Displacement and jerk, the equation for the final displacement is derived as follows:

[0073] Brief introduction of interpolation algorithm: It adopts linear interpolation method, and approximates the point group along the straight line by interpolating between two points.

[0074] (1) Assuming that a short distance is walked along the X direction at the starting point of the actual contour (a pulse equivalent axis walks a fixed distance), and the end point is found to be below the actual contour, the next line segment walks a short distance along the Y direction;

[0075] (2) If the end point of the line segment is still below the actual contour, continue to move a short distance in the Y direction until it is above the actual contour, then move a short distance in the X direction, and so on, until the end point of the contour is reached.

[0076] In this way, the actual contour is composed of segments of broken lines. Although it is a broken line, each interpolated segment is very small within the allowable accuracy range, so this broken line segment can still be approximately regarded as a straight line segment. This is linear interpolation.

[0077] The drive unit further includes a servo drive and two power wheels 13. The servo drive is installed in the equipment pod 3. The two power wheels 13 are clamped on both sides of the middle section of the track 20. The power wheel axles are fixed to the square steel plate. As mentioned above, the clamping force of the power wheels 13 can be adjusted by adjusting the clamping force between the supports 5. The rotation of the power wheels 13 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.

[0078] The robot's brake module 14 is installed in front of the equipment pod 3 and controls whether the brake pads are in contact with the track 20 surface through an electromagnetic device. When contact occurs, emergency braking is performed;

[0079] Furthermore, a cooling fan 15 is provided below the brake module 14 to dissipate heat from the equipment in the equipment pod 3;

[0080] The positioning system of the robot body 1 includes a multi-integrated positioning system including a distance measuring wheel 18, a laser radar 19, and image feature recognition. The distance measuring wheel 18 is used for rough positioning, image feature recognition is used for long-distance measurement error correction of the distance measuring wheel 18, and the laser radar 19 is used for obstacle avoidance, which can ensure long-distance absolute accuracy at the centimeter level and millimeter-level positioning of local important positions; in addition, the RFID positioning system in the auxiliary system includes an RFID 22 arranged on the track 20, which can also be used for long-distance measurement error correction of the distance measuring wheel 18.

[0081] Furthermore, the RFID 22 can be selected from at least one of the following: RFID 22 and anti-metal tag of Woji Technology, the model of RFID 22 is TR-H620, and the model of metal tag is TG-H50R;

[0082] Furthermore, according to the actual linearity of the tunnel, the RFIDs 22 can be arranged at intervals of 20 to 50 meters;

[0083] The power system of the robot body 1 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 the transmitter are integrated into an external charging pile. The charging pile is installed above the track 20 and is connected to an external power supply. The receiver 16 is installed outside the robot body structure. When the transmitter and the receiver 16 are close to each other and stationary, the battery will be wirelessly charged. In order to prevent the battery from being charged frequently, a charging threshold can be set through the control system. For example, the battery can only be charged when the power is less than 80%;

[0084] Furthermore, when the robot is powered by a built-in battery during 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 endurance and move autonomously to the nearest charging station for charging. The minimum protection power can be set to 20-30% of the battery's full power.

[0085] Furthermore, the installation spacing of charging piles is set according to the power consumption of the inspection robot, and can generally be set at 1.6 times the no-load driving distance of the inspection robot with the lowest protection power;

[0086] The body structure of the detection chamber 2 is substantially the same as that of the robot body 1 , that is, the detection chamber 2 includes another equipment pod 3 similar to the robot body 1 ;

[0087] The detection equipment of the detection chamber 2 includes an environmental monitoring sensor, a lining camera, an infrared thermal imager, a microphone, a laser rangefinder, a two-dimensional laser profiler 26, etc. The environmental monitoring sensor, the lining camera 24, the infrared thermal imager 25, the microphone 27, the laser rangefinder 28, and the two-dimensional laser profiler 26 are integrated and controlled by the PLC of the robot body 1; the lining camera and the infrared thermal imager are integrated and installed on the flat 360° rotating pan-tilt platform 23, and the flat 360° rotating pan-tilt platform 23 is installed below the robot body 1 for capturing the surface image of the tunnel lining structure and the tunnel environment; the two-dimensional laser profiler 26 is suspended in front of the detection chamber 2 for performing a 360° scan of the tunnel contour structure; the environmental monitoring sensor, the microphone 27, and the laser rangefinder 28 are installed in the equipment pod 3 of the detection chamber 2;

[0088] Furthermore, the infrared thermal imaging device can be selected as the Gewu Youxin Infrared Thermal Imager 25, which has a resolution of 640×480, a maximum frequency of 30Hz, a thermal sensitivity of ≤50mK@25℃, and a fixed-focus lens;

[0089] Furthermore, the lining camera 24 uses an automatic zoom camera. Based on the rotation adjustment of the pan / tilt head, it can achieve full-section coverage of the tunnel lining structure. The captured image resolution is 0.3mm. Through the sub-pixel segmentation algorithm, it can achieve accurate identification of cracks larger than 0.2mm in the lining structure, and the detection requirements meet the engineering needs.

[0090] In the auxiliary system, the track 20 may optionally have an I-shaped cross section. The track 20 is made of high-strength aluminum alloy with an anodized surface, which is high in strength, light in weight, wear-resistant, and corrosion-resistant. The straight section of a single track 20 is 3 to 4 meters long, and the turning section is designed separately. The turning radius is determined based on the minimum turning radius of the robot and the tunnel equipment limit.

[0091] Furthermore, the cross-sectional dimensions of the track 20 are: I-shaped, 60 mm wide on the upper surface, 90 mm wide on the lower surface, 110 mm in total height, and 5 mm in wall thickness;

[0092] The track hanger 21 is made of stainless steel, which is high in strength and corrosion-resistant. The track hanger 21 is fixed to the tunnel lining structure by chemical anchor bolts, and has strong load capacity and vibration resistance.

[0093] Chemical anchor selection: M8X110mm, drilling diameter 10mm, drilling depth 80mm, anchoring length 75mm;

[0094] Furthermore, the track hanger 21 is fixed to the track 20 by a clamp, a hole is drilled on site, and the clamp is fixedly connected to the track 20 by bolts, and the track 20 is fixedly connected to the track 20 by connecting plates and bolts;

[0095] The wireless network system adopts AP networking, and the network topology adopts an optical ring network linear link structure. An optical ring network switch is installed in each base station communication control box. Through the reserved dedicated single-mode 4-core optical fiber, it forms a ring network with the optical switch in the computer room. The standard installation spacing of the communication base station is 180 meters / set. The installation spacing can be shortened in the case of severe interference and obstruction in the tunnel.

[0096] The RFID 22 and wireless AP can be purchased from the market.

[0097] The front-end data processing system and the back-end data processing system of the data processing system both include high-performance computers and data processing software. The data processing system receives the collected data transmitted by 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;

[0098] Furthermore, based on the surface images of the tunnel lining structure collected by the robot, using machine learning, image recognition and other methods, and through the robot's supporting data processing system, it can perform image detection of cracks, water leakage, spalling, steel corrosion and damage to the tunnel lining structure, quickly generate detection analysis reports, and issue graded warnings;

[0099] Furthermore, based on the infrared thermal imaging images collected by the robot, using machine learning, image recognition and other methods, through the robot's accompanying data processing system, it can assist in the accurate identification of structural water leakage and remote monitoring of the wheel temperature of moving vehicles, and promptly issue warnings for vehicles with abnormal wheel heat or body temperature;

[0100] Furthermore, based on the laser point cloud data collected by the robot, through point cloud noise removal, point cloud 3D reconstruction and cutting extraction, point cloud curve fitting and other algorithm processing, it can be used to analyze the deformation and intrusion of tunnel lining structures;

[0101] Furthermore, based on the tunnel environment image data collected by the robot, AI intelligent analysis can achieve rapid perception and early warning of environmental events such as tunnel traffic volume, vehicle distribution, vehicle speed, and foreign object intrusion;

[0102] Furthermore, based on the environmental sensor data collected by the robot, through data analysis, it can achieve full perception of the light, temperature, humidity, and gas in each section of the tunnel;

[0103] 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 operation and maintenance personnel can remotely control robot movement, view equipment operating status, access equipment historical monitoring records, adjust inspection routes, add inspection tasks, and remotely digitally manage inspection and analysis data through the web interface.

[0104] Furthermore, inspection management includes daily inspection, regular inspection, key inspection and emergency guidance to meet various differentiated requirements of tunnel inspection.

[0105] (1) Daily inspection: daily or regular inspection of single or all items such as tunnel structure surface defects, contour deformation, contour limits, and environment;

[0106] (2) Regular inspection: Periodic inspection of single or all items such as tunnel structure surface defects, contour deformation, contour limits, and environment. The inspection frequency is generally 2 to 4 times a year.

[0107] (3) Key inspection: Use inspection robots to conduct key inspections on major defects found during routine inspections or on a designated key area in the tunnel.

[0108] (4) Emergency guidance: In case of emergency, the robot is guided to the designated location through the manual control module for emergency rescue guidance.

[0109] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection claimed by the claims of the present invention.

Claims

1. A rail-mounted tunnel intelligent inspection robot, characterized in that: It includes a robot body, a detection chamber, an auxiliary system, a data processing system and a robot management platform; the detection chamber is connected to the robot body through a switching mechanism; the robot body and the detection chamber are each suspended on a track through load-bearing wheels, the battery built into the robot body is charged through a wireless charging system on the track, and data communication with the outside world is carried out using a wireless network system; the auxiliary system is installed on the tunnel structure through a hanging bracket, and a network communication system is set up in the tunnel for the rail-mounted tunnel intelligent inspection robot using a wireless AP; The data collected by the robot body is analyzed by the data processing system, and data is connected with the robot management platform through the wireless network system, so that the robot body can accept task instructions from the robot management platform.

2. The rail-mounted tunnel intelligent inspection robot according to claim 1 is characterized in that: The robot body includes a body structure, a control system, a positioning system, a power system and a communication system for the robot body; the body structure for the robot body is used to carry the control system, the positioning system, the power system and the communication system, the positioning system transmits a position signal to the control system through a data line, the communication system interacts with the control system through a router, the control system is used to perform integrated control of the positioning system, the power system and the communication system, and the power system is used to provide power for the control system, the positioning system and the communication system; the body structure for the robot body includes a bearing structure substrate, the bearing structure substrate is suspended by the load-bearing wheels Hanging on the track, a guide wheel is arranged on the side below the load-bearing wheel, and the guide wheel slides along the side of the bottom of the track. The equipment pod is fixedly connected to the bottom of the load-bearing structure substrate, and the battery, PLC, microcomputer, and router are arranged in the equipment pod. A heat sink is arranged on the equipment pod; the control system includes a micro industrial computer and a PLC, and the micro industrial computer is used to process various instructions. The PLC is used to perform integrated control of the positioning system, the power system, and the communication system, and perform protocol communication with the micro industrial computer; the control system also includes a motion control system, and the motion control system includes a control unit, a drive unit, an execution unit, and a position feedback loop. The control system is used to perform the following motion control process: Step (1) After receiving the motion instruction, the PLC provides the control unit with the desired position information; Step (2) the control unit sends a corresponding driving instruction to the driving unit after receiving the expected position information, and the driving unit transmits the driving instruction to the execution unit after receiving the driving instruction; Step (3) the execution unit executes the task based on the driving instruction and feeds back the current position information to the control unit; Step (4) The control unit determines the deviation between the current position and the desired position, and issues a correction instruction according to the analysis result, and repeats steps (1), (2), (3), and (4) until the rail-mounted tunnel intelligent inspection robot moves accurately to the desired position; The positioning system includes a distance measuring wheel, a laser radar, and an image feature recognition module. The distance measuring wheel is used for rough positioning, the image feature recognition module is used for long-distance measurement error correction of the distance measuring wheel, and the laser radar is used for obstacle avoidance. The power system includes the battery and a wireless charging sending module. The wireless charging module includes a controller, a transmitter and a receiver. The controller and the transmitter are integrated into an external charging pile. The charging pile is installed above the track and connected to an external power supply. The receiver is installed on the outside of the body structure for the robot body. When the transmitter and the receiver are close to each other and stationary, the battery is wirelessly charged.

3. The rail-mounted tunnel intelligent inspection robot according to claim 2 is characterized in that: The control unit includes a positioning algorithm module, a reset algorithm module, an S-type acceleration and deceleration algorithm module, and an interpolation algorithm module; the driving unit includes a servo drive and two power wheels, the servo drive is installed in the equipment pod, the two power wheels are clamped on both sides of the middle section of the track, the axle of each power wheel is fixed to the bearing structure base plate by a screw, the distance between the axles is adjusted by the screw, and the rotation of the power wheel drives the rail-mounted tunnel intelligent inspection robot to travel in a straight line along the track.

4. The rail-mounted tunnel intelligent inspection robot according to claim 1, characterized in that: The detection chamber includes a body structure for the detection chamber, detection equipment and a backup battery; the detection equipment includes an environmental monitoring sensor, a lining camera, an infrared thermal imager, a microphone, a laser rangefinder, and a two-dimensional laser profiler, and the environmental monitoring sensor, the lining camera, the infrared thermal imager, the microphone, the laser rangefinder, and the two-dimensional laser profiler are integrated and controlled through the PLC of the robot body; the lining camera and the infrared thermal imager are integrated and installed on a flat 360° rotating pan-tilt platform, and the flat 360° rotating pan-tilt platform is installed below the robot body to shoot the surface image of the tunnel lining structure and the tunnel environment; the two-dimensional laser profiler is suspended at the front of the body structure for the detection chamber to perform a 360° scan of the tunnel contour structure; the environmental monitoring sensor, the microphone, and the laser rangefinder are installed in the equipment nacelle of the body structure for the detection chamber.

5. The rail-mounted tunnel intelligent inspection robot according to claim 1, characterized in that: The auxiliary system includes the track, the track hanging bracket, the wireless network system, the RFID positioning system, and the wireless charging system; wherein the RFID positioning system and the wireless charging system are installed on the track, the wireless network system adopts AP networking, and the network topology adopts a fiber optic ring network linear link structure. An optical ring network switch is installed in each base station communication control box, and a ring network is formed with the optical switch in the computer room through a reserved dedicated single-mode four-core optical fiber.

6. The rail-mounted tunnel intelligent inspection robot according to claim 1, characterized in that: The data processing system includes a front-end data processing system and a back-end data processing system, both of which include high-performance computers and data processing software. The data processing system receives the collected data transmitted by the robot body, 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; The collected data includes tunnel lining structure surface image, infrared thermal imaging image, laser point cloud Data, tunnel environment image data, environmental sensor data; The data processing system is used to perform image detection of cracks, water leakage, spalling, steel bar corrosion and damage to facilities and equipment in the tunnel lining structure based on the surface image of the tunnel lining structure, using machine learning and image recognition methods, generate a detection analysis report, and provide graded warnings; The data processing system is also used to accurately identify structural water leakage and remotely monitor the wheel temperature of running vehicles based on the infrared thermal imaging images by using machine learning and image recognition methods, and to promptly warn vehicles with abnormal wheel heat or body temperature; The data processing system is also used to analyze the deformation and intrusion of the tunnel lining structure based on the laser point cloud data by removing point cloud noise, reconstructing and cutting point cloud three-dimensionally, and processing point cloud curve fitting algorithms; The data processing system is also used to quickly perceive and warn environmental events such as tunnel traffic volume, vehicle distribution, vehicle speed, and foreign object intrusion based on the tunnel environment image data through AI intelligent analysis; The data processing system is also used to perceive the entire process of light, temperature, humidity and gas in each section of the tunnel through data analysis based on the environmental sensor data.

7. The rail-mounted tunnel intelligent 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; the robot management platform is used for remote digital management of the data collected by the inspection robot and the analysis results.

8. The rail-mounted tunnel intelligent inspection robot according to claim 1, characterized in that: The battery is used to power the rail-mounted tunnel intelligent patrol robot. The remaining power of the battery is monitored in real time. When the remaining power is lower than the set minimum protection power, the detection system stops working, and the rail-mounted tunnel intelligent patrol robot moves autonomously to the nearest charging pile for charging. The installation spacing of the charging piles is set according to the power consumption of the rail-mounted tunnel intelligent patrol robot.

9. The rail-mounted tunnel intelligent 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, and operation and maintenance personnel can remotely control robot movement, view equipment operation status, review equipment historical monitoring records, adjust inspection paths, add inspection tasks, and remotely digitally manage inspection and analysis data through a web interface; the inspection management includes daily inspections, regular inspections, key inspections, and emergency guidance.

10. The rail-mounted tunnel intelligent inspection robot according to claim 8, characterized in that: The minimum protection power is 20-30% of the full power of the battery; the installation spacing of the charging piles is 1.6 times the no-load driving distance of the rail-mounted tunnel intelligent inspection robot under the minimum protection power.

11. The rail-mounted tunnel intelligent inspection robot according to claim 1, characterized in that: The robot body and the detection chamber are respectively suspended on the track through two pairs of load-bearing wheels.

12. The rail-mounted tunnel intelligent inspection robot according to claim 2, characterized in that: The bearing structure base plate is suspended on the track through two pairs of load-bearing wheels.

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