Full-automatic bridge health detection beam bottom robot and use method thereof

Abstract

The invention relates to a full-automatic bridge health detection beam bottom robot which comprises a full-span deflection and damage detection device composed of wheels, a control motor, a rotary encoder, a tilt angle sensor, a camera, a light shield, an annular light bar, a spring, a pressure sensor and a controller. Images shot by the camera have fixed zooming parameters, so that the damage degree can be measured conveniently; the radar local space positioning and automatic operation system is composed of an aircraft main body, a front millimeter wave radar, a rear millimeter wave radar, four reflection targets, a controller and a solar charging pile, and the front millimeter wave radar, the rear millimeter wave radar and the four reflection targets are used for providing local space positioning for the aircraft main body. The controller presets the space trajectory of the beam bottom robot for operation detection and going to the solar charging pile, and automatic operation is achieved. The robot can accurately detect the full-span deflection and damage condition of the bridge, accurate space positioning and storage are carried out on data, and powerful support is provided for bridge health condition evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge health detection, and in particular to a fully automated bridge health detection beam bottom robot and a use method thereof. Background Art

[0002] With the increasing number of trunk highway bridges in my country, by the end of 2023, there will be 547,122 trunk highway bridges (expressways, national and provincial highways), totaling 78.2856 million meters. Efficient and accurate deflection monitoring of active bridges is crucial for ensuring public safety and traffic security, extending bridge service life, and reducing maintenance costs. However, traditional bridge monitoring methods rely primarily on regular manual inspections or single sensors. Regular manual inspections have limitations, and the accuracy of measurement data depends on the inspector's experience and skills. Single sensors, including strain gauges and accelerometers, can only capture localized data on a bridge, and operating time and operating environment have a significant impact on sensor lifespan. For example, piezoelectric accelerometers, commonly used in bridge vibration monitoring, can fail due to prolonged current overload, which can burn out the internal circuitry. In harsh environments such as high temperature and high humidity, the sensor's data acquisition accuracy is severely affected. Using traditional bridge monitoring methods to detect deflection and damage across the entire span consumes significant resources and no longer meets the needs of current industry development. Furthermore, existing drone damage identification technology is limited in its ability to accurately locate damage. The determination of image scaling parameters for an unmanned aircraft system (UAS), which includes the entire drone and associated control equipment, is based on visual inspection. However, due to the frequent movement of the UAS during inspection, the scaling parameters constantly change, and the camera on the UAS cannot always be parallel to the surface of the structure, resulting in tilted and blurred images. Furthermore, image acquisition technology is susceptible to the influence of external lighting conditions, which can easily lead to poor recognition results due to unstable lighting conditions.

[0003] Emerging wall-climbing drones combine the features of wall-climbing robots and drones. These new UAS attach to structures, facilitating the acquisition of clear surface images. However, existing wall-climbing drones undergo significant attitude changes during the ascent (a rapid change from horizontal to vertical), resulting in unstable flight and requiring high operator skill. Furthermore, research indicates that no practical wall-climbing drones are currently available for damage detection.

[0004] Therefore, it is particularly urgent to propose an automated system that can accurately detect the deflection and damage of the entire span of a bridge and accurately locate the damage location. In response to the related technical problems mentioned above, the present invention proposes a fully automated bridge health inspection beam bottom robot and its use method, which has the following advantages: 1. Precise positioning: By cooperating with a full-span deflection and damage detection device, front and rear dual millimeter-wave radars, and four reflective targets, a three-dimensional coordinate system is established with the help of the bridge support position. The aircraft body and the damaged part of the bridge can be accurately positioned with positioning accuracy reaching the millimeter level, ensuring the accuracy of the detection results. The application of the high-precision distance measurement and triangulation positioning principle of the millimeter-wave radar enables the aircraft body to accurately determine its own position in the complex environment under the bridge, overcoming the problem of poor positioning accuracy of traditional aircraft bodies when the GNSS signal is unstable or blocked, and providing stable, reliable and high-precision spatial positioning support for bridge inspection. 2. Efficient and accurate detection: Using the full-span deflection and damage detection device equipped on the aircraft body, it can quickly and efficiently perform comprehensive inspections on the bridge beam bottom, greatly reducing the time and workload of manual inspections and improving inspection efficiency. 3. Highly automated: The drone is capable of autonomous flight, inspection, and charging along pre-set trajectories, requiring minimal assistance from personnel. Through the controller's preset path planning algorithm and radar local spatial positioning system, the drone can autonomously complete complex flight missions, automating and maximizing inspection efficiency and improving stability and reliability. 4. Multi-data fusion: Integrating multiple functions such as deflection measurement, angle measurement, damage image capture, and millimeter-wave radar positioning, it can simultaneously acquire deflection data at all locations across the entire span of the bridge beam bottom, along with precise spatially located damage information, providing comprehensive and accurate data support for bridge health assessments. The fusion analysis of the data processing system enables real-time monitoring and assessment of bridge health, promptly identifying potential safety hazards and providing a scientific basis for bridge maintenance and management. 5. Unified acquisition environment: The drone provides upward lift throughout its operation, maintaining close proximity to the bridge beam bottom. Image and data acquisition is minimally affected by natural conditions, addressing the issue of poor image quality associated with unstable flight during inspections associated with traditional drone-based inspection systems. 6. Green and Energy-Saving: Solar charging stations are used to provide charging power for the aircraft, fully utilizing renewable energy and reducing reliance on traditional energy, in line with the requirements of green development. The solar charging station design not only reduces operating costs but also reduces carbon emissions, making it environmentally friendly and having positive social and economic benefits. Summary of the Invention

[0005] The purpose of the present invention is to address the problems in the above-mentioned prior art and provide a fully automated bridge health detection beam bottom robot and its use method, so as to realize an automated system for accurately detecting the deflection and damage of the entire span of the bridge and accurately locating the damage position.

[0006] In order to achieve the above object, the present invention has the following technical solutions:

[0007] A fully automated bridge health inspection beam bottom robot, comprising:

[0008] A full-span deflection and damage detection device is composed of a wheel, a control motor, a rotary encoder, an inclination sensor, a camera, a light shield, an annular light bar, a spring, a pressure sensor, and a controller. The wheel is driven by a control motor, the rotary encoder collects the wheel rotation angle, the inclination sensor can monitor the inclination angle of the full-span deflection and damage detection device, the camera collects beam bottom image data, the light shield and the annular light bar jointly provide a stable image acquisition environment for the camera, the wheel rests on the bottom of the bridge, so that the camera captures images with fixed zoom parameters, thereby facilitating the subsequent accurate measurement of the degree of damage, four springs are installed above the pressure sensor, so that the full-span deflection and damage detection device can deflect while the wheel is close to the beam bottom, which is conducive to measuring the angle, the pressure sensor transmits pressure data to the controller, and when the pressure data is within the preset value range of the controller, the fully automated bridge health detection beam bottom robot begins deflection and damage detection.

[0009] A radar local spatial positioning and automated operation system includes an aircraft body, front and rear dual millimeter-wave radars, four reflective targets, a controller, and a solar charging pile. The aircraft body is a carrier of the full-span deflection and damage detection device, providing upward lift for the full-span deflection and damage detection device. The front and rear dual millimeter-wave radars are installed on both sides of the aircraft body to ensure that the center of gravity of the aircraft body is centered. The four reflective targets are arranged in pairs at the supports on both sides. The front and rear dual millimeter-wave radars cooperate with the four reflective targets to provide local precise spatial positioning for the aircraft body, and transmit the spatial positioning to the controller in real time. The controller can preset the operation detection spatial trajectory of the fully automated bridge health detection beam bottom robot and the spatial trajectory to the solar charging pile, thereby realizing automated operation.

[0010] As a preferred solution, the rotary encoder is used to measure the wheel rotation angle θ in real time and transmit the measured angle value to the controller. When the controller detects that the rotation angle increment reaches the threshold θ1, it synchronously records the bottom beam inclination angle θ collected by the inclination sensor at this time. 2i , and the image data collected by the camera, i is the number of times the increment reaches θ1 after the start of measurement, and the robot forward distance increment ΔL corresponding to the i-th angle increment θ1 is calculated by the triangle geometry measurement principle i and deflection increment ΔF iThe system adds the current calculated value to the historical accumulated actual deflection value and actual forward distance, thereby obtaining the actual forward distance parameter L based on the rotation angle θ1. i And the actual deflection value F i , the specific calculation formula is:

[0011]

[0012] ΔF i =L θ1 sinθ 2i ;

[0013]

[0014] i=1, 2, 3, ... n;

[0015] The high-precision measurement of the inclination sensor ensures the accuracy of the deflection calculation and can accurately reflect the vertical deformation of the bridge in service.

[0016] As a preferred solution, the full-span deflection and damage detection device, the front and rear dual millimeter-wave radars, and the four reflective targets are used to accurately spatially position the fully automated bridge health detection beam bottom robot, thereby accurately spatially positioning the beam bottom positions corresponding to the deflection data and image data. The initial position detected by the full-span deflection and damage detection device is the bridge support. The horizontal distance y from the beam bottom robot to the support at this time is obtained by the following formula: i ,

[0017] Δy i =cosθ 2i ΔL i ;

[0018]

[0019] i=1,2,3...n;

[0020] Two millimeter-wave radars are respectively identified with two reflection targets arranged on the same side of the bridge support, and the straight-line distance between the millimeter-wave radar and the two reflection targets is measured. One of the reflection targets is used as the origin of the spatial coordinate system. The y-axis of the spatial coordinate system is perpendicular to the mid-span section, the z-axis is perpendicular to the horizontal plane, and the x-axis is perpendicular to the yz plane. Assuming that the distance between the millimeter-wave radar and one of the reflection targets is d1 and the distance to the other reflection target is d2, and the spatial coordinates of the two reflection targets are (x1, y1, z1) and (x2, y2, z2) respectively, the local spatial coordinates (x, y, z) of the millimeter-wave radar can be solved by the following equation:

[0021] (x-x1) 2 +(y-y1)2 +(z-z1) 2 =d1 2 ;

[0022] (x-x2) 2 +(y-y2) 2 +(z-z2) 2 =d2 2 ;

[0023] y=y i ,z=F i +h;

[0024] Among them, (x1, y1, z1) and (x2, y2, z2) can be known through measurement, and h is the height difference in the z direction between the reflective target and the initial position detected by the fully automated bridge health inspection beam bottom robot. Later, a three-dimensional model of the inspected bridge can be established, and the spatial coordinates of each position of the beam bottom, the corresponding deflection data and image data can be fused and integrated with the three-dimensional model to facilitate more intuitive expression of various data.

[0025] As a preferred solution, the dual front and rear millimeter-wave radars and four reflective targets are designed to compensate for the limited millimeter-wave radar beam angle. When the fully automated bridge health inspection beam-bottom robot begins inspection at a bridge support on one side, the millimeter-wave radar and reflective target set farther from that support are activated to locate the robot's spatial coordinates. As the fully automated bridge health inspection beam-bottom robot approaches mid-span, both sets of millimeter-wave radars and reflective target devices are activated. When the spatial coordinates of the two millimeter-wave radars match, indicating that the fully automated bridge health inspection beam-bottom robot has reached the mid-span of the bridge being inspected, the millimeter-wave radar and reflective target set activated initially are deactivated, and the millimeter-wave radar and reflective target set on the other side of the fully automated bridge health inspection beam-bottom robot—that is, the millimeter-wave radar and reflective target set closer to the initial position—are activated for spatial positioning.

[0026] As a preferred solution, the front and rear dual millimeter-wave radars and four reflective targets can spatially locate the full-span deflection and damage detection device. Whenever the full-span deflection and damage detection device collects deflection data and image data, the controller will receive these two sets of data, and match and store the spatial coordinates (x, y, z) of the corresponding position of the data with the data.

[0027] A method for using a fully automated bridge health inspection beam bottom robot:

[0028] 1. Equipment Installation

[0029] 1. Install four reflective targets at the supports on both sides of the bridge to ensure their accurate positioning and firm fixation, so as to provide precise spatial positioning reference for the fully automated bridge health inspection beam bottom robot (hereinafter referred to as the "beam bottom robot").

[0030] 2. Choose a suitable location to install a solar charging station, usually near one end of the bridge, to ensure that the robot at the bottom of the beam can return smoothly to charge after the mission is completed, while ensuring that it has good sunlight conditions to maintain an adequate power supply.

[0031] 3. Move the beam-bottom robot to the vicinity of the bridge, and manually control its aircraft body to rise to the vicinity of the bridge bottom, so that the wheels of the full-span deflection and damage detection device gently rest on the bottom of the beam, completing the initial positioning deployment.

[0032] 2. Preliminary spatial coordinate collection

[0033] 1. The robot manually controls the movement of the beam bottom, utilizing dual front and rear millimeter-wave radars in conjunction with reflective targets to initially collect spatial coordinates of the beam bottom. During this process, an inclination sensor monitors the beam bottom's tilt in real time, while a camera simultaneously captures image data of the beam bottom. A light shield and circular light bar ensure a stable image acquisition environment. Pressure sensors monitor the contact pressure between the wheels and the beam bottom and transmit this data to a controller.

[0034] 2. The controller receives and stores the initially collected spatial coordinate data, which will serve as an important basis for the subsequent trajectory preset.

[0035] 3. Running track preset

[0036] 1. Based on the initially collected spatial coordinates of the beam bottom, combined with the bridge's design drawings and inspection requirements, the controller presets the robot's spatial trajectory for beam bottom inspection. Using specialized software or programming, the trajectory is divided into multiple key collection points. Each collection point's coordinate location, inspection task (deflection measurement, image acquisition), and corresponding instructions (such as wheel speed and camera resolution) are clearly defined. The robot's return trajectory to the solar charging station is also preset to ensure it accurately returns to recharge when its mission is complete or the battery is low.

[0037] 4. Positioning and starting of the bottom beam robot

[0038] 1. After completing the preset trajectory, the robot is manually controlled to move to the starting point along the preset trajectory. During the movement, the millimeter-wave radar and reflective targets are continuously used for position correction to ensure that the robot accurately reaches the preset starting point.

[0039] 2. When the robot reaches the preset starting point and the pressure sensor detects that the contact pressure between the wheel and the bottom of the beam is within the preset range of the controller, it indicates that the robot is in place and in a stable state. At this time, the automated working program of the bottom beam robot is started, and the robot will automatically begin working according to the preset running detection space trajectory.

[0040] 5. Automated testing

[0041] 1. The robot automatically moves along the preset trajectory. The wheels are driven by the control motor and move along the bottom of the beam. The rotary encoder monitors the wheel rotation angle θ in real time and transmits it to the controller. When the rotation angle increment reaches the threshold θ1, the controller synchronously records the bottom beam tilt angle θ collected by the inclination sensor. 2i The image data collected by the camera is used to calculate the robot's forward distance increment ΔL corresponding to the position through the triangle geometry measurement principle. i and deflection increment ΔF i The system adds the current calculated value and the historical accumulated data to obtain the actual forward distance parameter L i And the actual deflection value F i , to realize the detection of deflection at various positions of the full span bridge.

[0042] 2. Dual front and rear millimeter-wave radars continuously interact with reflective targets, updating the robot's spatial coordinates in real time to ensure accurate detection. When the robot approaches the mid-span of the bridge, the millimeter-wave radar and reflective target set on the other side are activated to continue precise positioning and detection. Simultaneously, the controller continuously matches and stores the collected deflection and image data with the spatial coordinates (x, y, z) of the corresponding locations, providing foundational data for subsequent construction of a 3D bridge model and data fusion.

[0043] 6. Mission End and Recharge

[0044] 1. After the beam bottom robot completes the preset full-span inspection task, the controller automatically controls the aircraft body to fly toward the solar charging station according to the preset return trajectory.

[0045] 2. After the main body of the aircraft arrives at the solar charging station, it precisely docks with the charging port, and the charging process begins. Simultaneously, the robot transmits the stored inspection data to the backend server for further analysis and assessment of the bridge's health, thus completing the inspection mission. During the charging process, the robot remains in standby mode, responding to pre-set activation times to receive new inspection instructions.

[0046] Compared with the prior art, the present invention has at least the following beneficial effects:

[0047] Precise spatial positioning: By integrating a full-span deflection and damage detection device, dual front and rear millimeter-wave radars, and four reflective targets, and utilizing the bridge support locations to establish a three-dimensional coordinate system, the aircraft and damaged parts of the bridge can be precisely located, with millimeter-level accuracy, ensuring the accuracy of inspection results. The high-precision distance measurement and triangulation principles of millimeter-wave radar enable the aircraft to accurately determine its position in the complex environment beneath the bridge. This overcomes the poor positioning accuracy of traditional aircraft when GNSS signals are unstable or obstructed, providing stable, reliable, and high-precision spatial positioning support for bridge inspections.

[0048] Efficient detection: The aircraft body is equipped with a full-span deflection and damage detection device, which can quickly and efficiently conduct comprehensive inspections of the bottom of bridge beams, greatly reducing the time and workload of manual inspections and improving inspection efficiency.

[0049] High degree of automation: The aircraft can autonomously fly, inspect, and charge along pre-set trajectories, requiring minimal assistance from personnel. Using the controller's preset path planning algorithm and radar local positioning system, the aircraft can autonomously complete complex flight missions, automating and maximizing inspection efficiency and stability.

[0050] Multiple Data Fusion: Integrating multiple functions such as deflection measurement, angle measurement, damage imaging, and millimeter-wave radar positioning, the system can simultaneously obtain deflection data at all locations across the entire span of a bridge beam bottom and damage information with precise spatial positioning, providing comprehensive and accurate data support for bridge health assessments. The data processing system's integrated analysis enables real-time monitoring and assessment of bridge health, promptly identifying potential safety hazards and providing a scientific basis for bridge maintenance and management.

[0051] Unified collection environment: The flying body provides upward lift throughout the entire working state, always keeping close to the bottom of the bridge beam. The image and data collection process is less affected by natural conditions, so that the camera can capture images with fixed zoom parameters. The light shield and ring light bar jointly provide a stable image collection environment for the camera, which facilitates the accurate measurement of the damage degree in the later stage and solves the problem of poor image collection quality caused by unstable flight during the inspection process of traditional UAV inspection devices.

[0052] Green and Energy-Saving: Solar charging stations provide charging power for the aircraft, fully utilizing renewable energy and reducing reliance on traditional energy, in line with the requirements of green development. The solar charging station design not only reduces operating costs but also reduces carbon emissions, making it environmentally friendly and delivering positive social and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The present invention is based on the overall structural diagram of the fully automated bridge health detection beam bottom robot;

[0054] Figure 2 Schematic diagram of the full-span deflection and damage detection device based on the fully automated bridge health detection beam bottom robot of the present invention;

[0055] (a) Schematic diagram of the overall structure; (b) Schematic diagram of the elevation;

[0056] Figure 3 Schematic diagram of the main body of the aircraft device based on the fully automated bridge health inspection beam bottom robot of the present invention;

[0057] Figure 4 The present invention is based on the workflow diagram of the fully automated bridge health detection beam bottom robot;

[0058] Figure 5 Schematic diagram of the radar local spatial positioning and automated operation system of the fully automated bridge health detection beam bottom robot in the present invention;

[0059] (a) Radar local spatial positioning and automated operation system; (b) Schematic diagram of the robot's trajectory at the bottom of the beam; (c) Schematic diagram of the radar local spatial positioning and automated operation trajectory;

[0060] Figure 6 The present invention is based on the dual millimeter wave radar and reflective target working diagram of the fully automated bridge health detection beam bottom robot;

[0061] (a) The robot at the bottom of the beam is at the right support; (b) The robot at the bottom of the beam has dual radars working; (c) The robot at the bottom of the beam switches to working with different radars; (d) The robot at the bottom of the beam has a single radar working; (e) The robot at the bottom of the beam is at the left support;

[0062] Figure 7 This invention is based on a schematic diagram of information collected by a fully automated bridge health detection beam bottom robot.

[0063] In the attached figure: 1- full-span deflection and damage detection device; 101- wheels; 102- control motor; 103- rotary encoder; 104- tilt sensor; 105- camera; 106- light hood; 107- ring light bar; 108- spring; 109- pressure sensor; 110- controller; 2- radar local space positioning and automatic operation system; 201- aircraft body; 202- front and rear dual millimeter-wave radars; 203- reflective target; 204- solar charging station. DETAILED DESCRIPTION

[0064] The present invention will be described in further detail below with reference to the accompanying drawings.

[0065] Traditional bridge monitoring methods rely primarily on regular manual inspections or single sensors, which present numerous limitations. The accuracy of manual inspection data is affected by the operator's experience; single sensors, such as strain gauges and accelerometers, can only obtain partial data, and their service life is significantly affected by operating hours and the working environment. For example, piezoelectric accelerometers fail due to prolonged current overload, and the accuracy of data detection in harsh environments is affected. These traditional methods are time-consuming and labor-intensive to detect full-span deflection and damage. Existing drone damage identification methods have shortcomings in terms of accurate positioning of damage locations and the quality of acquired images. Therefore, there is an urgent need for an automated system that can accurately detect full-span deflection and damage across bridges and precisely locate damage locations.

[0066] See also Figure 1-Figure 5 The fully automated bridge health inspection robot for bottom beams according to the embodiment of the present invention includes:

[0067] The full-span deflection and damage detection device 1 consists of a wheel 101, a control motor 102, a rotary encoder 103, an inclination sensor 104, a camera 105, a light shield 106, a ring light bar 107, a spring 108, a pressure sensor 109, and a controller 110; the wheel 101 is driven by the control motor 102, the rotary encoder 103 collects the rotation angle of the wheel 101, the inclination sensor 104 can monitor the inclination angle of the full-span deflection and damage detection device 1, and the light shield 106 and the ring light bar 107 provide a stable image for the camera 105. In the acquisition environment, wheels 101 rest against the bottom of the bridge, ensuring that the camera 105 captures images with fixed zoom parameters, facilitating accurate damage assessment later. Four springs 108 are installed above the pressure sensor 109, allowing the full-span deflection and damage detection device 1 to deflect while maintaining the wheel 101 in close contact with the beam bottom, facilitating accurate angle readings. The pressure sensor 109 transmits pressure data to the controller 110. When the pressure data is within the controller 110's preset range, the fully automated bridge health monitoring beam bottom robot begins deflection and damage detection. In this embodiment of the present invention, the vehicle body 201 provides power and support for the autonomous operation of the full-span deflection and damage detection device 1. Front and rear dual millimeter-wave radars 202 are mounted on either side of the vehicle body 201, slightly below the vehicle body, ensuring a stable center of gravity and preventing displacement during operation. Four reflective targets 203 are arranged in pairs on the two side supports. The front and rear dual millimeter-wave radars 202, in conjunction with the four reflective targets 203, provide precise local spatial positioning for the vehicle body 201 and transmit this positioning information to the controller 110 in real time. The controller 110 can preset the operation detection space trajectory of the fully automated bridge health detection beam bottom robot and the space trajectory for heading to the solar charging pile 204, thereby realizing automated operation.

[0068] The rotary encoder 103 is used to measure the rotation angle θ of the wheel 101 in real time and transmit the measured angle value to the controller 110. When the controller 110 detects that the rotation angle increment reaches the threshold θ1, it simultaneously records the bottom inclination angle θ collected by the inclination sensor 104 at this time. 2i , and the image data collected by the camera 105, i is the number of times the increment reaches θ1 after the start of measurement, and the robot forward distance increment ΔL corresponding to the i-th angle increment θ1 is calculated by the triangle geometry measurement principle i and deflection increment ΔF i The system adds the current calculated value to the historical accumulated actual deflection value and actual forward distance, thereby obtaining the actual forward distance parameter L based on the rotation angle θ1. i And the actual deflection value F i， The specific calculation formula is:

[0069]

[0070] ΔF i =L θ1 sinθ 2i ;

[0071]

[0072] i=1, 2, 3, ... n;

[0073] The high-precision measurement of the inclination sensor 104 ensures the accuracy of the deflection calculation and can accurately reflect the vertical deformation of the bridge in service.

[0074] The full-span deflection and damage detection device 1, the front and rear dual millimeter-wave radars 202, and the four reflective targets 203 are used to accurately spatially position the fully automated bridge health detection beam bottom robot, thereby accurately spatially positioning each beam bottom position corresponding to the deflection data and image data. The initial position detected by the full-span deflection and damage detection device 1 is the bridge support. The horizontal distance y from the beam bottom robot to the support at this time is obtained by the following formula i ,

[0075] Δy i =cosθ 2i ΔL i ;

[0076]

[0077] i=1,2,3...n;

[0078] The two millimeter-wave radars 202 are respectively identified with two reflection targets 203 arranged on the same side of the bridge support, and the straight-line distance between the millimeter-wave radar 202 and the two reflection targets 203 is measured. One of the reflection targets 203 is used as the origin of the spatial coordinate system. The y-axis of the spatial coordinate system is perpendicular to the mid-span section, the z-axis is perpendicular to the horizontal plane, and the x-axis is perpendicular to the yz plane. Assuming that the distance between the millimeter-wave radar 202 and one of the reflection targets 203 is d1, and the distance between the millimeter-wave radar 202 and the other reflection target 203 is d2, and the spatial coordinates of the two reflection targets 203 are (x1, y1, z1) and (x2, y2, z2), respectively, the local spatial coordinates (x, y, z) of the millimeter-wave radar 202 can be solved by the following equation:

[0079] (x-x1) 2 +(y-y1) 2 +(z-z1) 2 =d1 2 ;

[0080] (x-x2) 2 +(y-y2) 2 +(z-z2) 2 =d2 2 ;

[0081] y=y i ,z=F i +h;

[0082] Among them, (x1, y1, z1) and (x2, y2, z2) can be known through measurement, and h is the height difference in the z direction between the reflective target 203 and the initial position detected by the fully automated bridge health inspection beam bottom robot. Later, a three-dimensional model of the inspected bridge can be established, and the spatial coordinates of each position of the beam bottom, the corresponding deflection data and image data can be fused and integrated with the three-dimensional model to facilitate more intuitive expression of various data.

[0083] See also Figure 6The dual front and rear millimeter-wave radars 202 and four reflective targets 203 are designed to compensate for the limited beam angle of the millimeter-wave radars 202. When the fully automated bridge health inspection beam-bottom robot begins inspection at a bridge support on one side, the millimeter-wave radar 202 and reflective target 203 set farther from that support are activated to determine the spatial coordinates of the fully automated bridge health inspection beam-bottom robot. When the fully automated bridge health inspection beam-bottom robot approaches the midspan, both sets of millimeter-wave radars 202 and reflective target 203 are activated. When the spatial coordinates of the two millimeter-wave radars 202 are identical, indicating that the fully automated bridge health inspection beam-bottom robot has reached the midspan of the bridge being inspected, the millimeter-wave radar 202 and reflective target 203 set activated initially are deactivated, and the millimeter-wave radar 202 and reflective target 203 set on the other side of the fully automated bridge health inspection beam-bottom robot—that is, the millimeter-wave radar 202 and reflective target 203 set closer to the initial position—are activated for spatial positioning.

[0084] See also Figure 7 The front and rear dual millimeter-wave radars 202 and the four reflective targets 203 can spatially locate the full-span deflection and damage detection device 1. Whenever the full-span deflection and damage detection device 1 collects deflection data and image data, the controller 110 will receive these two sets of data and match the spatial coordinates (x, y, z) of the corresponding position of the data with the data and store them.

[0085] A method for using a fully automated bridge health inspection beam bottom robot:

[0086] 3. Equipment Installation

[0087] 1. Install four reflective targets 203 at the supports on both sides of the bridge to ensure that they are accurately positioned and firmly fixed, so as to provide accurate spatial positioning reference for the fully automated bridge health inspection beam bottom robot (hereinafter referred to as the "beam bottom robot").

[0088] 2. Select a suitable location to install the solar charging station 204, usually near one end of the bridge, to ensure that the robot at the bottom of the beam can return smoothly to charge after the mission is completed, while ensuring that it has good sunlight conditions to maintain sufficient power supply.

[0089] 3. Move the beam bottom robot to the vicinity of the bridge, and manually control its aircraft body 201 to rise to the vicinity of the bottom of the bridge, so that the wheels 101 of the full-span deflection and damage detection device 1 gently lean against the bottom of the beam, completing the initial position deployment.

[0090] 4. Preliminary spatial coordinate collection

[0091] 1. The robot is manually controlled to move along the beam bottom, utilizing the front and rear dual millimeter-wave radars 202 and reflective targets 203 to perform preliminary spatial coordinate acquisition of the beam bottom. During this process, the tilt sensor 104 monitors the beam bottom's tilt angle in real time, while the camera 105 simultaneously captures image data of the beam bottom. A light shield 106 and annular light bar 107 ensure a stable image acquisition environment. The pressure sensor 109 monitors the contact pressure between the wheels 101 and the beam bottom and transmits this data to the controller 110.

[0092] 2. The controller 110 receives and stores the initially collected spatial coordinate data, which will serve as an important basis for the subsequent running trajectory preset.

[0093] 3. Running track preset

[0094] 1. Based on the initially collected spatial coordinates of the beam bottom, combined with the bridge design drawings and inspection requirements, the controller 110 presets the beam bottom robot's spatial trajectory for inspection. Using dedicated software or programming, the trajectory is divided into multiple key collection points. The coordinate position, inspection task (deflection measurement, image acquisition), and corresponding instructions (such as the rotation speed of wheels 101 and the resolution of camera 105) of each collection point are clearly defined. A return trajectory is also preset for the robot to the solar charging station 204 to ensure that it can accurately return to charge when the mission is completed or the battery is low.

[0095] 4. Positioning and starting of the bottom beam robot

[0096] 1. After completing the preset trajectory, the robot is manually controlled to move to the starting position along the preset trajectory. During the movement, the millimeter wave radar 202 and the reflective target 203 are continuously used for position correction to ensure that the robot accurately reaches the preset starting point.

[0097] 2. When the robot reaches the preset starting point and the pressure sensor 109 detects that the contact pressure between the wheel 101 and the bottom of the beam is within the preset range of the controller 110, it indicates that the robot is in place and in a stable state. At this time, the automated working program of the robot at the bottom of the beam is started, and the robot will automatically start working according to the preset running detection space trajectory.

[0098] 5. Automated testing

[0099] 1. The robot automatically moves along the preset trajectory. The wheel 101 moves along the bottom of the beam driven by the control motor 102. The rotary encoder 103 monitors the rotation angle θ of the wheel 101 in real time and transmits it to the controller 110. When the rotation angle increment reaches the threshold θ1, the controller 110 synchronously records the bottom beam tilt angle θ collected by the tilt sensor 104. 2iThe image data collected by the camera 105 is used to calculate the robot's forward distance increment ΔL corresponding to the position by using the triangle geometry measurement principle. i and deflection increment ΔF i The system adds the current calculated value and the historical accumulated data to obtain the actual forward distance parameter L i And the actual deflection value F i , to realize the detection of deflection at various positions of the full span bridge.

[0100] 2. The front and rear dual millimeter-wave radars 202 continuously interact with the reflective targets 203, updating the robot's spatial coordinates in real time to ensure accurate detection. When the robot approaches the mid-span of the bridge, the millimeter-wave radar 202 and reflective target 203 on the other side are activated to continue precise positioning and detection. Simultaneously, the controller 110 continuously matches and stores the collected deflection data and image data with the spatial coordinates (x, y, z) of the corresponding locations, providing foundational data for subsequent construction of a three-dimensional bridge model and data fusion.

[0101] 6. Mission End and Recharge

[0102] 1. After the beam bottom robot completes the preset full-span inspection task, the controller 110 automatically controls the aircraft body 201 to fly toward the solar charging pile 204 according to the preset return trajectory.

[0103] 2. After the robot 201 reaches the solar charging station 204, it precisely docks with the charging port, and charging begins. Simultaneously, the robot transmits the stored inspection data to a backend server for further analysis and assessment of the bridge's health, thus completing the inspection mission. During the charging process, the robot remains in standby mode, responding to pre-set activation times to receive new inspection instructions.

[0104] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A fully automated bridge health inspection beam bottom robot, characterized in that: include: A full-span deflection and damage detection device (1) is provided. The full-span deflection and damage detection device (1) is composed of a wheel (101), a control motor (102), a rotary encoder (103), an inclination sensor (104), a camera (105), a light shield (106), a ring light bar (107), a spring (108), a pressure sensor (109), and a controller (110). The wheel (101) is driven by the control motor (102). The rotary encoder (103) collects the rotation angle of the wheel (101). The inclination sensor (104) can monitor the inclination angle of the full-span deflection and damage detection device (1). The camera (105) collects beam bottom image data. The light shield (106) is used to detect the rotation angle of the wheel (101). 106) and the annular light bar (107) provide a stable image acquisition environment for the camera (105), the wheel (101) is against the bottom of the bridge, so that the camera (105) takes an image with a fixed zoom parameter, thereby facilitating accurate measurement of the degree of damage in the later stage, four springs (108) are installed above the pressure sensor (109), so that the full-span deflection and damage detection device (1) can be deflected while the wheel (101) is close to the bottom of the beam, thereby facilitating angle measurement, the pressure sensor (109) transmits pressure data to the controller (110), and when the pressure data is within the preset value range of the controller (110), the fully automated bridge health detection beam bottom robot starts deflection and damage detection; A radar local space positioning and automatic operation system (2) includes an aircraft body (201), front and rear dual millimeter wave radars (202), four reflective targets (203), a controller (110), and a solar charging pile (204). The aircraft body (201) is a carrier of the full-span deflection and damage detection device (1) and provides an upward lift for the full-span deflection and damage detection device (1). The front and rear dual millimeter wave radars (202) are installed on both sides of the aircraft body (201). The aircraft body (201) is positioned slightly downward to ensure that the center of gravity of the aircraft body (201) is centered, and four reflective targets (203) are arranged in pairs at the supports on both sides; the front and rear dual millimeter wave radars (202) cooperate with the four reflective targets (203) to provide local precise spatial positioning for the aircraft body (201), and transmit the spatial positioning to the controller (110) in real time. The controller (110) can preset the operation detection spatial trajectory of the fully automated bridge health detection beam bottom robot and the spatial trajectory to the solar charging pile (204), thereby realizing automated operation.

2. The fully automated bridge health inspection beam bottom robot according to claim 1 is characterized by: The rotary encoder (103) is used to measure the rotation angle θ of the wheel (101) in real time and transmit the measured angle value to the controller (110). When the controller (110) detects that the rotation angle increment reaches the threshold value θ1, the bottom inclination angle θ collected by the inclination sensor (104) is synchronously recorded. 2i , and the image data collected by the camera (105), i is the number of times the increment reaches θ1 after the start of measurement, and the robot forward distance increment ΔL corresponding to the i-th angle increment θ1 is calculated by the triangle geometry measurement principle i and deflection increment ΔF i The system adds the current calculated value to the historical accumulated actual deflection value and actual forward distance, thereby obtaining the actual forward distance parameter L based on the rotation angle θ1. i And the actual deflection value F i , the specific calculation formula is: ΔF i =L θ1 ·sinθ 2i ; i=1, 2, 3, ... n; The high-precision measurement of the tilt sensor (104) ensures the accuracy of the deflection calculation and can accurately reflect the vertical deformation of the bridge in service.

3. The fully automated bridge health inspection beam bottom robot according to claim 1, characterized in that: The full-span deflection and damage detection device (1), the front and rear dual millimeter-wave radars (202), and the four reflective targets (203) are used to accurately spatially position the fully automated bridge health detection beam bottom robot, thereby accurately spatially positioning each beam bottom position corresponding to the deflection data and image data. The initial position detected by the full-span deflection and damage detection device (1) is the bridge support. The horizontal distance y from the beam bottom robot to the support at this time is obtained by the following formula: i , Δy i =cosθ 2i ·ΔL i ; i=1,2,3...n; Two millimeter-wave radars (202) are respectively identified with two reflection targets (203) arranged on the same side of the bridge support, and the straight-line distance between the millimeter-wave radar (202) and the two reflection targets (203) is measured. One of the reflection targets (203) is used as the origin of a spatial coordinate system. The y-axis of the spatial coordinate system is perpendicular to the mid-span section, the z-axis is perpendicular to the horizontal plane, and the x-axis is perpendicular to the yz plane. Assuming that the distance between the millimeter-wave radar (202) and one of the reflection targets (203) is d1, and the distance between the millimeter-wave radar (202) and the other reflection target (203) is d2, and the spatial coordinates of the two reflection targets (203) are (x1, y1, z1) and (x2, y2, z2), respectively, the local spatial coordinates (x, y, z) of the millimeter-wave radar (202) can be solved by the following equation: (x-x1) 2 +(y-y1) 2 +(z-z1) 2 =d1 2 4 (x-x2) 2 +(y-y2) 2 +(z-z2) 2 =d2 2 ; y=y i ,z=F i +h; Among them, (x1, y1, z1), (x2, y2, z2) can be known through measurement, and h is the height difference in the z direction between the reflective target (203) and the initial position detected by the fully automated bridge health detection robot at the bottom of the beam. In the later stage, a three-dimensional model of the inspected bridge can be established, and the spatial coordinates of each position at the bottom of the beam, the corresponding deflection data and the image data can be fused and integrated with the three-dimensional model to facilitate more intuitive expression of each data.

4. The fully automated bridge health inspection beam bottom robot according to claim 1, characterized in that: The front and rear dual millimeter-wave radars (202) and the four reflection targets (203) are used to compensate for the limited beam angle of the millimeter-wave radar (202). When the fully automated bridge health detection beam bottom robot starts detection from a bridge support on one side, the millimeter-wave radar (202) and the reflection target (203) group farther away from the support are activated to locate the spatial coordinates of the fully automated bridge health detection beam bottom robot. When the fully automated bridge health detection beam bottom robot approaches the mid-span, both sets of millimeter wave radars (202) and reflection target (203) devices are activated. When the spatial coordinates of the two millimeter wave radars (202) are the same, it means that the fully automated bridge health detection beam bottom robot has reached the mid-span position of the detected bridge. Then, the millimeter wave radar (202) and reflection target (203) set activated in the initial stage are turned off, and the millimeter wave radar (202) and reflection target (203) set on the other side of the fully automated bridge health detection beam bottom robot are activated for spatial positioning, that is, the millimeter wave radar (202) and reflection target (203) set close to the initial position side is activated.

5. The fully automated bridge health inspection beam bottom robot according to claim 2, characterized in that: The front and rear dual millimeter-wave radars (202) and the four reflective targets (203) can spatially locate the full-span deflection and damage detection device (1). Whenever the full-span deflection and damage detection device (1) collects deflection data and image data, the controller (110) receives the two sets of data and matches and stores the spatial coordinates (x, y, z) of the corresponding position of the data.

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