Intelligent bridge repairing system

Abstract

The application provides a kind of intelligent bridge repair system, including detection terminal, cloud service platform and management terminal;Wherein, detection terminal includes the image acquisition module on mobile device, image acquisition module is used to collect bridge surface image data in the process of mobile device patrol detection, and the bridge surface image data collected is transmitted to cloud service platform;Cloud service platform is used to carry out image analysis on bridge surface according to the bridge surface image data obtained, and the bridge damage analysis result obtained is transmitted to management terminal;Management terminal is used to remotely control on-site repair terminal according to the bridge damage analysis result obtained, so that on-site repair terminal can reach bridge damage site, and the damaged part is repaired.The application helps to reduce the working strength of the operator outdoors, and at the same time helps to reduce the labor cost of large-scale bridge comprehensive detection and repair, improves the efficiency and intelligent level of bridge repair.

Description

Technical Field

[0001] This invention relates to the field of bridge repair technology, and in particular to an intelligent bridge repair system. Background Technology

[0002] Currently, small cracks are prone to appear on the surface of bridges, such as concrete or asphalt structures like road surfaces and piers, due to various reasons such as construction or long-term neglect. If these small cracks are not repaired in time, they will gradually affect the quality and safety of the bridge.

[0003] Existing technologies include devices specifically designed for bridge surface damage detection and repair. However, most of these devices require multiple operators to operate and guide them during the inspection and repair process. For large bridges, operators need to work continuously outdoors, which increases the risk of heatstroke and other health problems. Furthermore, prolonged outdoor work reduces the efficiency of bridge repair. These technologies fail to meet the needs of modern, intelligent bridge damage detection and repair for large bridges. Summary of the Invention

[0004] To address the aforementioned problems, this invention aims to provide an intelligent bridge repair system.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] This invention proposes an intelligent bridge repair system, comprising: a detection terminal, a cloud service platform, and a management terminal;

[0007] The detection terminal includes an image acquisition module mounted on a mobile device. The image acquisition module is used to collect bridge surface image data during the patrol and detection process of the mobile device and transmit the collected bridge surface image data to the cloud service platform. The collected bridge surface image data carries corresponding positioning information.

[0008] The cloud service platform is used to perform image analysis on the bridge surface based on the acquired bridge surface image data, obtain bridge damage analysis results, and transmit the obtained bridge damage analysis results to the management terminal; the bridge damage analysis results contain the positioning information carried by the corresponding bridge surface image data;

[0009] The management terminal is used to remotely control the on-site repair terminal based on the obtained bridge damage analysis results, so that the on-site repair terminal can reach the bridge damage site and repair the damaged area.

[0010] Preferably, the system also includes a field repair terminal;

[0011] The on-site repair terminal is used to reach the site of bridge damage and complete the corresponding repair operations under the control of the management terminal according to the received remote control instructions.

[0012] Preferably, the mobile devices include dedicated intelligent bridge inspection vehicles, drones, crawling robots, etc.

[0013] Preferably, the image acquisition module includes an image acquisition unit, a positioning unit, and a data transmission unit;

[0014] The image acquisition unit is used to acquire image data of the bridge surface at a set angle during the patrol and inspection process of the mobile device;

[0015] The positioning unit is used to acquire the current positioning information and integrate the acquired positioning information into the collected bridge surface image data;

[0016] The data transmission unit is used to transmit bridge surface image data with integrated positioning information to the cloud service platform in real time via a wireless communication network.

[0017] Preferably, the cloud service platform includes an image receiving unit, a preprocessing unit, a target extraction unit, a damage analysis unit, and an output unit;

[0018] The image receiving unit is used to acquire bridge surface image data transmitted by the detection terminal;

[0019] The preprocessing unit is used to preprocess the received bridge surface image data, including standardization and enhancement adjustment, to obtain a preprocessed bridge surface image.

[0020] The target extraction unit is used to extract targets from the preprocessed bridge surface image and obtain the target detection area image of the bridge surface in the image;

[0021] The damage analysis unit is used to analyze the obtained target detection area image using a damage analysis model trained on a neural network, and obtain the damage analysis results of the front area of ​​the target.

[0022] The output unit is used to extract the positioning information carried in the corresponding bridge surface image when the damage analysis result is abnormal, integrate the obtained positioning information into the current abnormal damage analysis result, and transmit the damage analysis result to the management terminal.

[0023] Preferably, the management terminal includes a large-screen display module and a remote control module;

[0024] The large-screen display module is used to receive damage analysis results transmitted from the cloud service platform and display them on a large screen.

[0025] The remote control module is used to send remote control commands to the corresponding field repair terminal when abnormal damage analysis results occur, so as to remotely control the corresponding field repair terminal, control the remote repair terminal to reach the bridge area with abnormal damage analysis results and complete the field repair.

[0026] Preferably, the remote control module includes a connection unit, a display unit, and a control unit;

[0027] The connection unit is used to establish a remote control connection with a designated field repair terminal, enabling the management terminal and the field repair terminal to complete data interaction;

[0028] The display unit is used to display the on-site image data received from the display terminal, so that the manager can remotely control the on-site repair terminal based on the displayed on-site image data.

[0029] The control unit is used to send control commands to the on-site repair terminal, including selection commands and repair unit control commands. The control commands are used to control the on-site repair terminal and complete the repair of the damaged area of ​​the bridge.

[0030] Preferably, the on-site repair terminal includes a mobile module, a connection module, a video communication module, and a repair module;

[0031] The connection module is used to establish a communication connection with the management terminal and complete the remote control data exchange between the field repair terminal and the management terminal;

[0032] The mobile module is used to control the on-site repair terminal to reach the damaged area of ​​the bridge according to the received mobile control commands;

[0033] The video communication module is used to acquire real-time images of the repair area of ​​the on-site repair terminal and transmit the acquired images back to the management terminal in real time.

[0034] The repair module is used to select the appropriate repair unit according to the received repair control command, and control the repair unit to align with the repair area to complete the repair of the damaged area of ​​the bridge.

[0035] The beneficial effects of this invention are as follows: It proposes an intelligent bridge repair system, in which a detection terminal is specifically designed to detect damage to surfaces such as road surfaces, piers, guardrails, and hangers of large bridges. This terminal collects bridge surface image data through automated patrols and transmits the collected data to a cloud service platform. Based on the powerful computing capabilities of the cloud service platform, intelligent damage detection is performed on the bridge surface images to obtain the detection results. When repairs are needed on damaged areas of the bridge, the on-site repair terminal can be remotely controlled via a management terminal. Managers and operators can then control the on-site repair terminal to reach the damaged area and complete the repairs. This intelligent bridge damage detection combined with remote-controlled bridge repair helps reduce the workload of operators outdoors, lowers the labor costs of comprehensive inspection and repair of large bridges, and improves the efficiency and intelligence of bridge repair. Attached Figure Description

[0036] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0037] Figure 1 This is a structural diagram of an intelligent bridge repair system according to the present invention. Detailed Implementation

[0038] The present invention will be further described in conjunction with the following application scenarios.

[0039] See Figure 1 It demonstrates an intelligent bridge repair system, including: a detection terminal, a cloud service platform, and a management terminal;

[0040] The detection terminal includes an image acquisition module mounted on a mobile device. The image acquisition module is used to collect bridge surface image data during the patrol and detection process of the mobile device and transmit the collected bridge surface image data to the cloud service platform. The collected bridge surface image data carries corresponding positioning information.

[0041] The cloud service platform is used to perform image analysis on the bridge surface based on the acquired bridge surface image data, obtain bridge damage analysis results, and transmit the obtained bridge damage analysis results to the management terminal; the bridge damage analysis results contain the positioning information carried by the corresponding bridge surface image data;

[0042] The management terminal is used to remotely control the on-site repair terminal based on the obtained bridge damage analysis results, so that the on-site repair terminal can reach the bridge damage site and repair the damaged area.

[0043] Preferably, the system also includes a field repair terminal;

[0044] The on-site repair terminal is used to reach the site of bridge damage and complete the corresponding repair operations under the control of the management terminal according to the received remote control instructions.

[0045] This invention proposes an intelligent bridge repair system. The system includes a dedicated detection terminal for assessing damage to surfaces such as pavement, piers, railings, and hangers on large bridges. This terminal collects bridge surface image data through automated patrols and transmits the data to a cloud service platform. Leveraging the powerful computing capabilities of the cloud platform, intelligent damage detection is performed on the bridge surface images to obtain the inspection results. When repairs are needed, the on-site repair terminal can be remotely controlled via a management terminal. Managers and operators can then use the management terminal to guide the on-site repair terminal to the damaged area and complete the repairs. This intelligent bridge damage detection combined with remote-controlled bridge repair reduces the workload of operators outdoors, lowers the labor costs of comprehensive inspection and repair of large bridges, and improves the efficiency and intelligence of bridge repair.

[0046] Preferably, the mobile devices include dedicated intelligent bridge inspection vehicles, drones, crawling robots, etc.

[0047] It can detect the location of different areas in a bridge, meeting the needs of large-scale bridge inspection and repair.

[0048] Preferably, the image acquisition module includes an image acquisition unit, a positioning unit, and a data transmission unit;

[0049] The image acquisition unit is used to acquire image data of the bridge surface at a set angle during the patrol and inspection process of the mobile device;

[0050] The positioning unit is used to acquire the current positioning information and integrate the acquired positioning information into the collected bridge surface image data;

[0051] The data transmission unit is used to transmit bridge surface image data with integrated positioning information to the cloud service platform in real time via a wireless communication network.

[0052] During the patrol process of the inspection terminal, the image acquisition module collects images of the bridge surface area at a preset angle. This effectively enables continuous and uninterrupted image data acquisition for large bridges, helping to avoid omissions or incompleteness in traditional manual inspections. Simultaneously, the module integrates corresponding positioning information into the image data during acquisition, facilitating accurate tracing of damaged areas after subsequent damage identification based on the bridge surface images.

[0053] Preferably, the cloud service platform includes an image receiving unit, a preprocessing unit, a target extraction unit, a damage analysis unit, and an output unit;

[0054] The image receiving unit is used to acquire bridge surface image data transmitted by the detection terminal;

[0055] The preprocessing unit is used to preprocess the received bridge surface image data, including standardization and enhancement adjustment, to obtain a preprocessed bridge surface image.

[0056] The target extraction unit is used to extract targets from the preprocessed bridge surface image and obtain the target detection area image of the bridge surface in the image. The target extraction unit uses edge detection, template matching and other techniques to segment and extract the target detection area of ​​the bridge surface in the image and obtain the target detection area image of the bridge surface.

[0057] The damage analysis unit is used to analyze the obtained target detection area image using a damage analysis model trained on a neural network, and obtain the damage analysis results of the front area of ​​the target.

[0058] The output unit is used to extract the positioning information carried in the corresponding bridge surface image when the damage analysis result is abnormal, integrate the obtained positioning information into the current abnormal damage analysis result, and transmit the damage analysis result to the management terminal.

[0059] By establishing a cloud service platform for centralized processing of collected bridge surface image data, the powerful computing capabilities of the cloud service platform can be used to centrally process bridge surface image data uploaded from various detection terminals. During processing, the obtained bridge surface image data first undergoes routine preprocessing to obtain standardized and clear images. Simultaneously, the preprocessed bridge surface images undergo target extraction processing, and the bridge surface regions within the images are further analyzed. Damage analysis models (such as crack recognition models and concrete damage models) trained based on neural networks (such as CNN and YOLOv5) are used to perform bridge damage analysis, yielding corresponding bridge damage analysis results. When anomalies are detected in the analysis results, the abnormal analysis results are transmitted to the management terminal for further processing.

[0060] In particular, considering that bridge surface images acquired under intense sunlight or prolonged exposure to heat can easily contain shadows due to the detection terminal itself blocking sunlight, affecting the accuracy of subsequent damage detection (such as crack identification) based on the bridge surface images, the following measures are taken to address these issues:

[0061] Preferably, the preprocessing unit performs enhancement and adjustment processing on the received bridge surface image data, including:

[0062] The color space of the acquired bridge surface image is converted from RGB color space to Lab color space, and the brightness sub-image tuL of the bridge surface image is extracted.

[0063] The average brightness value li# is calculated based on the brightness values ​​li(x,y) of the extracted brightness sub-image tuL pixels, and a regular brightness range [max(0,li# -tisu),min(100,li# +tisu)] is set based on the average brightness value li#, where tisu represents the brightness adjustment factor. Where li#25% represents the brightness value of the top 25% of pixels obtained by arranging the brightness values ​​of each pixel in the brightness sub-image from largest to smallest, li#75% represents the brightness value of the top 75% of pixels obtained by arranging the brightness values ​​of each pixel in the brightness sub-image from largest to smallest, and li# represents the set brightness adjustment parameter, where 35 <li#se<55;

[0064] Pixels whose brightness values ​​li(x,y) belong to the normal brightness range are marked as normal pixels pointC, and pixels whose brightness values ​​do not belong to the normal brightness range are marked as feature pixels pointT.

[0065] Brightness adjustment processing is performed on the feature pixels:

[0066] li′(x,y)=α×li#round(k)+β×[li#mean+sgn(li(x,y)-li#mean)×tisu]

[0067]

[0068] In the formula, li′(x,y) represents the brightness value of pixel (x,y) after brightness adjustment, li#round(k) represents the average brightness value of the k×k range centered on pixel (x,y), argmin represents the minimum function of the region target, li#round(k+2) represents the average brightness value of the k+2×k+2 range centered on pixel (x,y), li# represents the average brightness value of the brightness sub-image, tisu represents the brightness adjustment factor, sgn(li(x,y)-i#mean) represents the sign function, and α and β represent the set weight factors respectively;

[0069] Further brightness equalization processing is performed on all pixels:

[0070] li″(x,y)=γ×li#round(g)+δ×li#

[0071] Among them, li″(x,y) represents the brightness value of the pixel point (x,y) after brightness equalization processing, li#round(g) represents the average brightness value within the g×g range centered on the pixel point (x,y), g represents the set equalization distance, where g∈[3,5,7], li#bse represents the set brightness equalization parameter, where 60 < li#bse < 65, and γ and δ respectively represent the set weight factors;

[0072] Perform an inverse color space transformation based on the luminance sub-image tuL″ after brightness equalization processing, and re-convert the image to the RGB color space to obtain the pre-processed bridge surface image.

[0073] The above embodiments of the present invention propose a technical solution for pre-processing bridge surface images. Firstly, an adaptive brightness interval division is performed according to the luminance sub-image of the image to obtain characteristic pixel points that appear under conditions of exposure or shadow in the image. At the same time, brightness adjustment is performed according to the characteristic pixel points, which helps to reduce the interference of the characteristic pixel points by abnormal brightness information. In particular, a brightness adjustment processing scheme is proposed, which can adaptively set the adjustment parameter according to the change of pixel points in the surrounding area of the characteristic pixel points in the image, which helps to improve the adaptability and effect of the brightness adjustment of the characteristic pixel points. After the brightness of the characteristic pixel points is adjusted, the overall brightness of the image is further equalized, which helps to adjust the image to an appropriate brightness level, improve the representation level of damaged feature information in the bridge surface image, and improve the accuracy of subsequent damage detection (such as crack identification, etc.) based on the bridge surface image.

[0074] Preferably, the management terminal includes a large-screen display module and a remote control module;

[0075] The large-screen display module is used to receive the damage analysis result transmitted by the cloud service platform and perform large-screen display.

[0076] The remote control module is used to send a remote control instruction to the corresponding on-site repair terminal when an abnormal damage analysis result appears, so as to remotely control the corresponding on-site repair terminal, control the remote repair terminal to reach the bridge area with an abnormal damage analysis result and complete on-site repair.

[0077] The management terminal can be built based on dedicated intelligent devices or dedicated devices in the back-end management center. The large screen display module can display the bridge inspection status in real time, which helps managers to intuitively understand the bridge damage detection status. Furthermore, it can remotely control the corresponding on-site repair terminals for the damaged areas of the bridge to complete the on-site repair of the damaged areas. This helps to improve the comfort of the management personnel in the on-site bridge repair environment, and the remote control method can also improve the level of intelligence of bridge repair.

[0078] Preferably, the remote control module includes a connection unit, a display unit, and a control unit;

[0079] The connection unit is used to establish a remote control connection with a designated field repair terminal, enabling the management terminal and the field repair terminal to complete data interaction;

[0080] The display unit is used to display the on-site image data received from the display terminal, so that the manager can remotely control the on-site repair terminal based on the displayed on-site image data.

[0081] The control unit is used to send control commands to the on-site repair terminal, including selection commands and repair unit control commands. The control commands are used to control the on-site repair terminal and complete the repair of the damaged area of ​​the bridge.

[0082] Preferably, the on-site repair terminal includes a mobile module, a connection module, a video communication module, and a repair module;

[0083] The connection module is used to establish a communication connection with the management terminal and complete the remote control data exchange between the field repair terminal and the management terminal;

[0084] The mobile module is used to control the on-site repair terminal to reach the damaged area of ​​the bridge according to the received mobile control commands;

[0085] The video communication module is used to acquire real-time images of the repair area of ​​the on-site repair terminal and transmit the acquired images back to the management terminal in real time.

[0086] The repair module is used to select the appropriate repair unit according to the received repair control command, and control the repair unit to align with the repair area to complete the repair of the damaged area of ​​the bridge.

[0087] The mobile module of the on-site repair terminal can be based on drones, four-wheeled vehicles, crawling robots, etc., and the video communication module is equipped with image acquisition equipment. The repair module includes one or more repair units, including robotic arms, vacuum feeding mechanisms, strong wind devices, etc., so that the repair of damaged areas can be completed through remote control of the on-site repair terminal.

[0088] It should be noted that the functional units / modules in the various embodiments of the present invention can be integrated into one processing unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated into one unit / module. The integrated unit / module described above can be implemented in hardware or in the form of software functional units / modules.

[0089] From the above description of the embodiments, those skilled in the art should understand that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field-Programmable Gate Array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments can be implemented by a computer program instructing the associated hardware. During implementation, the program can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should be able to analyze that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. An intelligent bridge repair system, characterized in that, include: Testing terminals, cloud service platforms, and management terminals; The detection terminal includes an image acquisition module mounted on a mobile device. The image acquisition module is used to collect bridge surface image data during the patrol and detection process of the mobile device and transmit the collected bridge surface image data to the cloud service platform. The collected bridge surface image data carries corresponding positioning information. The cloud service platform is used to perform image analysis on the bridge surface based on the acquired bridge surface image data, obtain bridge damage analysis results, and transmit the obtained bridge damage analysis results to the management terminal; the bridge damage analysis results contain the positioning information carried by the corresponding bridge surface image data; The management terminal is used to remotely control the field repair terminal based on the obtained bridge damage analysis results, so that the field repair terminal can reach the bridge damage site and repair the damaged area. The cloud service platform includes an image receiving unit, a preprocessing unit, a target extraction unit, a damage analysis unit, and an output unit. The image receiving unit is used to acquire bridge surface image data transmitted by the detection terminal; The preprocessing unit is used to preprocess the received bridge surface image data, including standardization and enhancement adjustment, to obtain a preprocessed bridge surface image. The target extraction unit is used to extract targets from the preprocessed bridge surface image and obtain the target detection area image of the bridge surface in the image; The damage analysis unit is used to analyze the obtained target detection area image using a damage analysis model trained on a neural network, and obtain the damage analysis results of the target detection area. When the damage analysis results are abnormal, the output unit extracts the positioning information carried in the corresponding bridge surface image, integrates the obtained positioning information into the current abnormal damage analysis results, and transmits the damage analysis results to the management terminal. The preprocessing unit performs enhancement and adjustment processing on the received bridge surface image data, including: The acquired bridge surface image is converted from RGB to Lab color space, and a brightness sub-image is extracted from the bridge surface image. ; Based on the extracted brightness submap Pixel brightness value Calculate the average brightness value and based on average brightness value To set the standard brightness range ,in Indicates the brightness adjustment factor. ,in This represents the brightness values ​​of the top 25% of pixels obtained by sorting the brightness values ​​of each pixel in the brightness sub-image from largest to smallest. This represents the brightness values ​​of the top 75% of pixels obtained by sorting the brightness values ​​of each pixel in the brightness sub-image from largest to smallest. This indicates the set brightness adjustment parameter, where ; Brightness value Pixels that fall within the normal brightness range are marked as normal pixels. Pixels whose brightness values ​​do not belong to the normal brightness range are marked as feature pixels. ; Brightness adjustment processing is performed on the feature pixels: In the formula, Indicates the pixel after brightness adjustment processing brightness value, Represented by pixels Centered Average brightness value of the range The function representing the minimum objective function of the region. Represented by pixels Centered Average brightness value of the range This represents the average brightness value of the brightness submap. Indicates the brightness adjustment factor. Represents a symbolic function. and These represent the set weighting factors; Further brightness equalization processing is performed on all pixels: in, Indicates the pixel after brightness equalization processing brightness value, Represented by pixels Centered The average brightness value over the range, where g represents the set equalization distance, where , This represents the set brightness equalization parameter, where , and These represent the set weighting factors; Based on the brightness subgraph after brightness equalization processing Perform an inverse color space transformation to convert the image back to the RGB color space, resulting in a preprocessed image of the bridge surface.

2. The intelligent bridge repair system according to claim 1, characterized in that, This also includes on-site repair of terminals; The on-site repair terminal is used to reach the site of bridge damage and complete the corresponding repair operations under the control of the management terminal according to the received remote control instructions.

3. The intelligent bridge repair system according to claim 1, characterized in that, Mobile devices include dedicated smart bridge inspection vehicles, drones, and crawling robots.

4. The intelligent bridge repair system according to claim 1, characterized in that, The image acquisition module includes an image acquisition unit, a positioning unit, and a data transmission unit; The image acquisition unit is used to acquire image data of the bridge surface at a set angle during the patrol and inspection process of the mobile device; The positioning unit is used to acquire the current positioning information and integrate the acquired positioning information into the collected bridge surface image data; The data transmission unit is used to transmit bridge surface image data with integrated positioning information to the cloud service platform in real time via a wireless communication network.

5. The intelligent bridge repair system according to claim 1, characterized in that, The management terminal includes a large-screen display module and a remote control module; The large-screen display module is used to receive damage analysis results transmitted from the cloud service platform and display them on a large screen; The remote control module is used to send remote control commands to the corresponding field repair terminal when abnormal damage analysis results occur, so as to remotely control the corresponding field repair terminal, control the remote repair terminal to reach the bridge area with abnormal damage analysis results and complete the field repair.

6. The intelligent bridge repair system according to claim 1, characterized in that, The remote control module includes a connection unit, a display unit, and a control unit; The connection unit is used to establish a remote control connection with a designated field repair terminal, enabling the management terminal and the field repair terminal to complete data interaction; The display unit is used to display the on-site image data received from the detection terminal, so that the manager can remotely control the on-site repair terminal based on the displayed on-site image data. The control unit is used to send control commands to the on-site repair terminal, including selection commands and repair unit control commands. The control commands are used to control the on-site repair terminal and complete the repair of the damaged area of ​​the bridge.

7. The intelligent bridge repair system according to claim 1, characterized in that, The field repair terminal includes a mobile module, a connection module, a video communication module, and a repair module; The connection module is used to establish a communication connection with the management terminal and complete the remote control data exchange between the field repair terminal and the management terminal; The mobile module is used to control the on-site repair terminal to reach the damaged area of ​​the bridge according to the received mobile control commands; The video communication module is used to acquire real-time images of the repair area of ​​the on-site repair terminal and transmit the acquired images back to the management terminal in real time. The repair module is used to select the appropriate repair unit according to the received repair control command, and control the repair unit to align with the repair area to complete the repair of the damaged area of ​​the bridge.

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