A steel structure surface monitoring system and method based on unmanned aerial vehicle panoramic perception

Abstract

The application discloses a kind of steel structure surface monitoring system and method based on unmanned aerial vehicle panoramic perception, belong to the technical field of steel structure detection, it includes multi-port unmanned aerial vehicle and general control system, multi-port unmanned aerial vehicle is equipped with laser radar scanner, the general control system includes three-dimensional graph generation module, route planning module, flight control module, information receiving module and main graph generation module, three-dimensional graph generation module receives imported engineering drawing, and generates three-dimensional model graph according to steel structure coordinates in engineering drawing, route planning module is preset with unmanned aerial vehicle scanning range, route planning module marks steel structure connecting node and support steel column in three-dimensional model graph, flight route is planned according to unmanned aerial vehicle scanning range and marked coordinate, the application has the effect that remote control unmanned aerial vehicle can detect steel structure, and automatically plan flight route, generate detection result, save time and effort.

Description

Technical Field

[0001] This invention relates to the field of steel structure inspection technology, and in particular to a steel structure surface monitoring system and method based on UAV panoramic perception. Background Technology

[0002] Currently, steel structure inspection is one of the important technologies for building structure safety assessment and engineering quality evaluation. It involves on-site investigation, testing, and analysis of buildings or structures to evaluate their safety, reliability, and load-bearing capacity. Since manual inspection of steel structures is time-consuming, labor-intensive, and inaccurate, engineering units generally use equipment to inspect various aspects of the steel structure. Among the various aspects of steel structure inspection, the location of the steel structure is crucial. Monitoring the location of the steel structure allows for determination of whether it meets expectations and whether there are any deformation issues after a period of time.

[0003] The existing technical solutions mentioned above have the following drawbacks: When using equipment to inspect steel structures, staff need to bring the inspection equipment to the site for inspection, which is time-consuming, labor-intensive, and also dangerous. Summary of the Invention

[0004] To remotely inspect steel structures, save manpower, and avoid danger, this application provides a steel structure surface monitoring system and method based on UAV panoramic perception.

[0005] On the one hand, the steel structure surface monitoring system based on UAV panoramic perception provided in this application adopts the following technical solution: A steel structure surface monitoring system based on UAV panoramic perception includes a multi-port UAV and a central control system. The multi-port UAV is equipped with a lidar scanner, and the central control system includes a 3D map generation module, a route planning module, a flight control module, an information receiving module, and a main map generation module. The 3D model generation module receives the imported engineering drawings and generates a 3D model based on the steel structure coordinates in the engineering drawings, and then transmits the 3D model to the route planning module. The route planning module has a preset UAV scanning range. The route planning module marks the steel structure connection nodes and supporting steel columns in the 3D model. It plans the flight route according to the UAV scanning range and the marked coordinates, so that the UAV scanning range can cover all the marked coordinates. Spatial coordinate target points are set at each marked coordinate. The spatial coordinate target points are added to the flight route and the flight route is transmitted to the flight control module. The flight control module receives and stores the flight route. When the flight control module receives a start command from the outside, it sends the flight route to the multi-port UAV and controls the lidar scanner to scan the spatial coordinate target point. The information receiving module receives radar scanning information sent by the multi-port UAV and transmits the radar scanning information to the main image generation module; The main image generation module calls the 3D model image generated by the 3D image generation module, draws the actual 3D model image on the 3D model image based on the radar scanning information, and displays the actual 3D model image.

[0006] By adopting the above scheme, the system automatically generates a 3D model based on the engineering drawings and marks the main steel structure on the 3D model. Then, it automatically generates the flight path of the multi-port UAV, so that when the multi-port UAV flies along the flight path, the LiDAR scanner can scan all the main steel structures. The system actively controls the LiDAR scanner to scan the marked positions, making the scanned structure more accurate. After obtaining the scan data, the system can automatically generate a 3D model of the actual steel structure. The staff can understand the 3D point information of the current steel structure through the 3D model of the actual steel structure. The process is convenient, fast, and saves time and effort.

[0007] Preferably, it also includes an error detection module and an error handling module; The error judgment module calls the 3D model diagram of the 3D diagram generation module and the actual 3D model diagram of the main diagram generation module, compares the positions of the marked coordinates in the actual 3D model diagram with those in the 3D model diagram, highlights the marked coordinates whose positions in the actual 3D model diagram have changed, calls the coordinate information and detection time of the highlighted coordinates and transmits them to the error handling module. The error handling module stores the received coordinate information and detection time, and draws a coordinate change graph based on the stored coordinate information and detection time.

[0008] By adopting the above scheme, the system can automatically highlight the parts in the 3D diagram that do not conform to the engineering expectations, and can also draw coordinate change diagrams after multiple tests, so that users can intuitively understand the location and deformation process of the deformed parts of the steel structure.

[0009] Preferably, the error handling module has a preset change range warning value. It calculates the change of coordinate information of each highlighted coordinate within a preset time based on the coordinate change graph, adds the calculation result to the coordinate change graph, finds the part in the coordinate change graph that exceeds the change range warning value and marks it, and displays the marked coordinate change graph.

[0010] By adopting the above scheme, the system can predict the trend of steel structure deformation through coordinate change graphs and automatically mark the parts that may be dangerous, making it convenient for users to view and respond to maintenance in a timely manner.

[0011] Preferably, it also includes a change confirmation module and an overall adjustment module; The change confirmation module receives the coordinate change map from the error handling module. When the coordinate information of all marked coordinates in the coordinate change map changes, the change confirmation module detects the amount of change in the coordinate information of each marked coordinate. If the amount of change in the coordinate information of each marked coordinate is the same, an adjustment request is output based on the amount of change in the coordinate information of the marked coordinate. After receiving the adjustment command, the overall adjustment module receives the change in the coordinate information of the marked coordinates from the change confirmation module, and adjusts the coordinate information of the marked coordinates in the actual 3D model drawing according to the change.

[0012] If all coordinates in the scan result are offset by the same value, it may be a detection failure. In this case, all coordinates in the 3D model should be adjusted back to the same offset value, and an adjusted 3D model should be output.

[0013] Preferably, the system also includes a take-off and landing point determination module. This module calls the 3D model of the route planning module and selects a coordinate point near the start and end points of the flight route on the 3D model as the starting and ending reference coordinate points, respectively. When the UAV takes off, it controls the LiDAR scanner to detect the starting reference coordinate point, and when the UAV finishes flying, it controls the LiDAR scanner to detect the ending reference coordinate point. If the detected starting and ending reference coordinate points are not the same as the set starting and ending reference coordinate points, the system calculates the coordinate difference between the detected starting and ending reference coordinate points and the set starting and ending reference coordinate points, and determines whether the coordinate difference between the starting and ending reference coordinate points is the same. If they are the same, a position deviation signal is output; otherwise, a detection error signal is output.

[0014] By adopting the above scheme, the system presets two reference points as references for the take-off and landing points of the UAV, ensuring the accuracy of the UAV's take-off and landing points, thereby increasing the accuracy of the flight path of the UAV throughout the entire flight process and further increasing the detection accuracy.

[0015] Preferably, it also includes a deviation correction module, which receives the position deviation signal output by the take-off and landing point determination module. When the deviation correction module receives the position deviation signal, it corrects the flight path of the route planning module according to the coordinate difference.

[0016] By adopting the above scheme, when the take-off point and landing point of the drone deviate from the preset target point by the same distance, it is possible that the deviation occurred during the flight path calculation. Therefore, the flight path can be corrected to further increase the accuracy of detection.

[0017] Preferably, it also includes an expected deformation module, which receives the marked coordinate change map from the error handling module and stores it according to time. The expected deformation module sorts the stored coordinate change maps according to time, extracts the part of the coordinate change map representing the calculation result from the earliest time stored coordinate change map, and determines whether the coordinate change map after the coordinate change map is the same as the calculation result. If they are the same, the extracted coordinate change map is deleted. If they are not the same, the extraction of coordinate change maps is stopped and the coordinate change map that is different from the calculation result of the extracted coordinate change map is selected.

[0018] By adopting the above scheme, the system can verify the accuracy of the calculation results in the coordinate transformation graph. If the calculation is inaccurate, the inaccurate result will be output so that the user can make adaptive modifications to the coordinate transformation graph.

[0019] On the other hand, the steel structure surface monitoring method based on UAV panoramic perception provided in this application adopts the following technical solution: A method for monitoring the surface of steel structures based on UAV panoramic perception, comprising the steel structure surface monitoring system as described above, and including the following steps: Import the engineering drawing of the area to be inspected, and draw a 3D model based on the engineering drawing; Mark the steel structure connection nodes and supporting steel columns in the 3D model diagram; Plan the flight route based on the drone's scanning range and the marked coordinates, so that the drone's scanning range can cover all the marked coordinates, set spatial coordinate target points at each marked coordinate, and add the spatial coordinate target points into the flight route; After receiving the start command, the multi-port UAV is controlled to fly according to the flight path, and the lidar scanner is controlled to scan the target points in spatial coordinates. Obtain radar scan information from a LiDAR scanner; Draw the actual 3D model based on the radar scan information on the 3D model diagram.

[0020] By adopting the above scheme, a remotely controlled multi-port UAV carrying a laser scanning radar flies along the flight path, making the scanning structure of the laser scanning radar more accurate. After obtaining the scanning data, it can automatically generate a three-dimensional model of the actual steel structure. Staff can understand the three-dimensional point information of the current steel structure through the three-dimensional model of the actual steel structure. The process is convenient, fast and saves time and effort.

[0021] Preferably, the following steps are also included: Compare the positions of the marked coordinates in the actual 3D model with those in the 3D model, and highlight the marked coordinates in the actual 3D model whose positions have changed. A coordinate change graph is plotted based on the stored coordinate information and detection time. Based on the coordinate change graph, calculate the change of coordinate information of each highlighted coordinate within a preset time, and add the calculation results to the coordinate change graph; Locate and mark the portions of the coordinate change graph that exceed the warning value for the change range, and then display the marked coordinate change graph. Store the marked coordinate change graphs according to time. Sort the stored coordinate change graphs, extract the part of the coordinate change graph that represents the calculation result starting from the earliest time stored coordinate change graph, and determine whether the coordinate change graphs after this coordinate change graph are the same as the calculation result. If they are the same, delete the extracted coordinate transformation graph; If they are not the same, stop extracting coordinate transformation diagrams and select the coordinate transformation diagrams whose calculation results are different from those of the extracted coordinate transformation diagrams.

[0022] By adopting the above solution, parts of the 3D drawing that do not conform to the engineering expectations can be automatically highlighted. Furthermore, after multiple inspections, a coordinate change graph can be generated. This graph allows for the prediction of steel structure deformation trends and automatically identifies potentially hazardous areas for user review. Preferably, the following steps are also included: When the coordinate information of all marked coordinates in the coordinate transformation graph changes, detect the amount of change in the coordinate information of each marked coordinate. If the change in coordinate information of each marked coordinate is the same, then the coordinate information of the marked coordinate in the actual 3D model diagram is adjusted according to the change.

[0023] If all coordinates in the scan result are offset by the same value, it may be a detection failure. In this case, all coordinates in the 3D model should be adjusted back to the same offset value, and an adjusted 3D model should be output.

[0024] In summary, the present invention has the following beneficial effects: 1. A remotely controlled multi-port drone carrying a laser scanning radar flies along the flight path, making the laser scanning radar scan the structure more accurately. After obtaining the scan data, it can automatically generate a 3D model of the actual steel structure. Staff can understand the 3D point information of the current steel structure through the 3D model of the actual steel structure. The process is convenient, fast and saves time and effort.

[0025] 2. It can automatically highlight parts in the 3D drawing that do not conform to the engineering expectations, and can also draw coordinate change diagrams after multiple tests. The trend of steel structure deformation can be inferred from the coordinate change diagrams, and parts that may be dangerous can be automatically marked. Attached Figure Description

[0026] Figure 1 This is an overall system block diagram of Embodiment 1 of this application.

[0027] Explanation of reference numerals in the attached figures: 1. Multi-port UAV; 11. LiDAR scanner; 2. Central control system; 21. 3D map generation module; 22. Route planning module; 221. Flight control module; 23. Information receiving module; 24. Main map generation module; 241. Error judgment module; 242. Error handling module; 25. Change confirmation module; 26. Overall adjustment module; 27. Take-off and landing point judgment module; 28. Expected deformation module; 29. ​​Deviation correction module. Detailed Implementation Example

[0028] This application discloses a steel structure surface monitoring system based on UAV panoramic perception, such as... Figure 1 As shown, the system includes a multi-port UAV 1 and a central control system 2. The multi-port UAV 1 is equipped with a lidar scanner 11, which is an active optical remote sensing technology that acquires relevant target information by capturing the scattered light of the target. It mainly relies on radar principles, but uses laser as the primary carrier. The central control system 2 includes a 3D map generation module 21, a route planning module 22, a flight control module 221, an information receiving module 23, a main map generation module 24, an error judgment module 241, an error handling module 242, a change confirmation module 25, an overall adjustment module 26, a take-off and landing point judgment module 27, an expected deformation module 28, and a deviation correction module 29.

[0029] like Figure 1 As shown, the 3D model generation module 21 receives the imported engineering drawing and generates a 3D model based on the steel structure coordinates in the engineering drawing. The 3D model is then transmitted to the route planning module 22. The route planning module 22 has a preset UAV scanning range. It marks the steel structure connection nodes and supporting steel columns in the 3D model, plans the flight route based on the UAV scanning range and the marked coordinates, ensuring that the UAV scanning range covers all marked coordinates. Spatial coordinate target points are set at each marked coordinate and added to the flight route. The flight route is then transmitted to the flight control module 221.

[0030] like Figure 1As shown, the flight control module 221 receives and stores the flight route. When the flight control module 221 receives a start command from an external source, it sends the flight route to the multi-port UAV 1 and controls the lidar scanner 11 to scan the target points in spatial coordinates. The information receiving module 23 receives the radar scan information sent by the multi-port UAV 1 and transmits it to the main image generation module 24. The main image generation module 24 calls the 3D model generated by the 3D image generation module 21, draws the actual 3D model on the 3D model based on the radar scan information, and displays the actual 3D model.

[0031] The system remotely controls a multi-port drone to scan the steel structure. Staff can then understand the three-dimensional point information of the steel structure through a three-dimensional model of the actual steel structure. The process is convenient, fast, and saves time and effort.

[0032] like Figure 1 As shown, the takeoff and landing point determination module 27 calls the 3D model diagram of the route planning module 22 and selects a coordinate point near the start and end points of the flight route on the 3D model diagram as the starting reference coordinate point and the ending reference coordinate point, respectively. When the UAV takes off, the laser radar scanner 11 is controlled to detect the starting reference coordinate point, and when the UAV completes flight, the laser radar scanner 11 is controlled to detect the ending reference coordinate point. If the detected starting and ending reference coordinate points are different from the set starting and ending reference coordinate points, the coordinate difference between the detected starting and ending reference coordinate points and the set starting and ending reference coordinate points is calculated. It is then determined whether the coordinate difference between the starting and ending reference coordinate points is the same. If they are the same, a position deviation signal is output; otherwise, a detection error signal is output. The deviation correction module 29 receives the position deviation signal output by the takeoff and landing point determination module 27. When the deviation correction module 29 receives the position deviation signal, it corrects the flight route of the route planning module 22 according to the coordinate difference.

[0033] like Figure 1As shown, the error judgment module 241 calls the 3D model diagram from the 3D model generation module 21 and the actual 3D model diagram from the main model generation module 24. It compares the positions of the marked coordinates in the actual 3D model diagram with those in the 3D model diagram, highlights the marked coordinates whose positions in the actual 3D model diagram have changed, and retrieves the coordinate information and detection time of the highlighted coordinates, transmitting them to the error processing module 242. The error processing module 242 has a preset change range warning value. The error processing module 242 stores the received coordinate information and detection time, draws a coordinate change diagram based on the stored coordinate information and detection time, calculates the change of the coordinate information of each highlighted coordinate within a preset time based on the coordinate change diagram, adds the calculation result to the coordinate change diagram, finds and marks the portion in the coordinate change diagram that exceeds the change range warning value, and displays the marked coordinate change diagram. The system can automatically highlight parts in the 3D diagram that do not conform to the engineering expectations, and can also draw coordinate change diagrams after multiple tests. The system can infer the trend of steel structure deformation through coordinate change diagrams and automatically mark parts that may be dangerous, so that users can view them and respond to maintenance in a timely manner.

[0034] like Figure 1 As shown, the change confirmation module 25 receives the coordinate change map from the error handling module 242. When the coordinate information of all marked coordinates in the coordinate change map changes, the change confirmation module 25 detects the amount of change in the coordinate information of each marked coordinate. If the amount of change in the coordinate information of each marked coordinate is the same, an adjustment request is output based on the amount of change in the coordinate information of the marked coordinate. After receiving the adjustment command, the overall adjustment module 26 receives the amount of change in the coordinate information of the marked coordinates from the change confirmation module 25 and adjusts the coordinate information of the marked coordinates in the actual 3D model map based on the amount of change. If all coordinates in the scan result are offset by the same value, it may be a detection fault. In this case, all coordinates in the 3D model map are adjusted back by the same offset value, and an adjusted 3D model map is output.

[0035] like Figure 1 As shown, the expected deformation module 28 receives the marked coordinate transformation map from the error handling module 242 and stores it according to time. The expected deformation module 28 sorts the stored coordinate transformation maps according to time, extracts the part of the coordinate transformation map representing the calculation result starting from the earliest stored coordinate transformation map, and determines whether the coordinate transformation map after this coordinate transformation map is the same as the calculation result. If they are the same, the extracted coordinate transformation map is deleted; if they are different, the extraction of coordinate transformation maps stops, and coordinate transformation maps with different calculation results from the extracted coordinate transformation maps are selected. The system can verify the accuracy of the calculation result in the coordinate transformation map. If the calculation is inaccurate, the inaccurate result is output, allowing the user to make adaptive modifications to the coordinate transformation map.

[0036] The implementation principle of the steel structure surface monitoring system and method based on UAV panoramic perception in this application embodiment is as follows: The system automatically generates a three-dimensional model based on the engineering drawings and marks the main steel structures on the three-dimensional model. Then, it automatically generates the flight path of the multi-port UAV 1, so that when the multi-port UAV 1 flies along the flight path, the lidar scanner 11 can scan all the main steel structures. The system actively controls the lidar scanner 11 to scan the marked positions, making the scanned structure more accurate. After obtaining the scan data, the system can automatically generate a three-dimensional model of the actual steel structure. The staff can understand the three-dimensional point information of the current steel structure through the three-dimensional model of the actual steel structure. The process is convenient, fast and saves time and effort. Example

[0037] This application discloses a method for monitoring the surface of steel structures based on panoramic perception from unmanned aerial vehicles (UAVs), including the steel structure surface monitoring system as described in Embodiment 1. The specific steps are as follows: S100. Import the engineering drawing of the area to be detected, and draw a 3D model based on the engineering drawing.

[0038] S101. Mark the steel structure connection nodes and supporting steel columns in the 3D model diagram.

[0039] S102. Plan the flight route based on the UAV scanning range and the marked coordinates, so that the UAV scanning range can cover all the marked coordinates, set spatial coordinate target points at each marked coordinate, and add the spatial coordinate target points into the flight route.

[0040] S200, after receiving the start command, controls the multi-port UAV 1 to fly according to the flight route, and controls the lidar scanner 11 to scan the target point in spatial coordinates.

[0041] S201. Obtain radar scanning information from the LiDAR scanner 11.

[0042] S202. Draw the actual three-dimensional model diagram on the three-dimensional model diagram based on the radar scanning information.

[0043] S300. Compare the positions of the marked coordinates in the actual 3D model diagram with those in the 3D model diagram, and highlight the marked coordinates whose positions in the actual 3D model diagram have changed.

[0044] S301. Draw a coordinate change graph based on the stored coordinate information and detection time.

[0045] S302. Calculate the change of coordinate information of each highlighted coordinate within a preset time and add the calculation results to the coordinate change graph.

[0046] S400: Mark the portion of the graph that exceeds the warning value for the change range, and display the coordinate change graph after marking.

[0047] S401. Coordinate transformation graphs are stored according to time.

[0048] S500: Sort the coordinate change map, starting from the earliest stored coordinate change map, extract the part of the coordinate change map that represents the calculation result, and determine whether the coordinate change map after this coordinate change map is the same as the calculation result.

[0049] S501. Delete the extracted coordinate change graph.

[0050] S502, then stop extracting coordinate transformation diagrams and select coordinate transformation diagrams that differ from the calculated results of the extracted coordinate transformation diagrams.

[0051] S503. When the coordinate information of all marked coordinates in the figure changes, detect the amount of change in the coordinate information of each marked coordinate.

[0052] S504. If the changes in the coordinate information of the marked coordinates are all the same, then adjust the coordinate information of the marked coordinates in the actual 3D model drawing according to the changes.

[0053] S600: On the 3D model, select a coordinate point near the start and end points of the flight path as the starting and ending reference coordinate points, respectively.

[0054] S601, the multi-port UAV 1 controls the lidar scanner 11 to detect the starting reference coordinate point when it takes off, and controls the lidar scanner 11 to detect the ending reference coordinate point when the multi-port UAV 1 finishes flying.

[0055] S602. If the starting reference coordinate point and the ending reference coordinate point are not the same as the set starting reference coordinate point and the ending reference coordinate point, calculate the coordinate difference between the detected starting reference coordinate point and the set starting reference coordinate point and the ending reference coordinate point, and determine whether the coordinate difference between the starting reference coordinate point and the ending reference coordinate point is the same.

[0056] S603. The flight path of the route planning module 22 is corrected based on the coordinate difference.

[0057] S604, Issue an alarm.

[0058] The embodiments described herein are preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A steel structure surface monitoring system based on UAV panoramic perception, characterized in that: It includes a multi-port UAV (1) and a central control system (2). The multi-port UAV (1) is equipped with a lidar scanner (11). The central control system (2) includes a 3D map generation module (21), a route planning module (22), a flight control module (221), an information receiving module (23), and a main map generation module (24). The 3D model generation module (21) receives the imported engineering drawing and generates a 3D model drawing based on the steel structure coordinates in the engineering drawing, and transmits the 3D model drawing to the route planning module (22). The route planning module (22) has a preset UAV scanning range. The route planning module (22) marks the steel structure connection nodes and supporting steel columns in the three-dimensional model diagram. It plans the flight route according to the UAV scanning range and the marked coordinates, so that the UAV scanning range can cover all the marked coordinates. It sets spatial coordinate target points at each marked coordinate, adds the spatial coordinate target points into the flight route, and transmits the flight route to the flight control module (221). The flight control module (221) receives and stores the flight route. When the flight control module (221) receives the start command input from the outside, it sends the flight route to the multi-port UAV (1) and controls the laser radar scanner (11) to scan the spatial coordinate target point. The information receiving module (23) receives radar scanning information sent by the multi-port UAV (1) and transmits the radar scanning information to the main image generation module (24); The main image generation module (24) calls the three-dimensional model image generated by the three-dimensional image generation module (21), draws the actual three-dimensional model image on the three-dimensional model image according to the radar scanning information, and displays the actual three-dimensional model image; It also includes an error detection module (241) and an error handling module (242); The error judgment module (241) calls the three-dimensional model diagram of the three-dimensional diagram generation module (21) and the actual three-dimensional model diagram of the main diagram generation module (24), compares the position of the marked coordinates in the actual three-dimensional model diagram with the position of the marked coordinates in the three-dimensional model diagram, highlights the marked coordinates whose position in the actual three-dimensional model diagram has changed, calls the coordinate information and detection time of the highlighted coordinates and transmits them to the error processing module (242). The error handling module (242) stores the received coordinate information and detection time, and the error handling module (242) draws a coordinate change graph based on the stored coordinate information and detection time; The error handling module (242) has a preset change range warning value. It calculates the change of coordinate information of each highlighted coordinate within a preset time according to the coordinate change graph, adds the calculation result to the coordinate change graph, finds the part in the coordinate change graph that exceeds the change range warning value and marks it, and displays the marked coordinate change graph. It also includes a predictive deformation module (28), which receives the marked coordinate change map from the error handling module (242) and stores it according to time. The predictive deformation module (28) sorts the stored coordinate change maps according to time, extracts the part of the coordinate change map that represents the calculation result from the earliest time stored coordinate change map, and judges whether the coordinate change map after the coordinate change map is the same as the calculation result. If they are the same, the extracted coordinate change map is deleted. If they are not the same, the extraction of coordinate change map is stopped and the coordinate change map that is different from the calculation result of the extracted coordinate change map is selected.

2. The steel structure surface monitoring system based on UAV panoramic perception according to claim 1, characterized in that: It also includes a change confirmation module (25) and an overall adjustment module (26); The change confirmation module (25) receives the coordinate change diagram from the error handling module (242). When the coordinate information of all marked coordinates in the coordinate change diagram changes, the change confirmation module (25) detects the amount of change in the coordinate information of each marked coordinate. If the amount of change in the coordinate information of each marked coordinate is the same, an adjustment request is output according to the amount of change in the coordinate information of the marked coordinate. After receiving the adjustment instruction, the overall adjustment module (26) receives the change amount of the coordinate information of the marked coordinates from the change confirmation module (25), and adjusts the coordinate information of the marked coordinates in the actual three-dimensional model diagram according to the change amount.

3. The steel structure surface monitoring system based on UAV panoramic perception according to claim 1, characterized in that: It also includes a take-off and landing point judgment module (27). The take-off and landing point judgment module (27) calls the three-dimensional model of the route planning module (22). According to the flight route, it selects a coordinate point near the start and end points of the flight route in the three-dimensional model as the start reference coordinate point and the end reference coordinate point, respectively. When the UAV takes off, it controls the laser radar scanner (11) to detect the start reference coordinate point. When the UAV finishes flying, it controls the laser radar scanner (11) to detect the end reference coordinate point. If the detected start reference coordinate point and end reference coordinate point are not the same as the set start reference coordinate point and end reference coordinate point, it calculates the coordinate difference between the detected start reference coordinate point and end reference coordinate point and the set start reference coordinate point and end reference coordinate point, and judges whether the coordinate difference between the start reference coordinate point and the end reference point is the same. If they are the same, it outputs a position deviation signal. If they are not the same, it outputs a detection error signal.

4. A steel structure surface monitoring system based on UAV panoramic perception according to claim 3, characterized in that: It also includes a deviation correction module (29), which receives the position deviation signal output by the take-off and landing point judgment module (27). When the deviation correction module (29) receives the position deviation signal, it corrects the flight path of the route planning module (22) according to the coordinate difference.

5. A method for monitoring the surface of a steel structure based on panoramic perception from an unmanned aerial vehicle (UAV), comprising the steel structure surface monitoring system as described in any one of claims 1-4, characterized in that, Includes the following steps: Import the engineering drawing of the area to be inspected, and draw a 3D model based on the engineering drawing; Mark the steel structure connection nodes and supporting steel columns in the 3D model diagram; Plan the flight route based on the drone's scanning range and the marked coordinates, so that the drone's scanning range can cover all the marked coordinates, set spatial coordinate target points at each marked coordinate, and add the spatial coordinate target points into the flight route; After receiving the start command, control the multi-port UAV (1) to fly according to the flight route, and control the laser radar scanner (11) to scan the target point in spatial coordinates; Obtain radar scanning information from the lidar scanner (11); Draw the actual 3D model based on the radar scan information on the 3D model diagram.

6. The method for monitoring the surface of a steel structure based on panoramic perception by an unmanned aerial vehicle (UAV) according to claim 5, characterized in that, It also includes the following steps: Compare the positions of the marked coordinates in the actual 3D model with those in the 3D model, and highlight the marked coordinates in the actual 3D model whose positions have changed. A coordinate change graph is plotted based on the stored coordinate information and detection time. Based on the coordinate change graph, calculate the change of coordinate information of each highlighted coordinate within a preset time, and add the calculation results to the coordinate change graph; Locate and mark the portions of the coordinate change graph that exceed the warning value for the change range, and then display the marked coordinate change graph. Store the marked coordinate change graphs according to time. Sort the stored coordinate change graphs, extract the part of the coordinate change graph that represents the calculation result starting from the earliest time stored coordinate change graph, and determine whether the coordinate change graphs after this coordinate change graph are the same as the calculation result. If they are the same, delete the extracted coordinate transformation graph; If they are not the same, stop extracting coordinate transformation diagrams and select the coordinate transformation diagrams whose calculation results are different from those of the extracted coordinate transformation diagrams.

7. A method for monitoring the surface of a steel structure based on UAV panoramic perception according to claim 6, characterized in that, It also includes the following steps: When the coordinate information of all marked coordinates in the coordinate transformation graph changes, detect the amount of change in the coordinate information of each marked coordinate. If the change in coordinate information of each marked coordinate is the same, then the coordinate information of the marked coordinate in the actual 3D model diagram is adjusted according to the change.

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