Fan inspection route generation method and system based on unmanned aerial vehicle
By generating and smoothly processing drone inspection routes, the complex problems of drone inspection operations are solved, automated inspections are realized, and efficiency and accuracy are improved.
Patent Information
- Application Number
- CN202411830585.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-12
- Publication Date
- 2025-06-10
AI Technical Summary
The drone inspection operation is complicated and some routes are difficult to operate manually, resulting in inefficient inspections.
By obtaining the cabin position coordinates of the fan to be inspected, the position coordinates of the drone's departure point and the stop point, a preliminary patrol route is generated, and the final patrol route is obtained through smoothing processing, so that the drone can fly automatically and complete the patrol task.
It realizes the automatic generation of drone inspection routes, simplifies the operation process, improves patrol efficiency and accuracy, and reduces the occurrence of manual errors.
Smart Images
Figure CN120122676A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of drone inspection, and more particularly, to a method and system for generating a fan inspection route based on a drone. Background Art
[0002] Fan blades are an important part of a wind turbine, one of the key components, and a device for capturing wind energy. Therefore, the safety and reliability of the blades are particularly important, which is the key to ensuring the normal operation of the fan. Applying drone technology to inspect fan blades can quickly perform fault inspections and confirm fault information, achieving the goal of preliminary screening for surface damage of the blades.
[0003] Currently, the common blade inspections in wind farms mainly focus on patrol inspections. Mainly, operation and maintenance personnel conduct regular inspections and use binoculars to check whether there are abnormalities on the blade surface. Such inspections often rely on the personal experience of on-site personnel and cannot detect early fine cracks. In recent years, some wind farms have equipped drones for blade inspections, but the drone inspection operations are relatively complex, and some routes are difficult to operate manually. Summary of the Invention
[0004] The problem solved by the present invention is that in recent years, some wind farms have equipped drones for blade inspections, but the drone inspection operations are relatively complex, and some routes are difficult to operate manually.
[0005] To solve the above problems, in a first aspect, the present invention provides a method for generating a fan inspection route based on a drone, the method comprising: Obtaining the position coordinates of the nacelles of all fans to be inspected, the position coordinates of the drone's starting point, and the position coordinates of a pre-set docking point; Generating inspection points at each fan to be inspected according to the position coordinates of the nacelles of the fans to be inspected, and generating a preliminary inspection route through the inspection points at each fan to be inspected, the position coordinates of the drone's starting point, and the position coordinates of the pre-set docking point; Performing smoothing processing on the generated preliminary inspection route to obtain a final inspection route; The drone flies to the first initial inspection point of the first fan to be inspected according to the final inspection route, and successively passes through each inspection point of the first fan to be inspected and stays for taking pictures. After the picture taking is completed, the drone flies back to the first initial inspection point, and then flies to the second initial inspection point of the second fan to be inspected according to the final route until the picture taking of all fans to be inspected is completed. The drone flies to the pre-set docking point according to the final inspection route.
[0006] Further, the specific process of obtaining the position coordinates of the nacelles of all fans to be inspected, the position coordinates of the drone's starting point, and the position coordinates of the pre-set docking point is as follows: Deploy drones to conduct preliminary aerial surveys above the wind farm, collect three-dimensional coordinate data of the wind turbines in real time, and use computer vision technology to identify the position coordinates of the wind turbine nacelles; Select the drone starting point according to the layout of the wind farm and the flight capabilities of the drone, and determine the position coordinates of the drone starting point; Set docking points according to the inspection needs, and determine the position coordinates of the docking points to ensure that the drone can recharge or transfer data at the docking points when performing tasks; Ensure that the position coordinates of the nacelles of all wind turbines to be inspected, the position coordinates of the drone starting point, and the position coordinates of the docking points are in the same coordinate system.
[0007] Furthermore, the specific process of ensuring that the position coordinates of the nacelles of all wind turbines to be inspected, the position coordinates of the drone starting point, and the position coordinates of the docking points are in the same coordinate system is as follows: Perform coordinate transformation through the coordinate transformation formula where T is the transformation matrix, containing rotation, scaling, and displacement information, is the original coordinate, is the transformed coordinate; Perform translation or scaling through the translation formula and the scaling formula where , , are the translation amounts on the x, y, and z axes respectively, , , are the scaling factors on the x, y, and z axes respectively; Obtain the transformed wind turbine nacelle coordinates ,the position coordinates of the drone starting point ,the position coordinates of the docking point ,where is the wind turbine number; After the transformation is completed, verify whether all coordinates are in the same coordinate system. The formula is as follows: where represents the position coordinates of the drone starting point or the position coordinates of the docking point; Compare the verification coefficient with the preset verification threshold If ,it is determined that the coordinates are consistent. If ,it is determined that the coordinates are inconsistent and the coordinate transformation needs to be performed again.
[0008] Furthermore, the process of generating inspection points at each wind turbine to be inspected according to the position coordinates of the nacelles of the wind turbines to be inspected is as follows: Generate inspection points for the nacelle position coordinates of each wind turbine , where is the th inspection point coordinate of the th wind turbine, is the position offset of the inspection point relative to the nacelle of the wind turbine, , is the total number of nacelles of the wind turbines to be inspected.
[0009] Furthermore, the process of generating the preliminary inspection route is as follows: By calculating the sum of the distances from each inspection point of each wind turbine to be inspected to the starting point of the UAV and the distances from each inspection point to the preset docking point respectively, obtain the minimum sum of distances for each wind turbine to be inspected, and confirm the initial inspection point of each wind turbine to be inspected; By calculating the shortest distance from the starting point of the UAV passing through the initial inspection points of each wind turbine to be inspected in sequence and finally flying to the preset docking point, determine the order of the UAV flying to all wind turbines to be inspected for detection; After each wind turbine to be inspected passes through other inspection points in sequence from the initial inspection point and then returns to the initial inspection point, obtain the inspection route of each wind turbine to be inspected; Generate the preliminary inspection route according to the determined order of the UAV flying to all wind turbines to be inspected for detection and the inspection routes of each wind turbine to be inspected.
[0010] Furthermore, the process of obtaining the final inspection route is as follows Use Bezier curve or spline curve to smooth the preliminary inspection route, and the smoothing curve formula is as follows: where is the parameter during smoothing processing, , is the control point.
[0011] On the second aspect, a wind turbine inspection route generation system based on UAV is provided for executing the above-mentioned wind turbine inspection route generation method based on UAV. The system includes: A data acquisition module for acquiring the nacelle position coordinates of the wind turbine, the position coordinates of the starting point of the UAV, and the position coordinates of the docking point; An inspection point generation module for generating inspection points at each wind turbine to be inspected according to the nacelle position coordinates of the wind turbine to be inspected; A preliminary route generation module for generating a preliminary inspection route through the inspection points at each wind turbine to be inspected, the position coordinates of the starting point of the UAV, and the position coordinates of the preset docking point; A route smoothing processing module, which is used to smooth the generated preliminary inspection route to obtain the final inspection route; An inspection execution module, which is used to control the UAV to perform inspections according to the final route and take pictures at each inspection point; An inspection return or continuation module, which is used to control the UAV to return to the initial point and go to the next fan after completing the inspection of one fan, or control the UAV to fly to a preset docking point.
[0012] Preferably, the data acquisition module includes: A collection and recognition unit, which is used to deploy the UAV to conduct preliminary aerial photography above the wind farm, collect the three-dimensional coordinate data of the fans in real time, and use computer vision technology to identify the position coordinates of the fan nacelles; A selection unit, which is used to select the UAV starting point according to the layout of the wind farm and the flight ability of the UAV, and determine the position coordinates of the UAV starting point; A docking point setting unit, which is used to set docking points according to inspection needs and determine the position coordinates of the docking points to ensure that the UAV can charge or transmit data at the docking points when performing tasks; A coordinate system synchronization unit, which is used to ensure that the position coordinates of the nacelles of all fans to be inspected, the position coordinates of the UAV starting point, and the position coordinates of the docking points are in the same coordinate system.
[0013] Preferably, the preliminary route generation module includes: An initial inspection point confirmation unit, which is used to obtain the minimum sum of distances for each fan to be inspected by calculating the sum of the distances from each inspection point of each fan to be inspected to the UAV starting point and the distances from each inspection point to the preset docking point, and confirm the initial inspection points of each fan to be inspected; A fan inspection sequence confirmation unit, which is used to determine the sequence of the UAV flying to all fans to be inspected by calculating the shortest distance for the UAV starting point to pass through the initial inspection points of each fan to be inspected in turn and finally fly to the preset docking point; An inspection point inspection sequence confirmation unit for each fan to be inspected, which is used to obtain the inspection route of each fan to be inspected after passing through other inspection points in turn from the initial inspection point and then returning to the initial inspection point; An inspection route generation unit, which is used to generate a preliminary inspection route according to the determined sequence of the UAV flying to all fans to be inspected and the inspection routes of each fan to be inspected.
[0014] In a third aspect, a computing device for a method for generating a fan inspection route based on a UAV is provided, including: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods described above.
[0015] Beneficial effects: By the method for generating a wind turbine inspection route based on an unmanned aerial vehicle (UAV), the inspection route of the UAV is automatically generated, solving the problems that the UAV inspection operation is relatively complex and some routes are difficult to operate manually. Description of the drawings
[0016] Figure 1 Is a flowchart of the method for generating a wind turbine inspection route based on an unmanned aerial vehicle; Figure 2 Is a block diagram of the system for generating a wind turbine inspection route based on an unmanned aerial vehicle. Detailed implementation manners
[0017] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention is provided with reference to the accompanying drawings.
[0018] In one embodiment, the present invention provides a method for generating a wind turbine inspection route based on an unmanned aerial vehicle, the method including: Obtaining the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the UAV starting point, and the position coordinates of a preset docking point; Generating inspection points at each wind turbine to be inspected according to the nacelle position coordinates of the wind turbines to be inspected, and generating a preliminary inspection route through the inspection points at each wind turbine to be inspected, the position coordinates of the UAV starting point, and the position coordinates of the preset docking point; Performing smoothing processing on the generated preliminary inspection route to obtain a final inspection route; The UAV flies to the first initial inspection point of the first wind turbine to be inspected according to the final inspection route, and successively passes through each inspection point of the first wind turbine to be inspected and stays for taking pictures. After the picture taking is completed, the UAV flies back to the first initial inspection point again, and then flies to the second initial inspection point of the second wind turbine to be inspected according to the final route until the picture taking of all wind turbines to be inspected is completed. The UAV flies to the preset docking point according to the final inspection route.
[0019] As a preferred solution of this embodiment, the specific process of obtaining the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the UAV starting point, and the position coordinates of the preset docking point is as follows: Deploying the UAV to conduct preliminary aerial photography above the wind farm, collecting three-dimensional coordinate data of the wind turbines in real time, and using computer vision technology to identify the nacelle position coordinates of the wind turbines; Select the UAV starting point according to the layout of the wind farm and the flight ability of the UAV, and determine the position coordinates of the UAV starting point; Set the docking points according to the inspection needs, and determine the position coordinates of the docking points to ensure that the UAV can be charged or data-transmitted at the docking points when performing tasks; Ensure that the nacelle position coordinates of all the wind turbines to be inspected, the position coordinates of the UAV starting point, and the position coordinates of the docking points are in the same coordinate system.
[0020] As an optimal solution of this embodiment, the specific process of ensuring that the nacelle position coordinates of all the wind turbines to be inspected, the position coordinates of the UAV starting point, and the position coordinates of the docking points are in the same coordinate system is as follows: Perform coordinate transformation through the coordinate transformation formula where T is the transformation matrix, including rotation, scaling, and displacement information, is the original coordinate, is the transformed coordinate; Perform translation or scaling through the translation formula and the scaling formula where , , are the translation amounts on the x, y, and z axes respectively, , , are the scaling factors on the x, y, and z axes respectively; Obtain the transformed nacelle coordinates of the wind turbine ,the position coordinates of the UAV starting point ,the position coordinates of the docking point where is the wind turbine number; After the transformation is completed, verify whether all the coordinates are in the same coordinate system. The formula is as follows: where represents the position coordinates of the UAV starting point or the position coordinates of the docking point; Compare the verification coefficient with the preset verification threshold If , it is determined that the coordinates are consistent. If , it is determined that the coordinates are inconsistent and the coordinate transformation needs to be performed again.
[0021] As an optimal solution of this embodiment, the process of generating inspection points at each wind turbine to be inspected according to the nacelle position coordinates of the wind turbine to be inspected is as follows: Generate inspection points for the nacelle position coordinates of each wind turbine where For the th inspection point coordinates of the th fan, is the position offset of the inspection point relative to the fan nacelle, , is the total number of nacelles of the fans to be inspected.
[0022] As a preferred solution of this embodiment, the process of generating the preliminary inspection route is as follows: By calculating the sum of the distances from each inspection point of each fan to be inspected to the UAV starting point and the distances from each inspection point to a preset docking point respectively, the minimum sum of distances of each fan to be inspected is obtained, and the initial inspection points of each fan to be inspected are confirmed; By calculating the shortest distance from the UAV starting point through the initial inspection points of each fan to be inspected in turn and finally flying to the preset docking point, the order of the UAV flying to all fans to be inspected for detection is determined; After each fan to be inspected passes through other inspection points in turn from the initial inspection point and then returns to the initial inspection point, the inspection route of each fan to be inspected is obtained; According to the determined order of the UAV flying to all fans to be inspected for detection and the inspection routes of each fan to be inspected, a preliminary inspection route is generated.
[0023] As a preferred solution of this embodiment, the process of obtaining the final inspection route is as follows Use Bezier curve or spline curve to smooth the preliminary inspection route, and the smoothing curve formula is as follows: Among them, is the path point after smoothing, is the parameter during smoothing processing, , is the control point.
[0024] In another embodiment, a fan inspection route generation system based on UAV is provided for executing the above-mentioned fan inspection route generation method based on UAV. The system includes: A data acquisition module, which is used to acquire the nacelle position coordinates of the fan, the position coordinates of the UAV starting point and the position coordinates of the docking point to ensure that the UAV can accurately identify the target; An inspection point generation module, which is used to generate inspection points at each fan to be inspected according to the nacelle position coordinates of the fan to be inspected, so as to ensure that the UAV will not miss key positions during the inspection process; The preliminary flight path generation module is used to generate a preliminary inspection flight path through the inspection points at each wind turbine to be inspected, the position coordinates of the UAV departure point, and the position coordinates of the pre-set docking points, which can help plan the flight path of the UAV; The flight path smoothing processing module is used to smooth the generated preliminary inspection flight path to obtain the final inspection flight path, which can improve the flight stability and safety and reduce sharp turns and drastic changes; The inspection execution module is used to control the UAV to return to the initial point after completing the inspection of one wind turbine and go to the next wind turbine, or control the UAV to fly to the pre-set docking point, which conforms to the basic operation process of UAV operation; The inspection return or continue module is used to control the UAV to return to the initial point after completing the inspection of one wind turbine and go to the next wind turbine, or control the UAV to fly to the pre-set docking point. Such a process can effectively cover all wind turbines to be inspected.
[0025] In implementation, the data acquisition module includes: The collection and recognition unit is used to deploy the UAV to conduct preliminary aerial photography above the wind farm, collect the three-dimensional coordinate data of the wind turbines in real time, and use computer vision technology to identify the position coordinates of the wind turbine nacelles; The selection unit is used to select the UAV departure point according to the layout of the wind farm and the flight ability of the UAV, and determine the position coordinates of the UAV departure point; The docking point setting unit is used to set docking points according to the inspection needs and determine the docking point position coordinates to ensure that the UAV can charge or transfer data at the docking point when performing tasks; The coordinate system synchronization unit is used to ensure that the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the UAV departure point, and the position coordinates of the docking points are in the same coordinate system.
[0026] In implementation, the preliminary flight path generation module includes: The initial inspection point confirmation unit is used to obtain the minimum sum of distances for each wind turbine to be inspected by calculating the sum of the distances from each inspection point of each wind turbine to be inspected to the UAV departure point and the distances from each inspection point to the pre-set docking point, and confirm the initial inspection points of each wind turbine to be inspected; The inspection sequence confirmation unit for wind turbines is used to determine the inspection sequence of the UAV flying to all wind turbines to be inspected by calculating the shortest distance for the UAV departure point to pass through the initial inspection points of each wind turbine to be inspected in turn and finally fly to the pre-set docking point; The inspection sequence confirmation unit for each inspection line point is used to obtain the inspection flight path of each wind turbine to be inspected when each wind turbine to be inspected passes through other inspection points in turn from the initial inspection point and returns to the initial inspection point; An inspection route generation unit is configured to generate a preliminary inspection route according to the determined sequence of the UAV flying to all the wind turbines to be inspected and the inspection routes of each wind turbine to be inspected.
[0027] In another embodiment, a computing device for a method of generating a wind turbine inspection route based on a UAV is provided, including: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods in the above-mentioned method.
[0028] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and these changes and modifications will all fall within the protection scope of the present invention.
Claims
1. A method for generating a wind turbine inspection route based on an unmanned aerial vehicle, characterized in that: The method comprises: Obtain the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the drone's starting point, and the position coordinates of the pre-set stop point; Generate inspection points at each wind turbine to be inspected according to the position coordinates of the cabin of the wind turbine to be inspected, and generate a preliminary inspection route through the inspection points at each wind turbine to be inspected, the position coordinates of the starting point of the UAV, and the position coordinates of the pre-set stop point; Smoothing the generated preliminary inspection route to obtain the final inspection route; According to the final inspection route, the UAV flies to the first initial inspection point of the first wind turbine to be inspected, and passes through each inspection point of the first wind turbine to be inspected in turn and stops to take pictures. After taking pictures, the UAV flies back to the first initial inspection point and flies to the second initial inspection point of the second wind turbine to be inspected according to the final route again, until all wind turbines to be inspected are photographed. The UAV flies to the pre-set stop point according to the final inspection route.
2. The method for generating a wind turbine inspection route based on a drone according to claim 1, characterized in that: The specific process of obtaining the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the starting point of the drone, and the position coordinates of the pre-set stop point is as follows: Deploy drones to take preliminary aerial photos above the wind farm, collect three-dimensional coordinate data of wind turbines in real time, and use computer vision technology to identify the coordinates of the wind turbine nacelle location; Select the starting point of the drone according to the layout of the wind farm and the flight capability of the drone, and determine the location coordinates of the starting point of the drone; According to inspection needs, set up docking points and determine the coordinates of the docking points to ensure that the drone can be charged or transmit data at the docking points when performing tasks; Ensure that the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the drone's starting point, and the position coordinates of the stop point are in the same coordinate system.
3. The method for generating a wind turbine inspection route based on a drone according to claim 2, characterized in that: The specific process of ensuring that the nacelle position coordinates of all wind turbines to be inspected, the position coordinates of the starting point of the drone, and the position coordinates of the docking point are in the same coordinate system is as follows: Through the coordinate transformation formula Perform coordinate transformation, where T is the transformation matrix, which contains rotation, scaling and displacement information. is the original coordinate, is the transformed coordinate; By translation formula and scaling formula To pan or zoom, , , are the translations on the x, y, and z axes respectively, , , are the scaling factors on the x, y, and z axes respectively; Get the converted wind turbine nacelle coordinates , the location coordinates of the drone’s starting point , the location coordinates of the stop point ,in, Number the fan; After completing the transformation, verify that all coordinates are in the same coordinate system. The formula is as follows: in, Indicates the location coordinates of the drone's departure point or the location coordinates of the stop point; The verification coefficient With the preset verification threshold Compare, if , then the coordinates are consistent. If , then the coordinates are judged to be inconsistent and need to be re-converted.
4. The method for generating a wind turbine inspection route based on a drone according to claim 3 is characterized in that: The process of generating the inspection point at each wind turbine to be inspected according to the nacelle position coordinates of the wind turbine to be inspected is as follows: Generate inspection points for each wind turbine's cabin location coordinates ,in, For the The first fan The coordinates of the inspection points, is the position offset of the inspection point relative to the wind turbine nacelle, , The total number of nacelles of the wind turbines to be inspected.
5. The method for generating a wind turbine inspection route based on a drone according to claim 4, characterized in that: The process of generating a preliminary inspection route is as follows: By calculating the sum of the distance from each inspection point of each wind turbine to be inspected to the starting point of the drone and the distance from each inspection point to the pre-set stop point, the sum of the minimum distances of each wind turbine to be inspected is obtained, and the initial inspection point of each wind turbine to be inspected is confirmed; The order in which the drones fly to all wind turbines to be inspected is determined by calculating the shortest distance from the starting point of the drone to the pre-set stop point after passing through the initial inspection point of each wind turbine to be inspected. Each wind turbine to be inspected passes through other inspection points in sequence from the initial inspection point and then returns to the initial inspection point, thereby obtaining the inspection route of each wind turbine to be inspected; A preliminary inspection route is generated according to the determined order in which the UAVs fly to all wind turbines to be inspected for inspection and the inspection route of each wind turbine to be inspected.
6. The method for generating a wind turbine inspection route based on a drone according to claim 5, characterized in that: The process of obtaining the final inspection route is as follows Use Bezier curve or spline curve to smooth the preliminary inspection route. The smooth curve formula is as follows: in, is the parameter for smoothing. , For the control point.
7. A wind turbine inspection route generation system based on a drone, used to execute the wind turbine inspection route generation method based on a drone according to any one of claims 1 to 6, characterized in that: The system comprises: A data acquisition module is used to obtain the position coordinates of the wind turbine cabin, the position coordinates of the starting point of the drone, and the position coordinates of the stop point; The inspection point generation module is used to generate the inspection point at each wind turbine to be inspected according to the nacelle position coordinates of the wind turbine to be inspected; A preliminary route generation module is used to generate a preliminary inspection route through the inspection points at each wind turbine to be inspected, the location coordinates of the departure point of the UAV and the location coordinates of the pre-set stop points; The route smoothing processing module is used to smooth the generated preliminary inspection route to obtain the final inspection route; The inspection execution module is used to control the drone to inspect according to the final route and take photos at each inspection point; The inspection return or continue module is used to control the drone to return to the starting point and go to the next wind turbine after completing the inspection of one wind turbine, or to control the drone to fly to a pre-set stop point.
8. The wind turbine inspection route generation system based on drone according to claim 7 is characterized in that: The data acquisition module includes: The collection and identification unit is used to deploy drones to take preliminary aerial photos above the wind farm, collect the three-dimensional coordinate data of the wind turbines in real time, and use computer vision technology to identify the coordinates of the wind turbine nacelle location; A selection unit, used to select a starting point of the UAV according to the layout of the wind farm and the flight capability of the UAV, and determine the position coordinates of the starting point of the UAV; The docking point setting unit is used to set the docking point according to the inspection needs and determine the coordinates of the docking point to ensure that the drone can be charged or transmit data at the docking point when performing the mission; The coordinate system synchronization unit is used to ensure that the cabin position coordinates of all wind turbines to be inspected, the position coordinates of the starting point of the drone, and the position coordinates of the stop point are in the same coordinate system.
9. The wind turbine inspection route generation system based on drone according to claim 7 is characterized in that: The preliminary route generation module includes: The initial inspection point confirmation unit is used to obtain the sum of the minimum distances of each wind turbine to be inspected by respectively calculating the sum of the distances from each inspection point of each wind turbine to be inspected to the starting point of the drone and the distances from each inspection point to a preset stop point, and confirm the initial inspection point of each wind turbine to be inspected; The wind turbine inspection sequence confirmation unit is used to determine the sequence in which the drone flies to all wind turbines to be inspected for inspection by calculating the shortest distance from the starting point of the drone to the preset stop point after passing through the initial inspection point of each wind turbine to be inspected in sequence; The inspection sequence confirmation unit of each inspection point is used for each wind turbine to be inspected to pass through other inspection points in sequence from the initial inspection point and then return to the initial inspection point to obtain the inspection route of each wind turbine to be inspected; The inspection route generating unit is used to generate a preliminary inspection route according to the determined sequence of the UAVs flying to all wind turbines to be inspected for inspection and the inspection route of each wind turbine to be inspected.
10. A computing device for generating a wind turbine inspection route based on an unmanned aerial vehicle, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods according to claims 1-6.