Bridge disease monitoring method based on inspection robot

Abstract

The present invention relates to the technical field of bridge structure monitoring, and specifically to a bridge disease monitoring method based on an inspection robot, comprising: obtaining a BIM model of a bridge, collecting GIS data of a location of the bridge and establishing associations with elements in the BIM model, and integrating the BIM model and the GIS data into a BIM+GIS fusion model; configuring a sensor and a communication module in the inspection robot, building a Web platform and establishing a communication connection with the inspection robot; when the inspection robot inspects the bridge, real-time data is collected through sensors, and the collected bridge structure data and position data of the inspection robot are sent to the Web platform; the Web platform receives and parses the position data, searches for a component corresponding to the position data in the BIM+GIS fusion model according to the position data, and maps the real-time position of the inspection robot to the corresponding component, thereby realizing accurate positioning and dynamic visualization of the position of the inspection robot.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge structure monitoring, and in particular to a bridge disease monitoring method based on an inspection robot. Background Art

[0002] With the acceleration of urbanization, bridges, as an important part of transportation infrastructure, are directly related to the safety of life and property of the public. The traditional manual inspection method is inefficient, costly and has potential safety hazards. In recent years, with the development of the Internet of Things, automation technology and computer graphics, it has become possible to use inspection robots for bridge inspection, which not only improves work efficiency but also reduces the risks of manual inspection.

[0003] However, there is currently a lack of a solution on the market that can monitor and intuitively display the position of the inspection robot during the inspection process in real time. Summary of the invention

[0004] The purpose of the present invention is to propose a bridge disease monitoring method based on a patrol robot to solve the problems raised in the background technology. To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0005] A bridge disease monitoring method based on an inspection robot, the monitoring method comprising the following steps:

[0006] Obtain the BIM model of the bridge, collect GIS data of the bridge location and establish associations with elements in the BIM model, and use BIM and GIS integration tools to integrate the BIM model and GIS data into a BIM+GIS fusion model;

[0007] Configure sensors and communication modules in the inspection robot, build a Web platform that supports multiple communication protocols, and establish a communication connection with the inspection robot to receive and process data from the inspection robot;

[0008] When the inspection robot starts to inspect the bridge, it collects real-time data through sensors, packages the collected bridge structure data and the inspection robot's position data in a predetermined format, and sends them to the Web platform through the communication module;

[0009] The Web platform receives and parses the location data, searches for components corresponding to the location data in the BIM+GIS fusion model based on the location data, and maps the real-time position of the inspection robot to the corresponding component.

[0010] A further improvement is that the Web platform receives location data and parses it including:

[0011] Determine whether the coordinate system used by the inspection robot when collecting data is consistent with the coordinate system in the BIM+GIS fusion model. If not, perform coordinate transformation on the position data to make it match the coordinate system in the BIM+GIS fusion model.

[0012] A further improvement is that the monitoring method further comprises:

[0013] The BIM+GIS fusion model is rendered and displayed on the Web platform using WebGL three-dimensional visualization technology. The position of the inspection robot in the actual bridge structure is presented on the BIM+GIS fusion model in an intuitive and visual way. A user-friendly interactive interface is designed to allow users to browse the entire bridge model and view the position of the inspection robot from different perspectives by simply clicking and dragging.

[0014] A further improvement is that the monitoring method further comprises:

[0015] When the inspection robot is located in the internal structure of a bridge or other complex parts, a cutaway view is generated to more clearly show the location of the inspection robot and its surrounding environment.

[0016] A further improvement is that the method for generating a cutaway view is:

[0017] A variety of cutting plane options are provided on the web interface, including horizontal plane, vertical plane, and inclined plane, allowing users to draw cutting paths of any shape with a mouse or stylus, and flexibly intercept areas of interest. When users adjust cutting parameters, the preview window is immediately updated to show the effect after cutting;

[0018] Generate the corresponding section view in the BIM+GIS fusion model according to the cutting surface or path selected by the user. In this process, add animation effects to smoothly show the transformation process from the original model to the section view, and add annotations and instructions on the section view, including size, material, and construction details.

[0019] The introduction of global illumination and shadow projection rendering technology makes the cross-section view look more realistic. By adjusting the position and intensity of the light source to highlight important parts, the user is allowed to adjust the transparency of different layers in the cross-section view to observe the structure hidden inside. Different colors are used to represent various components or materials to enhance recognition. The color is dynamically adjusted according to changes in temperature and stress to reflect the actual working conditions, helping users better understand the environment around the inspection robot.

[0020] A further improvement is that after the Web platform and the inspection robot establish a communication connection, a step of testing the communication link is also included. The specific method of testing the communication link includes:

[0021] Connectivity test: Use the ping command or network diagnostic tools to check the connectivity between the robot and the Web platform, observe the packet loss rate and delay, and evaluate the network quality;

[0022] Data transmission test: Write a simple client program to simulate the inspection robot to send a small amount of test data to the server, record the receiving status, and check the data integrity, sequence and timeliness;

[0023] Exception handling test: intentionally disconnect the network connection or shut down the server, observe how the system responds, and test the reconnection mechanism, error recovery logic, and alarm notification function.

[0024] A further improvement is that the method of building a web platform that supports multiple communication protocols includes:

[0025] Server setup: Choose a cloud service provider or self-built server to deploy web applications;

[0026] API interface design: define RESTful API interfaces and follow open standards so that front-end applications can easily call back-end services;

[0027] Database design: Create a relational database or NoSQL database to store the inspection robot's historical data, user information, and other metadata, design a reasonable table structure and index, and optimize query efficiency;

[0028] Security measures: Protect the secure transmission and storage of sensitive information through identity authentication, authorization mechanisms and data encryption.

[0029] A further improvement is that the method of mapping the real-time position of the inspection robot to the corresponding component includes:

[0030] Icon display: Add an icon representing the inspection robot to the corresponding component of the BIM+GIS fusion model, and set its position to the resolved coordinate value;

[0031] Path tracking: As the robot continues to move, its position display in the BIM+GIS fusion model is continuously updated, and the coordinates of the icon are continuously updated to form a continuous path, visually displaying the inspection route of the inspection robot.

[0032] A further improvement is that the communication protocol between the Web platform and the inspection robot adopts any one of the HTTP protocol, WebSocket protocol, MQTT protocol, and CoAP protocol.

[0033] A further improvement is that the method of real-time data collection through sensors includes:

[0034] Initialize sensors: Calibrate and configure each sensor through the written initialization code;

[0035] Start data flow: Once the inspection robot is started, the data collection process of all sensors is immediately started, and multi-threaded programming technology is used to improve concurrent processing capabilities and reduce delays; Time synchronization: Use the NTP protocol or built-in RTC to maintain time consistency and ensure that the timestamps of all sensors are accurate.

[0036] The beneficial effects of the present invention are:

[0037] After receiving the position data of the inspection robot through the Web platform, the present invention will parse it to determine the current exact position of the inspection robot, and then based on the parsed position data, the Web platform can find the corresponding bridge component in the BIM+GIS fusion model, associate the position data transmitted by the inspection robot with the elements in the BIM+GIS fusion model, find the corresponding component in the BIM+GIS fusion model, and the Web platform maps the real-time position of the inspection robot to the corresponding component in the BIM+GIS fusion model. In this way, the user can intuitively see the real-time inspection position of the inspection robot and can also record the historical inspection path, thereby realizing the accurate positioning and dynamic visualization of the inspection robot's position, and bringing innovation to bridge management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of the bridge disease monitoring method based on the inspection robot of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0041] Please refer to the attached Figure 1 The embodiment of the present invention proposes a bridge disease monitoring method based on a patrol robot, specifically an intelligent monitoring solution that combines Building Information Modeling (BIM) and Geographic Information System (GIS).

[0042] Specifically, the inspection robot can be a cable climbing robot for inspecting the defects of bridge cables; the inspection robot can also be a bottom inspection vehicle for steel box beams for inspecting the defects of bottom steel box beams of bridges. In addition, it can also be a robot for inspecting other specific parts of bridges.

[0043] like Figure 1 As shown, the monitoring method comprises the following steps:

[0044] Step S1: Obtain the BIM model of the bridge, collect GIS data of the bridge location and establish associations with elements in the BIM model, and use BIM and GIS integration tools to integrate the BIM model and GIS data into a BIM+GIS fusion model.

[0045] Specifically, you can contact the bridge construction unit or design institute to obtain the latest BIM model file (usually in IFC format), and use BIM and GIS integration tools (such as Autodesk InfraWorks, Bentley ContextCapture) to integrate the BIM model and GIS data into a BIM+GIS fusion model.

[0046] Step S2: configure sensors and communication modules in the inspection robot, build a Web platform that supports multiple communication protocols, and establish a communication connection with the inspection robot to receive and process data from the inspection robot.

[0047] Specifically, appropriate sensors can be selected according to needs, such as GPS modules (for obtaining geographic location), IMU (inertial measurement unit, used to detect posture and motion status), laser scanners, ultrasonic detectors, temperature / humidity sensors, cameras, etc. Equip the robot with a suitable communication module. For scenarios that require high stability and speed, fiber optic communication or wired cable transmission is given priority; for scenarios with high flexibility and easy deployment, wireless communication modules (such as Wi-Fi, 4G / 5G) can be used. In addition, a reliable power management system needs to be designed to ensure that the robot has sufficient power support when working for a long time. At the same time, a microcontroller or embedded computer is installed in the robot to collect data from various sensors and perform preliminary processing (such as filtering and calibration) before packaging and sending.

[0048] Step S3: When the inspection robot starts to inspect the bridge, real-time data is collected through sensors, and the collected bridge structure data and the inspection robot's position data are packaged in a predetermined format and sent to the Web platform through the communication module.

[0049] Specifically, when the inspection robot moves on the bridge along a predetermined path, it will continuously collect data on the bridge structure and its own location information through the sensors it carries. The inspection robot will package the collected data in a predefined format and can perform operations such as data compression and encryption to ensure data security and efficiency. The packaged data will select the most appropriate communication method based on actual conditions to ensure timely transmission of the data.

[0050] Step S4: The Web platform receives and parses the location data, searches for components corresponding to the location data in the BIM+GIS fusion model based on the location data, and maps the real-time position of the inspection robot to the corresponding component.

[0051] Specifically, after receiving the location data of the inspection robot, the Web platform will parse it to determine the current exact location of the inspection robot to determine which part of the bridge the robot is currently located in. Then, based on the parsed location data, the Web platform can find the corresponding bridge components in the BIM+GIS fusion model and associate the location data transmitted by the inspection robot with the elements in the BIM+GIS fusion model. For example, based on the cable number of the robot, the distance from the bridge pier and other information, the Web platform finds the corresponding cable component in the BIM+GIS fusion model. The Web platform maps the real-time location of the inspection robot to the corresponding component in the BIM+GIS fusion model. In this way, users can intuitively see the real-time inspection position of the inspection robot and record historical inspection paths, thus realizing the precise positioning and dynamic visualization of the inspection robot's position, which has brought innovation to bridge management.

[0052] In a preferred solution of this embodiment, in step S4, the Web platform receives the location data and performs analysis including:

[0053] Determine whether the coordinate system used by the inspection robot when collecting data is consistent with the coordinate system in the BIM+GIS fusion model. If not, perform coordinate transformation on the position data to make it match the coordinate system in the BIM+GIS fusion model.

[0054] Specifically, the coordinate conversion of location data to match the coordinate system in the BIM+GIS fusion model can be carried out in the following ways: Unified coordinate system: In order to ensure that data from different data sources can be analyzed and processed in the same coordinate system, coordinate conversion is required. First, a unified coordinate system is determined, such as the World Geodetic Coordinate System (WGS84). Spatial reference point matching: By finding some known spatial reference points, the data from different data sources are matched with these reference points to achieve coordinate conversion.

[0055] In a preferred solution of this embodiment, the monitoring method further includes:

[0056] The BIM+GIS fusion model is rendered and displayed on the Web platform using WebGL 3D visualization technology. The position of the inspection robot in the actual bridge structure is presented in an intuitive and visual way on the BIM+GIS fusion model. A user-friendly interactive interface is designed to allow users to browse the entire bridge model and view the position of the inspection robot from different perspectives through simple clicks and drags. Managers can view it directly through the browser without installing additional professional software.

[0057] It should be understood that WebGL (Web Graphics Library) is a JavaScript API that allows interactive 3D graphics to be rendered in web browsers without plug-ins. Using WebGL, high-performance, high-fidelity 3D visualizations can be created. Based on the WebGL framework (such as Three.js, Babylon.js), a virtual scene is built to accommodate the BIM+GIS fusion model. This scene can include elements such as lighting, materials, textures, etc. to provide more realistic visual effects. As the inspection robot moves on its path, the Web platform receives and parses its position data in real time and performs coordinate conversion as needed (as described above). The updated robot position information is then applied to the BIM+GIS fusion model. In the WebGL scene, the current position of the inspection robot is represented by animation or other forms of dynamic display. For example, an icon or model representing the robot can be added to the model and moved as the actual position changes.

[0058] In a preferred solution of this embodiment, the monitoring method further includes: realizing static digital simulation and digital twins through open USD and Omniverse platforms. The specific method is as follows: Model import: import the BIM+GIS fusion model and the model of the inspection robot into the Omniverse platform using the universal scene description language (OpenUSD); Scene construction: use the powerful functions of the Omniverse platform to build a realistic virtual scene, and perform visual digital simulation and digital twins; Data connection: connect the data collected by the inspection robot with the model imported by modeling to realize real-time data-driven digital twin display.

[0059] In a preferred solution of this embodiment, the monitoring method further includes:

[0060] When the inspection robot is located in the internal structure of a bridge or other complex parts, a cutaway view is generated to more clearly show the location of the inspection robot and its surrounding environment.

[0061] It is understandable that the cross-section view function is introduced to enhance the visualization of the internal structure of the bridge or other complex parts, so as to more clearly show the location of the inspection robot and its surrounding environment.

[0062] Specifically, the method for generating a cut view is:

[0063] A variety of cutting plane options are provided on the web interface, including but not limited to horizontal planes, vertical planes, and inclined planes. These options can be provided through preset buttons or drop-down menus, which are convenient for users to quickly select. Allow users to draw cutting paths of any shape through the mouse or stylus, and flexibly intercept the area of ​​interest, which can be a straight line, curve, or free-form polygon to meet the needs of different scenarios. When the user adjusts the cutting parameters (such as the angle and position of the plane, the shape of the path, etc.), the preview window is immediately updated to show the effect after cutting, which ensures that users can see the changes instantly during the operation, making it easier to find the best cutting solution.

[0064] According to the cutting surface or path selected by the user, the corresponding section view is generated in the BIM+GIS fusion model. In this process, animation effects are added to smoothly display the transition process from the original model to the section view. This can give users a continuous visual experience and help them better understand spatial relationships. Annotations and descriptions are added to the section view, including information such as size, material, and construction details. These annotations can help users quickly identify key components and features, and provide detailed technical data when needed.

[0065] The introduction of global illumination and shadow projection rendering technology makes the cross-section view look more realistic. By simulating the real light propagation, a more natural light and dark contrast can be created, highlighting important parts and increasing the depth of the picture. By adjusting the position and intensity of the light source to highlight important parts, the user is allowed to adjust the transparency of different layers in the cross-section view to observe the structure hidden inside. Different colors are used to represent various components or materials to enhance recognition. According to the changes in temperature and stress, the color is dynamically adjusted to reflect the actual working conditions. For example, a thermal map is used to reflect the temperature distribution, or a color gradient is used to represent the stress level. This dynamic color change can help users intuitively understand the environmental conditions around the inspection robot.

[0066] In a preferred solution of this embodiment, in step S2, after the Web platform establishes a communication connection with the inspection robot, a step of testing the communication link is also included. The specific method of testing the communication link includes:

[0067] Connectivity test: Use the ping command or network diagnostic tools to check the connectivity between the robot and the Web platform, observe the packet loss rate and latency, and evaluate the network quality.

[0068] It should be understood that by sending an ICMP Echo request (i.e. "ping") to the inspection robot, it is possible to verify whether there is a valid network path between the two. Execute the ping <robot IP address> command from the Web platform or monitoring terminal to check whether there is packet loss. Ideally, the packet loss rate is 0%. Record the round-trip time (RTT) to evaluate network latency. Lower latency means better network performance. Observe the degree of latency variation. Excessive jitter may affect the quality of real-time data transmission. In addition to ping, other network diagnostic tools such as Traceroute, MTR (MyTraceroute), etc. can be used to deeply analyze each node on the network path and identify the links that may cause problems.

[0069] Data transmission test: Write a simple client program to simulate the inspection robot sending a small amount of test data to the server, record the reception status, and check the data integrity, sequence, and timeliness.

[0070] It should be understood that a simple client program can be developed to simulate the inspection robot sending a small amount of test data to the Web platform. This program should be able to configure the amount, frequency and format of data sent to cover different application scenarios. The specific operation is: start the client program and send the test data packet according to the preset parameters. Verify integrity: Receive and verify data on the server side to ensure that all sent data can arrive intact and without error. Checksum, hash value and other methods can be used to verify the integrity of the data; Verify sequence: Check whether the received data packets are arranged in the order of sending. For an ordered data stream, any disorder may be a sign of a network problem. Verify timeliness: Measure the time difference from sending to receiving to evaluate the timeliness of data transmission.

[0071] Exception handling test: intentionally disconnect the network connection or shut down the server, observe how the system responds, and test the reconnection mechanism, error recovery logic, and alarm notification function.

[0072] It should be understood that by simulating network failure scenarios, such as unplugging the network cable, turning off the Wi-Fi router, etc., observe how the system responds to such abnormal situations. Specifically, detect the reconnection mechanism: test the automatic reconnection function of the inspection robot to confirm that it can quickly re-establish the connection with the Web platform after the network is restored; detect the error recovery logic: check whether the system can correctly handle unfinished data transmission, such as resending lost data packets, or skipping unrecoverable errors to continue working. By simulating server-side failures, such as shutting down the Web platform process or restarting the server, the fault tolerance of the system can be tested. Specifically, detect alarm notifications: ensure that when the server is detected to be unavailable, the system can promptly issue an alarm to notify relevant personnel. This can be achieved through email, SMS, instant messaging, etc.; detect status monitoring: set up a status monitoring page or dashboard to display the online status of the server and inspection robot in real time to help administrators quickly locate and solve problems.

[0073] In a preferred solution of this embodiment, a method for building a Web platform supporting multiple communication protocols includes:

[0074] Server setup: Choose a cloud service provider (such as AWS, Azure, Alibaba Cloud) or build your own server to deploy Web applications. The server needs to have good computing power and storage space.

[0075] API interface design: Define RESTful API interfaces and follow open standards (such as OpenAPISpecification) so that front-end applications can easily call back-end services.

[0076] Database design: Create a relational database (such as MySQL, PostgreSQL) or a NoSQL database (such as MongoDB) to store the inspection robot's historical data, user information, and other metadata, design a reasonable table structure and index, and optimize query efficiency.

[0077] Security measures: Protect the secure transmission and storage of sensitive information through authentication (such as OAuth2.0), authorization mechanism (role-based access control) and data encryption (SSL / TLS).

[0078] In a preferred solution of this embodiment, in step S4, the method of mapping the real-time position of the inspection robot onto the corresponding component includes:

[0079] Icon display: Add an icon representing the inspection robot to the corresponding component of the BIM+GIS fusion model, and set its position to the resolved coordinate value.

[0080] Path tracking: As the robot moves, its position display in the BIM+GIS fusion model is continuously updated, and the coordinates of the icon are continuously updated to form a continuous path, which intuitively displays the inspection route of the inspection robot. At the same time, it has the playback function of the inspection route, allowing users to review the complete journey of the inspection robot, understand how it covers the entire bridge, and view problems found along the way.

[0081] It is understandable that an icon that is easily recognizable and coordinated with the bridge environment can be selected for the inspection robot. This icon can be a simple graphic (such as a car) or a more complex 3D model, depending on the user's preference and the performance requirements of the system.

[0082] The Web platform continuously receives location update information from the inspection robot. After parsing, this information is converted into a coordinate system suitable for the BIM+GIS fusion model (if coordinate conversion is required). Whenever new location data is received, the icon position is automatically updated so that the icon is always located on the component where the robot is currently located. This real-time update ensures that users can see the latest position of the robot more intuitively and in real time. As the inspection robot continues to move, by recording each location point, a path composed of multiple points is formed. These points can be connected by line segments to form a continuous path, which intuitively displays the inspection route of the inspection robot. The color, width and style of the path can be customized to highlight different types of inspection activities or distinguish different inspection stages. For example, different colors are used to represent normal inspections and sections where problems are found.

[0083] The present invention allows the user to review the complete itinerary of the inspection robot through the playback function of the inspection route. Through the animation effect, the robot is simulated to walk again along the actual path, so that the user can clearly see how it covers the entire bridge. In addition, interactive control buttons such as play, pause, fast forward, and fast rewind are provided, so that the user can flexibly operate the playback process according to their own needs. The speed adjustment option can also be set so that the user can view the inspection situation at different rates. During the playback process, when the inspection robot passes by a location where an abnormality or disease is found, a special mark can be added to the path or a prompt box can be popped up to display a detailed problem description and related data (such as pictures, videos, sensor readings, etc.).

[0084] In this embodiment, the communication protocol between the Web platform and the inspection robot adopts any one of the HTTP protocol, WebSocket protocol, MQTT protocol, and CoAP protocol.

[0085] It should be understood that HTTP protocol: When the robot uses HTTP protocol for data transmission, the Web platform can receive data through the server. HTTP protocol is simple and universal, and is suitable for non-real-time data transmission. For example, the robot can periodically send the collected data to the server in the form of HTTP requests, and the server stores and processes it after receiving it. WebSocket protocol: The WebSocket protocol can realize full-duplex communication between the client and the server, and can receive data sent by the robot in real time. It is suitable for scenarios with high real-time requirements, such as real-time monitoring and control of robots. MQTT protocol: MQTT is a lightweight message queue telemetry transmission protocol suitable for data transmission between IoT devices. The robot can act as a publisher to publish data to a specific topic, and the Web platform can act as a subscriber to receive data. This method can effectively reduce the network bandwidth occupancy and improve the efficiency of data transmission. CoAP protocol: Constrained Application Protocol (CoAP) is a protocol designed specifically for constrained devices, suitable for resource-constrained robots and low-power network environments. Those skilled in the art can select a communication protocol according to actual needs.

[0086] In a preferred solution of this embodiment, in step S3, the method for real-time data collection by sensors includes:

[0087] Initialize the sensor: Calibrate and configure each sensor through the written initialization code. For example, set the update frequency of GPS, the sampling rate of IMU, etc.

[0088] Start data flow: Once the inspection robot is started, the data collection process of all sensors is immediately started, and multi-threaded programming technology is used to improve concurrent processing capabilities and reduce delays.

[0089] Time synchronization: Use NTP protocol or built-in RTC (real-time clock) to maintain time consistency and ensure that the timestamps of all sensors are accurate.

[0090] In a preferred embodiment of the present invention, the monitoring method further comprises the following steps:

[0091] The introduction of machine learning algorithms enables the inspection robot to autonomously adjust the inspection speed, height and angle according to environmental changes (including weather conditions, traffic conditions) and task requirements. Specific implementation methods include:

[0092] First, data collection and preprocessing are carried out. Meteorological and traffic monitoring sensors are deployed around the bridge to collect weather (including temperature, humidity, wind speed, etc.) and traffic conditions (including traffic volume, speed, etc.) data in real time. At the same time, public data sources, including weather forecasts and traffic broadcast information, are integrated to obtain more comprehensive environmental data. These raw data are cleaned, noise and outliers are removed, and normalized to improve the training effect of the machine learning model.

[0093] Next, build and train the machine learning model. According to the complexity of the problem and the characteristics of the data, you can select the appropriate machine learning algorithm, such as decision tree, random forest or deep learning model, and use historical data to train the machine learning model so that it can accurately predict the impact of environmental changes on the inspection strategy of the inspection robot. Evaluate the performance of the model through methods such as cross-validation, and adjust the hyperparameters to optimize the model.

[0094] Then, an adjustment strategy for the patrol robot is formulated. According to the prediction results of the machine learning model, adjustment rules for the patrol robot's patrol speed, height, and angle under different weather and traffic conditions are formulated. The trained model is embedded into the control system of the patrol robot, enabling it to receive environmental data in real time and dynamically adjust the patrol strategy based on the prediction results.

[0095] Finally, evaluation and optimization are carried out. The inspection efficiency and data collection quality of the inspection robot are evaluated regularly. According to the evaluation results, the machine learning model, adjustment strategy and system are continuously optimized to improve the autonomous adjustment capability of the inspection robot and the comprehensiveness and accuracy of data collection, and the optimal inspection route and time are predicted based on weather and traffic flow.

[0096] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A bridge disease monitoring method based on an inspection robot, characterized in that: The monitoring method comprises the following steps: Obtain the BIM model of the bridge, collect GIS data of the bridge location and establish associations with elements in the BIM model, and use BIM and GIS integration tools to integrate the BIM model and GIS data into a BIM+GIS fusion model; Configure sensors and communication modules in the inspection robot, build a Web platform that supports multiple communication protocols, and establish a communication connection with the inspection robot to receive and process data from the inspection robot; When the inspection robot starts to inspect the bridge, it collects real-time data through sensors, packages the collected bridge structure data and the inspection robot's position data in a predetermined format, and sends them to the Web platform through the communication module; The Web platform receives and parses the location data, searches for components corresponding to the location data in the BIM+GIS fusion model based on the location data, and maps the real-time position of the inspection robot to the corresponding component.

2. A bridge disease monitoring method based on a patrol robot according to claim 1, characterized in that: The web platform receives location data and performs parsing including: Determine whether the coordinate system used by the inspection robot when collecting data is consistent with the coordinate system in the BIM+GIS fusion model. If not, perform coordinate transformation on the position data to make it match the coordinate system in the BIM+GIS fusion model.

3. A bridge disease monitoring method based on a patrol robot according to claim 1, characterized in that: The monitoring method further comprises: The BIM+GIS fusion model is rendered and displayed on the Web platform using WebGL three-dimensional visualization technology. The position of the inspection robot in the actual bridge structure is presented on the BIM+GIS fusion model in an intuitive and visual way. A user-friendly interactive interface is designed to allow users to browse the entire bridge model and view the position of the inspection robot from different perspectives by simply clicking and dragging.

4. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: The monitoring method further comprises: When the inspection robot is located in the internal structure of a bridge or other complex parts, a cutaway view is generated to more clearly show the location of the inspection robot and its surrounding environment.

5. A bridge disease monitoring method based on a patrol robot according to claim 4, characterized in that: To create a cut view: A variety of cutting plane options are provided on the web interface, including horizontal plane, vertical plane, and inclined plane, allowing users to draw cutting paths of any shape with a mouse or stylus, and flexibly intercept areas of interest. When users adjust cutting parameters, the preview window is immediately updated to show the effect after cutting; Generate the corresponding section view in the BIM+GIS fusion model according to the cutting surface or path selected by the user. In this process, add animation effects to smoothly show the transformation process from the original model to the section view, and add annotations and instructions on the section view, including size, material, and construction details. The introduction of global illumination and shadow projection rendering technology makes the cross-section view look more realistic. By adjusting the position and intensity of the light source to highlight important parts, the user is allowed to adjust the transparency of different layers in the cross-section view to observe the structure hidden inside. Different colors are used to represent various components or materials to enhance recognition. The color is dynamically adjusted according to changes in temperature and stress to reflect the actual working conditions, helping users better understand the environment around the inspection robot.

6. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: After the Web platform and the inspection robot establish a communication connection, the step of testing the communication link is also included. The specific method of testing the communication link includes: Connectivity test: Use the ping command or network diagnostic tools to check the connectivity between the robot and the Web platform, observe the packet loss rate and delay, and evaluate the network quality; Data transmission test: Write a simple client program to simulate the inspection robot to send a small amount of test data to the server, record the receiving status, and check the data integrity, sequence and timeliness; Exception handling test: intentionally disconnect the network connection or shut down the server, observe how the system responds, and test the reconnection mechanism, error recovery logic, and alarm notification function.

7. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: Methods for building a web platform that supports multiple communication protocols include: Server setup: Choose a cloud service provider or self-built server to deploy web applications; API interface design: define RESTful API interfaces and follow open standards so that front-end applications can easily call back-end services; Database design: Create a relational database or NoSQL database to store the inspection robot's historical data, user information, and other metadata, design a reasonable table structure and index, and optimize query efficiency; Security measures: Protect the secure transmission and storage of sensitive information through identity authentication, authorization mechanisms and data encryption.

8. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: Methods for mapping the real-time position of the inspection robot onto the corresponding component include: Icon display: Add an icon representing the inspection robot to the corresponding component of the BIM+GIS fusion model, and set its position to the resolved coordinate value; Path tracking: As the robot continues to move, its position display in the BIM+GIS fusion model is continuously updated, and the coordinates of the icon are continuously updated to form a continuous path, visually displaying the inspection route of the inspection robot.

9. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: The communication protocol between the Web platform and the inspection robot adopts any one of the HTTP protocol, WebSocket protocol, MQTT protocol, and CoAP protocol.

10. The bridge disease monitoring method based on the inspection robot according to claim 1 is characterized in that: Methods for real-time data collection through sensors include: Initialize sensors: Calibrate and configure each sensor through the written initialization code; Start data flow: Once the inspection robot starts, the data collection process of all sensors is immediately started, and multi-threaded programming technology is used to improve concurrent processing capabilities and reduce delays; Time synchronization: Use NTP protocol or built-in RTC to maintain time consistency and ensure that the timestamps of all sensors are accurate.

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