Unmanned aerial vehicle path planning method and platform for fan inspection

Abstract

The invention provides an unmanned aerial vehicle path planning method and platform for fan inspection, and relates to the technical field of fan inspection, and the method comprises the steps: employing an unmanned aerial vehicle differential positioning technology, and obtaining the position information of a fan tower cylinder base; overlook flight parameters of the unmanned aerial vehicle are set by combining the position information of the fan tower drum base, and the unmanned aerial vehicle is controlled to collect a fan overlook image to determine the orientation of a fan hub; setting front-view flight parameters of the unmanned aerial vehicle by combining the position information of the tower drum base of the fan, and controlling the unmanned aerial vehicle to collect front-view images of the fan so as to determine the position information of fan blades; inputting the fan top view image and the fan front view image into a predetermined model library, and matching to obtain fan blade shape information; and performing routing inspection path planning based on the obtained information, and controlling the unmanned aerial vehicle to perform routing inspection operation. According to the method, the technical problems that the existing unmanned aerial vehicle fan inspection process depends on the mode of manually adjusting the blade position and fixing the route, and the inspection process is limited, and the consumed time is long are solved, and the inspection efficiency and safety of fan inspection are improved.

Description

Technical Field

[0001] The present application relates to the technical field of wind turbine inspection, and specifically to a method and platform for unmanned aerial vehicle (UAV) path planning for wind turbine inspection. Background Art

[0002] In today's wind power generation field, the application of drones has become an important part of intelligent operation and maintenance. Drone wind turbine inspection technology uses drones equipped with high-definition cameras and other sensors to monitor and analyze the operating status of wind turbines efficiently and safely.

[0003] The commonly used wind turbine drone inspection method is to fix the wind turbine blades into an inverted Y-shaped layout and design the drone's flight path. This method requires staff to climb to the top of the tower to manually adjust the blade position before inspection, which increases safety risks during the operation. The fixed route design lacks flexibility and cannot adjust the route according to the real-time position of the wind turbine. The blades need to be adjusted frequently, and the entire inspection process takes a long time, resulting in a significant decrease in inspection efficiency. In addition, this method may also lead to the omission of certain key areas, reducing the comprehensiveness and accuracy of the inspection. Summary of the invention

[0004] The present application provides a drone path planning method and platform for wind turbine inspection, which solves the technical problem that the existing drone wind turbine inspection process relies on manual adjustment of blade position and fixed flight path, resulting in a long inspection process and affecting the overall inspection efficiency. It achieves the technical effect of reducing human intervention, improving the inspection efficiency of wind turbine inspection, and reducing safety risks.

[0005] In view of the above problems, on the one hand, the present application provides a UAV path planning method for wind turbine inspection, the method comprising: using UAV differential positioning technology to obtain wind turbine tower base position information; setting the UAV's overhead flight parameters in combination with the wind turbine tower base position information, controlling the UAV to collect overhead images of the wind turbine according to the overhead flight parameters, and analyzing the wind turbine overhead images to determine the direction of the wind turbine hub; setting the UAV's front-view flight parameters in combination with the wind turbine tower base position information, controlling the UAV to collect front-view images of the wind turbine according to the front-view flight parameters, and positioning the blades according to the wind turbine front-view images to determine the wind turbine blade position information; inputting the wind turbine overhead image and the wind turbine front-view image into a predetermined model library, matching and obtaining the wind turbine blade shape information; performing inspection path planning based on the wind turbine tower base position information, the wind turbine hub direction, the wind turbine blade position information and the wind turbine blade shape information, outputting the planned inspection path, and controlling the UAV to perform inspection operations according to the planned inspection path.

[0006] On the other hand, the present application also provides a UAV path planning platform for wind turbine inspection, the platform comprising: a position information acquisition module, the position information acquisition module is used to use the UAV differential positioning technology to obtain the position information of the wind turbine tower base; a bird's-eye view acquisition module, the bird's-eye view acquisition module is used to set the UAV's bird's-eye view flight parameters in combination with the wind turbine tower base position information, control the UAV to collect the wind turbine bird's-eye view image according to the bird's-eye view flight parameters, and analyze the wind turbine bird's-eye view image to determine the direction of the wind turbine hub; a front view acquisition module, the front view acquisition module is used to set the UAV's front view flight parameters in combination with the wind turbine tower base position information Flight parameters, controlling the UAV to collect the front-view image of the wind turbine according to the front-view flight parameters, and positioning the blades according to the front-view image of the wind turbine to determine the position information of the wind turbine blades; a blade shape matching module, the blade shape matching module is used to input the top-view image and the front-view image of the wind turbine into a predetermined model library, and obtain the wind turbine blade shape information by matching; an inspection path planning module, the inspection path planning module is used to plan the inspection path based on the wind turbine tower base position information, the wind turbine hub orientation, the wind turbine blade position information and the wind turbine blade shape information, output the planned inspection path, and control the UAV to perform inspection operations according to the planned inspection path.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] Using the UAV differential positioning technology, the location information of the wind turbine tower base is obtained, providing accurate basic data for subsequent inspections. The UAV's overhead flight parameters are set in combination with the wind turbine tower base location information, and the UAV is controlled to collect the overhead image of the wind turbine according to the overhead flight parameters, and the overhead image of the wind turbine is analyzed to determine the direction of the wind turbine hub. The front view flight parameters of the UAV are set in combination with the wind turbine tower base location information, and the UAV is controlled to collect the front view image of the wind turbine according to the front view flight parameters, and the blades are positioned according to the front view image of the wind turbine to determine the position information of the wind turbine blades. The overhead view image and the front view image of the wind turbine are input into the predetermined model library, the wind turbine blade shape information is obtained by matching, and the specific state of the wind turbine is identified, providing accurate reference data for subsequent inspection path planning. Inspection path planning is performed based on the wind turbine tower base location information, the wind turbine hub direction, the wind turbine blade position information and the wind turbine blade shape information, and the planned inspection path is output, and the UAV is controlled to perform inspection operations according to the planned inspection path.

[0009] In summary, this application has achieved high-precision and intelligent wind turbine inspection by introducing drone differential positioning technology and intelligent path planning. Through accurate acquisition of top-view and front-view images and intelligent matching, the structure and status information of the wind turbine can be effectively identified, so as to plan the inspection route in a targeted manner without the need to manually adjust the blade position, thus improving the safety and efficiency of the inspection.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A flow chart of a method for planning a drone path for wind turbine inspection provided in an embodiment of the present application;

[0012] Figure 2 A schematic diagram of the structure of a UAV path planning platform for wind turbine inspection provided in an embodiment of the present application.

[0013] Description of the reference numerals: position information acquisition module 10 , overhead view acquisition module 20 , front view acquisition module 30 , leaf shape matching module 40 , inspection path planning module 50 . DETAILED DESCRIPTION

[0014] The embodiments of the present application provide a drone path planning method and platform for wind turbine inspection, thereby solving the technical problem that the existing drone wind turbine inspection process relies on manual adjustment of blade position and fixed routes, resulting in a long inspection process and affecting the overall inspection efficiency. The embodiment of the present application achieves the technical effect of reducing human intervention, improving the inspection efficiency of wind turbine inspection, and reducing safety risks.

[0015] Embodiment 1, as Figure 1 As shown, an embodiment of the present application provides a drone path planning method for wind turbine inspection, the method comprising:

[0016] Step S1: Use drone differential positioning technology to obtain the location information of the wind turbine tower base.

[0017] Furthermore, step S1 of the embodiment of the present application further includes:

[0018] Step S11: Use the drone differential positioning technology to collect the three-point position information of the wind turbine base.

[0019] Step S12: Calculate the wind turbine tower base position information based on the three-point position information, wherein the wind turbine tower base position information includes the longitude, latitude and altitude of the wind turbine tower base.

[0020] Specifically, the drone flies near the wind turbine tower and activates its differential positioning device. This device usually includes a GPS receiver and a base station. The base station is located at a known location, receives GPS signals and calculates the deviation from the actual location, and transmits the correction information to the drone, thereby improving its positioning accuracy.

[0021] The drone selects three points in the area near the wind turbine base and uses differential positioning equipment to collect the location information of the three points, including longitude, latitude and altitude. Since the wind turbine tower base is generally circular, the three selected points should be evenly distributed around the base to form an approximate triangle. The center of the circumscribed circle of the triangle formed by the three points is the center of the wind turbine tower base. According to geometric knowledge, the intersection of the perpendicular bisectors of the three sides of the triangle is the center of the circumscribed circle of the triangle. The longitude, latitude and altitude information of the center of the wind turbine tower base can be calculated through the location information of the three points, that is, the location information of the wind turbine tower base.

[0022] Through differential positioning technology, the drone obtains accurate information on the location of the wind turbine tower base, providing precise reference points for subsequent inspection tasks and ensuring that the drone can accurately locate and navigate during the inspection process.

[0023] Step S2: setting the overhead flight parameters of the UAV in combination with the wind turbine tower base position information, controlling the UAV to collect overhead images of the wind turbine according to the overhead flight parameters, and analyzing the overhead images of the wind turbine to determine the direction of the wind turbine hub.

[0024] Furthermore, step S2 of the embodiment of the present application further includes:

[0025] Step S21: Setting the overhead flight parameters based on the tower height, blade length and the position information of the wind turbine tower base, wherein the overhead flight parameters include overhead flight longitude and latitude and overhead flight altitude, the overhead flight longitude and latitude are the longitude and latitude of the wind turbine tower base, and the overhead flight altitude is the sum of the altitude, tower height, blade length and vertical safety distance.

[0026] Step S22: controlling the UAV to collect overhead images of the wind turbine according to the overhead flight longitude and latitude and the overhead flight altitude, analyzing the overhead images of the wind turbine based on the image collection orientation and the shooting hub orientation, and obtaining the direction of the wind turbine hub.

[0027] Specifically, tower height refers to the vertical distance from the ground to the top of the wind turbine tower. Blade length refers to the length of the wind turbine blade from the center of the hub to the tip of the blade. Blade length is directly related to the wind turbine's ability to capture wind. Bird's-eye view flight parameters refer to the control parameters of the drone when taking bird's-eye view photos, ensuring that the drone can capture images of the wind turbine in the best posture. Bird's-eye view flight parameters include bird's-eye view flight latitude and longitude and bird's-eye view flight altitude. The hub is a key component that connects the wind turbine blades to the tower, and its orientation determines the relative position of the blades.

[0028] First, based on the location information of the wind turbine tower base obtained in the previous step, set the drone's overhead flight parameters. The drone's overhead flight longitude and latitude will be directly set to the longitude and latitude of the wind turbine tower base to ensure that the drone flies in the correct position. The overhead flight altitude is set to the sum of the altitude, tower height, blade length and vertical safety distance. Among them, the altitude is extracted from the location information of the wind turbine tower base obtained in step S1, the tower height and blade length can be obtained from the wind turbine equipment manual, and the vertical safety distance is the minimum safety distance between the drone and the target object during flight, which can be determined through the drone design manual, usually 30 meters.

[0029] According to the set overhead flight latitude and longitude and the overhead flight altitude, the drone is controlled to fly according to these parameters and collect overhead images of the wind turbine. Through image processing technology, the wind turbine hub in the overhead image is identified and its orientation in the image is determined, that is, the shooting hub orientation. Combined with the shooting orientation of the drone, that is, the image collection orientation, the actual orientation of the wind turbine hub is inferred.

[0030] Through the above steps, the drone can be controlled to fly overhead and obtain accurate overhead images of the wind turbine, thereby determining the direction of the wind turbine hub, providing important information for subsequent blade positioning and inspection path planning.

[0031] Step S3: setting the front-view flight parameters of the UAV in combination with the wind turbine tower base position information, controlling the UAV to collect the front-view image of the wind turbine according to the front-view flight parameters, and positioning the blades according to the front-view image of the wind turbine to determine the position information of the wind turbine blades.

[0032] Furthermore, step S3 of the embodiment of the present application also includes:

[0033] Step S31: setting the flight parameters based on the tower height, blade length, wind turbine tower base position information and wind turbine hub orientation, wherein the flight parameters include flight longitude and latitude, flight altitude and horizontal distance, the flight longitude and latitude are calculated based on the longitude and latitude of the wind turbine tower base, wind turbine hub orientation, blade length and horizontal distance, and the flight altitude is the tower height.

[0034] Step S32: Control the UAV to collect the front-view image of the wind turbine according to the front-view flight longitude and latitude, the front-view flight altitude and the front-view flight horizontal distance, and locate the blades according to the front-view image of the wind turbine to obtain the position information of the wind turbine blades, wherein the position information of the wind turbine blades includes the position of the wind turbine blades and the angle between the blade closest to the wind turbine tower and the tower.

[0035] Specifically, after completing the acquisition of the overhead image, the front view flight parameters of the UAV are set in combination with the position information of the wind turbine tower base, and the UAV is controlled to collect the front view image of the wind turbine according to the front view flight parameters, and the blades are positioned according to the front view image of the wind turbine to determine the position information of the wind turbine blades. The front view flight parameters are the flight setting parameters of the UAV when performing frontal shooting, including the front view flight latitude and longitude, the front view flight altitude, and the front view flight horizontal distance.

[0036] The flight altitude is the flight altitude of the drone when taking a frontal shot, which is set to the tower height; the horizontal distance of the flight refers to the horizontal distance between the drone and the front of the wind turbine hub, which affects the field of view and clarity of image acquisition. It is generally set to 20 meters and can be adjusted appropriately according to actual conditions to ensure that all wind turbine blades are in the drone's shooting screen. The longitude and latitude of the flight are the specific geographical locations of the drone when taking a frontal shot. This location is calculated based on the longitude and latitude of the wind turbine tower base, the direction of the wind turbine hub, the length of the blades, and the horizontal distance of the flight. Specifically, the longitude and latitude of the flight are obtained by offsetting the tower base position toward the direction of the hub by a certain distance. The specific offset distance is the sum of the blade length and the horizontal distance of the flight.

[0037] According to the set flight latitude and longitude, flight altitude and horizontal distance, the drone is controlled to collect images facing the wind turbine to obtain the front view image of the wind turbine. The collected front view image is analyzed by image processing technology to identify the orientation of the wind turbine blades in the image. Combined with the drone collection position, the specific position of each leaf is located, and the angle between the blade closest to the tower and the tower is calculated. That is, the position information of the wind turbine blades. This angle provides accurate reference information for the subsequent formulation of the inspection route.

[0038] Step S4: inputting the wind turbine top view image and the wind turbine front view image into a predetermined model library, and matching and acquiring the wind turbine blade shape information.

[0039] Furthermore, step S4 of the embodiment of the present application also includes:

[0040] Step S41: extracting fan features from the fan overhead view image and the fan front view image using image recognition technology to obtain fan feature information.

[0041] Step S42: inputting the fan characteristic information into a predetermined model library to perform fan model matching to obtain the fan blade shape information.

[0042] Specifically, the predetermined model library is a database that stores different wind turbine models and blade shape information. The wind turbine overhead view image and wind turbine front view image collected in step S2 and step S3 are obtained, and input into the predetermined model library for data matching to determine the specific wind turbine model and blade shape information, so as to facilitate the subsequent targeted planning of the inspection route and improve the adaptability of the UAV wind turbine inspection process.

[0043] The specific matching process first uses image recognition technology to pre-process the acquired wind turbine top view and front view images, including denoising, contrast enhancement and image resizing, to improve image quality. Then, algorithms such as edge detection, contour extraction or template matching are used to extract specific feature information of the wind turbine from the pre-processed images, including key features such as the geometry of the wind turbine, the length and width of the blades, and the shape of the hub.

[0044] Then, the extracted fan feature information is integrated into a feature vector and input into a predetermined model library. A matching algorithm (for example, Euclidean distance, cosine similarity, etc.) is used to perform a similarity comparison analysis between the input feature information and the data in the model library to find a fan model similar to the input image feature vector, and return the blade shape information of the fan model, including the specific blade shape, material properties, and design parameters.

[0045] Through image recognition and data matching, the detailed blade shape information of the wind turbine to be inspected can be quickly obtained, which not only improves the efficiency of the inspection, but also provides accurate data support for subsequent inspection tasks.

[0046] Step S5: planning an inspection path based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, outputting the planned inspection path, and controlling the drone to perform inspection operations according to the planned inspection path.

[0047] Furthermore, step S5 of the embodiment of the present application further includes:

[0048] Step S51: Based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, an inspection path is planned to obtain an initial inspection path, wherein the initial inspection path includes a wind turbine blade leading edge image acquisition path, a wind turbine blade front side image acquisition path and a wind turbine blade back side image acquisition path.

[0049] Step S52: Obtain image overlap constraints, and generate the planned inspection path according to the image overlap constraints and the fan blade leading edge image acquisition path, the fan blade front side image acquisition path, and the fan blade back side image acquisition path.

[0050] Specifically, the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information, and wind turbine blade shape information determined in the previous steps are integrated to plan a specific inspection route. The generated inspection path is output as a flight instruction for the drone. These instructions detail the take-off point of the drone, the coordinates of each shooting point, and the required flight altitude. According to the planned path, the drone is controlled to perform the actual inspection operation. The drone will fly along the specified path and automatically capture images of the wind turbine when passing each shooting point.

[0051] The specific path planning process includes: integrating the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information to form a basic data set. Based on these basic data, the path planning algorithm, such as the Dijkstra algorithm or the A* algorithm, is used to plan the shooting angles and positions for image acquisition of the leading edge of the wind turbine blade, the front of the wind turbine blade and the back of the wind turbine blade, respectively, and generate multiple initial inspection paths for the image acquisition path of the leading edge of the wind turbine blade, the image acquisition path of the front of the wind turbine blade and the image acquisition path of the back of the wind turbine blade. When the drone flies along the leading edge of the blade, the waypoints are evenly divided according to the shape and length of the blade; when planning the front and back image acquisition path, generally 4 waypoints are planned for the front and back of each blade. Since each wind turbine has 3 blades, a total of 12 waypoints will be planned. In addition, an exit waypoint needs to be set, and a total of 13 waypoints are planned for each face. These waypoints are evenly distributed around the outline of the wind turbine blade.

[0052] Set image overlap constraints, that is, the overlap requirements between the two images in the continuous image acquisition process, to ensure that there is enough information overlap between adjacent images to improve the consistency and integrity of the inspection data. Usually the image overlap is at least 40%, and it can also be adjusted according to the actual inspection task requirements to achieve seamless splicing and accurate analysis in subsequent processing. According to the set image overlap constraints, the initial inspection path is adjusted, and the image acquisition path of the leading edge of the fan blade, the image acquisition path of the front of the fan blade, and the image acquisition path of the back of the fan blade are integrated to generate an optimized planned inspection path that meets the image overlap constraints and ensures that the drone can cover all areas that need to be inspected.

[0053] The above steps plan the inspection route based on comprehensive wind turbine information, which not only improves the efficiency and safety of the inspection, but also ensures that the drone can fully cover all key parts of the wind turbine, collect comprehensive and accurate wind turbine data, and provide reliable data support for the maintenance and management of the wind turbine.

[0054] Furthermore, the method described in the embodiment of the present application also includes:

[0055] The wind turbine overhead view image, the wind turbine front view image and the planned inspection path are transmitted to a predetermined storage device for storage and preservation.

[0056] Specifically, the collected wind turbine overhead images, wind turbine frontal images and planned inspection route data are sorted and packaged. The data packets are encrypted and transmitted through the network to a predetermined storage device, such as an internal server, cloud storage space or other secure data center, to ensure data security and traceability.

[0057] In summary, the drone path planning method for wind turbine inspection provided by the embodiment of the present application has the following technical effects:

[0058] Using the UAV differential positioning technology, the location information of the wind turbine tower base is obtained, providing accurate basic data for subsequent inspections. The UAV's overhead flight parameters are set in combination with the wind turbine tower base location information, and the UAV is controlled to collect the overhead image of the wind turbine according to the overhead flight parameters, and the overhead image of the wind turbine is analyzed to determine the direction of the wind turbine hub. The front view flight parameters of the UAV are set in combination with the wind turbine tower base location information, and the UAV is controlled to collect the front view image of the wind turbine according to the front view flight parameters, and the blades are positioned according to the front view image of the wind turbine to determine the position information of the wind turbine blades. The overhead view image and the front view image of the wind turbine are input into the predetermined model library, the wind turbine blade shape information is obtained by matching, and the specific state of the wind turbine is identified, providing accurate reference data for subsequent inspection path planning. Inspection path planning is performed based on the wind turbine tower base location information, the wind turbine hub direction, the wind turbine blade position information and the wind turbine blade shape information, and the planned inspection path is output, and the UAV is controlled to perform inspection operations according to the planned inspection path.

[0059] In general, the embodiment of the present application realizes high-precision and intelligent wind turbine inspection by introducing drone differential positioning technology and intelligent path planning. By accurately collecting top-view and front-view images and intelligent matching, the structure and status information of the wind turbine can be effectively identified, so as to plan the inspection route in a targeted manner without manually adjusting the blade position, thereby improving the safety and efficiency of the inspection.

[0060] Embodiment 2, as Figure 2 As shown, the embodiment of the present application provides a UAV path planning platform for wind turbine inspection, and the platform includes:

[0061] The position information acquisition module 10 is used to obtain the position information of the wind turbine tower base by using the drone differential positioning technology.

[0062] The overhead acquisition module 20 is used to set the overhead flight parameters of the drone in combination with the wind turbine tower base position information, control the drone to collect the overhead image of the wind turbine according to the overhead flight parameters, and analyze the overhead image of the wind turbine to determine the direction of the wind turbine hub.

[0063] The front view acquisition module 30 is used to set the front view flight parameters of the UAV in combination with the wind turbine tower base position information, control the UAV to collect the wind turbine front view image according to the front view flight parameters, and locate the blades according to the wind turbine front view image to determine the wind turbine blade position information.

[0064] The blade shape matching module 40 is used to input the wind turbine top view image and the wind turbine front view image into a predetermined model library, and match and obtain the wind turbine blade shape information.

[0065] The inspection path planning module 50 is used to plan the inspection path based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, output the planned inspection path, and control the UAV to perform inspection operations according to the planned inspection path.

[0066] Furthermore, the location information acquisition module 10 of the embodiment of the present application is also used to perform the following steps:

[0067] The three-point position information of the wind turbine base is collected using UAV differential positioning technology.

[0068] The wind turbine tower base position information is calculated based on the three-point position information, wherein the wind turbine tower base position information includes the longitude, latitude and altitude of the wind turbine tower base.

[0069] Furthermore, the overhead view acquisition module 20 in the embodiment of the present application is also used to perform the following steps:

[0070] The overhead flight parameters are set based on the tower height, blade length and the position information of the wind turbine tower base, wherein the overhead flight parameters include overhead flight longitude and latitude and overhead flight altitude, the overhead flight longitude and latitude are the longitude and latitude of the wind turbine tower base, and the overhead flight altitude is the sum of the altitude, tower height, blade length and vertical safety distance.

[0071] The drone is controlled to collect overhead images of the wind turbine according to the overhead flight longitude and latitude and the overhead flight altitude, and the overhead images of the wind turbine are analyzed based on the image collection orientation and the shooting hub orientation to obtain the direction of the wind turbine hub.

[0072] Furthermore, the face acquisition module 30 in the embodiment of the present application is also used to perform the following steps:

[0073] The upright flight parameters are set based on the tower height, blade length, wind turbine tower base position information and wind turbine hub orientation, wherein the upright flight parameters include upright flight longitude and latitude, upright flight altitude and upright flight horizontal distance, the upright flight longitude and latitude are calculated based on the longitude and latitude of the wind turbine tower base, the wind turbine hub orientation, blade length and upright flight horizontal distance, and the upright flight altitude is the tower height.

[0074] The drone is controlled to collect the front-view image of the wind turbine according to the front-view flight longitude and latitude, the front-view flight altitude and the front-view flight horizontal distance, and the blades are positioned according to the front-view image of the wind turbine to obtain the position information of the wind turbine blades, wherein the position information of the wind turbine blades includes the position of the wind turbine blades and the angle between the blade closest to the wind turbine tower and the tower.

[0075] Furthermore, the leaf shape matching module 40 in the embodiment of the present application is also used to perform the following steps:

[0076] The image recognition technology is used to extract the fan features from the fan overhead view image and the fan front view image to obtain the fan feature information.

[0077] The fan characteristic information is input into a predetermined model library for fan model matching to obtain the fan blade shape information.

[0078] Furthermore, the inspection path planning module 50 of the embodiment of the present application is also used to perform the following steps:

[0079] Inspection path planning is performed based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information to obtain an initial inspection path, wherein the initial inspection path includes a wind turbine blade leading edge image acquisition path, a wind turbine blade front side image acquisition path and a wind turbine blade back side image acquisition path.

[0080] The image overlap constraint is obtained, and the planned inspection path is generated according to the image overlap constraint and the fan blade leading edge image acquisition path, the fan blade front side image acquisition path, and the fan blade back side image acquisition path.

[0081] Furthermore, the platform described in the embodiment of the present application is also used to perform the following steps:

[0082] The wind turbine overhead view image, the wind turbine front view image and the planned inspection path are transmitted to a predetermined storage device for storage and preservation.

[0083] Through the above-mentioned detailed description of the UAV path planning method for wind turbine inspection in this specification, those skilled in the art can clearly understand the UAV path planning platform for wind turbine inspection in this embodiment. For the platform disclosed in Example 2, since it corresponds to the method disclosed in Example 1, it has corresponding functional modules and beneficial effects. For relevant matters, please refer to the description of the method part.

[0084] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A UAV path planning method for wind turbine inspection, characterized in that: include: Use drone differential positioning technology to obtain wind turbine tower base location information; The overhead flight parameters of the UAV are set in combination with the wind turbine tower base position information, the UAV is controlled to collect the overhead image of the wind turbine according to the overhead flight parameters, and the overhead image of the wind turbine is analyzed to determine the direction of the wind turbine hub; The front-view flight parameters of the UAV are set in combination with the wind turbine tower base position information, the UAV is controlled to collect the front-view image of the wind turbine according to the front-view flight parameters, and the blades are positioned according to the front-view image of the wind turbine to determine the position information of the wind turbine blades; Inputting the wind turbine top view image and the wind turbine front view image into a predetermined model library, and matching and acquiring the wind turbine blade shape information; Inspection paths are planned based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information, and wind turbine blade shape information, and the planned inspection paths are outputted. The UAV is controlled to perform inspection operations according to the planned inspection paths.

2. The UAV path planning method for wind turbine inspection according to claim 1 is characterized in that: Use drone differential positioning technology to obtain wind turbine tower base location information, including: Use drone differential positioning technology to collect three-point position information of the wind turbine base; The wind turbine tower base position information is calculated based on the three-point position information, wherein the wind turbine tower base position information includes the longitude, latitude and altitude of the wind turbine tower base.

3. The UAV path planning method for wind turbine inspection according to claim 2 is characterized in that: The method comprises: setting the overhead flight parameters of the drone in combination with the wind turbine tower base position information, controlling the drone to collect the overhead image of the wind turbine according to the overhead flight parameters, and analyzing the overhead image of the wind turbine to determine the direction of the wind turbine hub, including: The overlooking flight parameters are set based on the tower height, the blade length and the position information of the wind turbine tower base, wherein the overlooking flight parameters include the overlooking flight longitude and latitude and the overlooking flight altitude, the overlooking flight longitude and latitude are the longitude and latitude of the wind turbine tower base, and the overlooking flight altitude is the sum of the altitude, the tower height, the blade length and the vertical safety distance; The drone is controlled to collect overhead images of the wind turbine according to the overhead flight longitude and latitude and the overhead flight altitude, and the overhead images of the wind turbine are analyzed based on the image collection orientation and the shooting hub orientation to obtain the direction of the wind turbine hub.

4. The UAV path planning method for wind turbine inspection according to claim 3 is characterized in that: The front-view flight parameters of the UAV are set in combination with the wind turbine tower base position information, the UAV is controlled to collect the front-view image of the wind turbine according to the front-view flight parameters, and the blades are positioned according to the front-view image of the wind turbine to determine the position information of the wind turbine blades, including: The front view flight parameters are set based on the tower height, blade length, wind turbine tower base position information and wind turbine hub orientation, wherein the front view flight parameters include the front view flight longitude and latitude, the front view flight altitude and the front view flight horizontal distance, the front view flight longitude and latitude are calculated based on the longitude and latitude of the wind turbine tower base, the wind turbine hub orientation, blade length and the front view flight horizontal distance, and the front view flight altitude is the tower height; The drone is controlled to collect the front-view image of the wind turbine according to the front-view flight longitude and latitude, the front-view flight altitude and the front-view flight horizontal distance, and the blades are positioned according to the front-view image of the wind turbine to obtain the position information of the wind turbine blades, wherein the position information of the wind turbine blades includes the position of the wind turbine blades and the angle between the blade closest to the wind turbine tower and the tower.

5. The method for UAV path planning for wind turbine inspection according to claim 1, characterized in that: Inputting the wind turbine top view image and the wind turbine front view image into a predetermined model library, and matching and acquiring the wind turbine blade shape information, including: Extracting fan features from the fan overhead view image and the fan front view image using image recognition technology to obtain fan feature information; The fan characteristic information is input into a predetermined model library for fan model matching to obtain the fan blade shape information.

6. The method for UAV path planning for wind turbine inspection according to claim 1, characterized in that: Based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, an inspection path is planned, and a planned inspection path is output, including: Based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, an inspection path is planned to obtain an initial inspection path, wherein the initial inspection path includes a wind turbine blade leading edge image acquisition path, a wind turbine blade front image acquisition path and a wind turbine blade back image acquisition path; The image overlap constraint is obtained, and the planned inspection path is generated according to the image overlap constraint and the fan blade leading edge image acquisition path, the fan blade front side image acquisition path, and the fan blade back side image acquisition path.

7. The UAV path planning method for wind turbine inspection according to claim 1 is characterized in that: The wind turbine overhead view image, the wind turbine front view image and the planned inspection path are transmitted to a predetermined storage device for storage and preservation.

8. The UAV path planning platform for wind turbine inspection is characterized by: The platform is used to execute the method according to any one of claims 1 to 7, including: A position information acquisition module, wherein the position information acquisition module is used to obtain the position information of the wind turbine tower base by using the drone differential positioning technology; A bird's-eye view acquisition module, the bird's-eye view acquisition module is used to set the bird's-eye view flight parameters of the drone in combination with the wind turbine tower base position information, control the drone to collect the wind turbine bird's-eye view image according to the bird's-eye view flight parameters, and analyze the wind turbine bird's-eye view image to determine the direction of the wind turbine hub; A front view acquisition module, the front view acquisition module is used to set the front view flight parameters of the UAV in combination with the wind turbine tower base position information, control the UAV to collect the wind turbine front view image according to the front view flight parameters, and locate the blades according to the wind turbine front view image to determine the wind turbine blade position information; A blade shape matching module, wherein the blade shape matching module is used to input the fan top view image and the fan front view image into a predetermined model library, and match and obtain the fan blade shape information; The inspection path planning module is used to plan the inspection path based on the wind turbine tower base position information, wind turbine hub orientation, wind turbine blade position information and wind turbine blade shape information, output the planned inspection path, and control the drone to perform inspection operations according to the planned inspection path.

Images