A fan automatic inspection path planning method

Abstract

The application discloses a kind of fan automatic inspection path planning methods, first by unmanned aerial vehicle identification hub and blade, positioning fan key point and calculates the position coordinates of fan key point;Then calculate fan orientation, blade fan angle, and according to fan orientation, blade fan angle, blade root coordinates and the length of blade calculates blade tip position coordinates;Then according to blade root position coordinates and blade tip position coordinates calculate cruise key point position coordinates;Finally control unmanned aerial vehicle according to the path specified and carry out inspection.The application does not need manual intervention to mark flight, reduces personnel investment and reduces operation risk, solves the limitation of unmanned aerial vehicle manual marking inspection, realizes according to the actual key coordinate position of fan and carries out inspection path planning, improves the inspection efficiency of fan blade.

Description

Technical Field

[0001] This invention relates to the field of wind turbine inspection technology, and in particular to an automatic wind turbine inspection path planning method. Background Technology

[0002] Wind power, as a major form of new energy development and utilization, is being widely developed and utilized worldwide. To improve the work efficiency of wind turbine maintenance personnel, the rapidly developing drone technology is gradually being applied to wind turbine blade inspection. Currently, there are two main methods for drone inspection. One is manual control of the drone by the inspector, with the drone carrying a high-definition camera to collect surface condition data of the wind turbine blades. This method requires a high level of drone operation skill from the inspector. The second method is point-marking flight, where the inspector first manually controls the drone to mark key locations on the blades, and then loads the marking results for waypoint flight. This method improves work efficiency to some extent compared to fully manual flight inspection and reduces the possibility of inspection flight failures. However, because the wind turbine's shutdown status and orientation differ each time it is inspected, and point marking is required for each inspection, it significantly increases the extra work of drone inspection. All of the above inspection methods suffer from variations in historical shooting angles, field of view, shooting distances, and focal lengths for the same wind turbine, resulting in historical inspection data that is not based on the same benchmark.

[0003] An existing UAV inspection system and method (a surveying UAV and a UAV-based surveying method) uses a UAV system in conjunction with a ground station for inspection, overcoming the problems of low efficiency and low safety of manual inspection. By taking close-up pictures of wind turbine blades with the UAV, the working status of the blades can be accurately grasped at the ground station. The accuracy of the data after analysis and comparison is also high, and the inspection results obtained are also relatively accurate. The UAV, combined with a gimbal, can achieve multi-angle and large-area inspection, avoiding inspection blind spots, improving inspection efficiency, greatly reducing the inspection burden of personnel, eliminating the need for manual inspection, and improving safety. However, this invention uses a point-marking flight method. When the UAV flies to the sample point to be measured, it hovers and performs multiple latitude and longitude point positioning and elevation point measurements at each sample point, resulting in multiple sets of measurement data. This leads to the inspection data not being based on the same benchmark. Summary of the Invention

[0004] The purpose of this invention is to provide an automatic inspection path planning method for wind turbines, which plans the inspection path based on the actual key coordinate positions of the wind turbines obtained automatically, thereby improving the inspection efficiency of wind turbine blades.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An automatic inspection path planning method for wind turbines includes the following steps:

[0007] S1: Wind turbine identification is performed using a drone. The wind turbine identification is obtained by identifying the hub and blades in the drone image, wherein there are several blades that are evenly distributed along the hub.

[0008] S2: Locate the key points of the wind turbine and calculate their coordinates. The key points include the hub key point and the blade root key point. The hub key point is the center of the hub, and the blade root key point is the lateral center of the blade root. Due to the large size of the blades, the blade tip position can be calculated based on the blade root position and blade angle. Therefore, the center hub and blade root are selected as the key points.

[0009] S3: Calculate the fan orientation and blade angle based on the coordinates of the key points at the hub and the root of the blade, and calculate the coordinates of the blade tip based on the fan orientation, blade angle, blade root coordinates and blade length.

[0010] S4: Calculate the coordinates of the key cruise points based on the coordinates of the blade root and the blade tip.

[0011] S5: Control the drone to perform inspections along the prescribed path.

[0012] The system uses a drone to identify the hub and blades, locate key points on the wind turbine (hub key points and blade root key points), and calculate the coordinates of these key points. Then, it calculates the turbine orientation and blade angle, and based on these coordinates, calculates the blade tip coordinates. Next, it calculates the coordinates of the navigation key points based on the blade root and tip coordinates. Finally, it controls the drone to perform inspections along a predetermined path. This system achieves automatic acquisition of the actual key coordinates of the wind turbine for inspection path planning, improving the efficiency of wind turbine blade inspections.

[0013] The wind turbine orientation and blade tip coordinates are calculated using trigonometric relationships based on the coordinates of key points at the hub, the blade root, and the blade length. The world coordinates of the key position 's' can be obtained using the formula...

[0014]

[0015] The calculation yields a unique world coordinate s, where u and v are the pixel coordinates of the detected target in the image, M is the camera intrinsic parameter, R is the rotation matrix, and t is the translation matrix. This method can then be used to calculate the key position coordinates s = (x, y, z) of the hub and blade root.

[0016] The specific process for calculating the wind turbine orientation in step S3 based on the position coordinates of the key points at the hub and the blade root is as follows:

[0017] The key point calculation is the actual position. After calculating the blade root coordinates, the gimbal pose is slightly adjusted, and several non-key coordinates are calculated using the same method, for a total of N key coordinates (x, y, z), where x is longitude, y is latitude, and z is altitude. When looking down at the wind turbine, its fitted plane is perpendicular to the ground, and a two-dimensional fitting of this plane can be directly used. Let y = bx + a represent this, and the least squares formula is established to obtain...

[0018]

[0019] Solving

[0020]

[0021]

[0022] The latitude and longitude relationship of the vertical plane in which the fan is oriented can be obtained, and then the included angle θ0 of the fan orientation can be obtained as tan θ0 = tan θ0. -1 b.

[0023] Step S3 calculates the actual angle between the blade and the vertical direction through image processing, linear feature recognition, and other processes.

[0024] The specific process for calculating the coordinates of the blade tip position in step S3 is as follows:

[0025] Let the root coordinates of a blade be (x, y, z), the calculated fan orientation be θo, the blade angle be θc, and the blade length be L. The actual coordinates of the blade tip are calculated in two steps. First, calculate the height h of the blade tip. Using the blade length L and the angle θc between the blade and the vertical, calculate the vertical projection length Δh of the blade. The height z of the blade root plus the projection length Δh equals the height h of the blade tip. Next, calculate the latitude and longitude (x0, y0) of the blade tip. Using the blade length L and the angle θc between the blade and the vertical, calculate the horizontal projection length Δl of the blade. This length is the distance between the latitude and longitude coordinates of the blade root and the blade tip. Combining this with the fan orientation θo, the latitude and longitude (x0, y0) of the blade tip can be calculated. Finally, the latitude, longitude, and height coordinates of the blade tip (x0, y0, h) can be obtained.

[0026] As a further option, step S1 includes:

[0027] S11: Control the wind turbine to be inspected to stop, place the drone equipped with camera, laser rangefinder and onboard computer in front of the wind turbine, control the drone to take off, keep the camera gimbal centered during the hub blade identification process, and control the drone pitch angle to always be 0°.

[0028] S12: The onboard computer of the UAV is pre-deployed with a target detection module for the wind turbine hub and blades. It acquires camera video streams in real time during the UAV's ascent and detects the wind turbine hub and blades through the camera video streams.

[0029] S13: After detecting the wind turbine hub and blade roots, the position of the UAV is finely adjusted so that the blade roots are all within the field of view, and key points of the wind turbine hub and blades are located by laser ranging.

[0030] S14: By controlling the pitch angle of the drone, the planned inspection path, data collection angle, distance, focal length, etc. can be kept consistent when inspecting the same wind turbine multiple times, which solves the problem of inconsistent and different historical data benchmarks.

[0031] As a further embodiment, step S2 includes:

[0032] S21: Process the detected images of the hub and blades, extract image features, and calculate the coordinates of key points at the hub and the root of the blades based on the image features.

[0033] S22: Calculate the pixel difference between the key point coordinates of the wind turbine hub and the image center, convert the pixel difference into the displacement of the drone, control the movement of the drone, and control the gimbal to center the wind turbine hub while making the wind turbine hub the center of the camera image, and the drone pitch angle is 0°.

[0034] S23: Activate the drone laser rangefinder function, measure the distance L from the gimbal to the key point, record the drone pose and gimbal pose when the key point of the wind turbine hub is located at the center of the image, and calculate the position coordinates of the hub.

[0035] S24: Repeat steps S22 and S23 to place the key points at the root of the leaf at the center of the camera image, and then calculate their position coordinates.

[0036] As a further option, step S3 includes:

[0037] S31: When the key point of the wind turbine hub is located at the center of the camera image, control the gimbal to pitch and pan, collect the three-dimensional coordinate information of the blade root, and perform plane fitting on the collected three-dimensional coordinates to obtain the wind turbine orientation angle.

[0038] S32: Process the image where the hub interest point is located at the center of the image, extract its line features, and calculate the angle between the blades and the angle between the blades and the vertical direction of the camera;

[0039] S33: Based on the relationship between coordinates, convert the blade angle and fan orientation into the actual blade orientation;

[0040] S34: Starting from the coordinates of the blade root and using the actual length of the blade as the distance, calculate the actual coordinates of the blade tip in the direction in which the wind turbine blades face.

[0041] As a further option, step S4 includes:

[0042] S41: Based on the calculated coordinates of key points at the blade root and blade tip, the cruise key points are obtained by expanding the safe distance. At the cruise key points, the drone's turning behavior and camera video acquisition switching behavior need to be controlled.

[0043] S42: Specify a waypoint based on the wind turbine's shape and angle. The specified waypoint includes the UAV's attitude and speed. The direction connecting the blade root and blade tip indicates that the UAV is flying in a straight line, while the transition from one blade surface to another at the blade tip indicates that the UAV is flying in a curve. The camera's upward viewing angle θ is based on the blade angle θ corresponding to the specified waypoint. c The calculation is performed using the following formula:

[0044] θ=±90-θ c .

[0045] S43: The UAV loads the planned waypoints and begins inspection according to the waypoint parameters. The inspection is completed when the last waypoint is reached. The UAV then returns to the designated position according to the preset instructions and ends the inspection.

[0046] By automatically acquiring the actual key coordinates of the wind turbine, the inspection path is planned, which solves the problem of reduced inspection efficiency caused by the need for drones to capture panoramic images of the wind turbine for path planning.

[0047] The beneficial effects achieved by this invention are as follows:

[0048] This invention uses a drone to identify the hub and blades, locate key points of the wind turbine, and calculate the coordinates of these key points. It then calculates the wind turbine orientation and blade angle, and based on these coordinates, the blade tip coordinates are calculated. Next, the key points for navigation are calculated using the blade root and tip coordinates. Finally, the drone is controlled to perform inspections along a predetermined path. This eliminates the need for manual intervention for point-marking flights, reducing personnel input and operational risks. It overcomes the limitations of manual drone point-marking inspections, enabling automatic acquisition of the wind turbine's actual key coordinates for inspection path planning, thus improving the efficiency of drone-based wind turbine blade inspections. Attached Figure Description

[0049] Figure 1 This is a flowchart of the automatic inspection path planning for wind turbine blades according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the location coordinate detection of key points at the wind turbine hub and the root of the wind turbine blades according to an embodiment of the present invention.

[0051] Figure 3 This is a schematic diagram of the wind turbine blade orientation angle detection according to an embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of the overall orientation detection of the fan according to an embodiment of the present invention;

[0053] Figure 5 This is a schematic diagram of the cruise key points and path planning results in an embodiment of the present invention. Detailed Implementation

[0054] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] The invention will be further described below with reference to the accompanying drawings and embodiments, such as... Figures 1-5 As shown,

[0056] like Figure 1 As shown, an automatic inspection system for wind turbine blades based on UAV laser ranging includes the following steps:

[0057] S1. Control the wind turbine to stop, and use a drone equipped with a camera, lidar, onboard computer and other loads to identify the hub and blades of the wind turbine;

[0058] S2. Calculate the key point coordinates of the wind turbine hub and the root of the wind turbine blades and adjust the UAV pose so that the key points are located in the center of the image. Then, calculate the position coordinates of the hub and the root of the wind turbine blades based on the laser range measurement value, the UAV pose, and the gimbal pose.

[0059] S3. Based on the image where the hub key points are located at the center of the image, the UAV pose, and the gimbal pose, calculate the overall orientation angle of the wind turbine, the included angle of the blades, and the coordinates of the blade tip position.

[0060] S4. Calculate the coordinates of key waypoints for automatic inspection by the UAV, and perform waypoint flight based on the calculated waypoints;

[0061] S5. The inspection is completed when the last waypoint is reached. The inspection returns to the designated position according to the preset instructions and ends.

[0062] Specifically, step S1 is as follows:

[0063] 1. Control the wind turbine to be inspected to stop, place the drone equipped with camera, laser rangefinder and onboard computer in front of the wind turbine, control the drone to take off, keep the camera gimbal centered during the hub blade identification process, and control the drone pitch angle to 0°.

[0064] 2. The onboard computer of the UAV is pre-deployed with a target detection module for the wind turbine hub and blades, which acquires camera video streams in real time during the UAV's ascent to detect the presence of the wind turbine hub and blades;

[0065] 3. After detecting the wind turbine hub and blade roots, the position of the UAV is finely adjusted so that the roots of all three wind turbine blades are in the field of view. Then, key points of the wind turbine hub and blades are located by laser ranging.

[0066] Specifically, this invention is mainly used in three-bladed wind turbines, which are Y-shaped with relatively distinct features at their center and three tail ends, aiding in the positioning calculation of the turbine blades. These correspond to the center hub and blade tip positions. Due to the large blade size, the blade tip position can be calculated based on the blade root position and blade angle; therefore, the center hub and blade root are selected as the key points.

[0067] The world coordinates of the key position s can be obtained from the formula

[0068]

[0069] The calculation yields unique world coordinates s, where u and v are the pixel coordinates of the detected target in the image, M is the calibrated camera intrinsic parameter, R is the rotation matrix, and t is the translation matrix. This method can be used to calculate the key position coordinates of the hub and blade root.

[0070] The specific process for calculating the wind turbine orientation in step S3 based on the position coordinates of the key points at the hub and the blade root is as follows:

[0071] The key point calculation is based on the actual position. After calculating the leaf root coordinates, the gimbal pose is slightly adjusted, and several non-key coordinates are calculated using the same method, resulting in a total of N key coordinates (x, y, z), where x is longitude, y is latitude, and z is altitude. For example... Figure 4 As shown, when viewed from above, the fitted plane of the wind turbine is perpendicular to the ground. A two-dimensional fit can be directly used to fit this plane. Let y = bx + a represent this, and establish the least squares formula to obtain...

[0072]

[0073] Solving

[0074]

[0075]

[0076] We can obtain the latitude and longitude relationship between the wind turbine's orientation and the vertical plane it occupies, and then obtain the wind turbine's orientation angle θ0 = tan -1 b;

[0077] In step S3, the blade angle is calculated through image processing and linear feature recognition, such as... Figure 3 The figure shows the actual angle between the blade and the vertical direction.

[0078] The specific process for calculating the coordinates of the blade tip position in step S3 is as follows:

[0079] Let the root coordinates of a certain blade be (x, y, z), and the calculated wind turbine orientation be θ. o blade angle θ c The blade length is L. The actual coordinates of the blade tip are calculated in two steps. First, the height h of the blade tip is calculated using the blade length L and the angle θ between the blade and the vertical direction. c Calculate the vertical projection length Δh of the blade. The height z at the leaf root plus the projection length Δh equals the height h at the leaf tip. Calculate the latitude and longitude (x0, y0) of the leaf tip using the blade length L and the angle θ between the blade and the vertical direction. c Calculate the horizontal projection length Δl of the blade, which is the distance between the latitude and longitude coordinates of the blade root and the blade tip, combined with the wind turbine orientation θ. o The latitude and longitude (x0, y0) of the leaf tip can be calculated, and the latitude, longitude and altitude coordinates (x0, y0, h) of the leaf tip can be obtained by combining them.

[0080] like Figure 2 As shown, step S2 specifically includes:

[0081] 1. Process the images of the detected hub and blades, extract image features, and calculate the coordinates of key points on the wind turbine hub and the coordinates of three key points at the blade roots based on the image features, denoted as P. c0 P c1 P c2 P c3 ;where P c0 For the key point of the wheel hub, P c1 P c2 P c3 All are key points at the leaf root, O c The center of the image.

[0082] 2. Calculate keypoint Pc0 and image center O. c The pixel difference is converted into the displacement of the drone, and the movement of the drone is controlled. During the process of centering the wind turbine hub in the image, the gimbal is controlled to return to center and the drone's pitch angle is 0°.

[0083] 3. Activate the drone's laser rangefinder function, measure the distance L from the gimbal to the key point, and record that the key point of the wind turbine hub is located at the center O of the image. c The drone pose and gimbal pose at that time are used to calculate the position coordinates P of the wheel hub.w0 ;

[0084] 4. Repeat steps 2, 3, and 4, successively adjusting the three key points P at the base of the leaf. c1 P c2 P c3 Located at the center of the image O c Then calculate its position coordinates P. w1 P w2 P w3 .

[0085] like Figure 3 , Figure 4 , Figure 5 As shown, step S3 specifically includes:

[0086] 1. When the key point of the wind turbine hub is located at the center of the image, control the gimbal to pitch and traverse, collect the three-dimensional coordinate information of N blade roots, perform plane fitting on the collected N three-dimensional coordinates, and obtain the wind turbine orientation angle θ0.

[0087] 2. Process the image where the hub's point of interest is located at the image center, extract its line features, and calculate the angles between the blades and the angle between the blades and the perpendicular direction of the camera. c1 P c2 P c3 The corresponding blade angle is denoted as θ. c1 θ c2 θ c3 ;

[0088] 3. Based on the relationship between coordinates, convert the blade angle and fan orientation into the actual blade orientation θ. w1 θ w2 θ w3 θ w ;

[0089] 4. Using the coordinates at the blade root as the starting point and the actual blade length as the distance, calculate the actual coordinates P of the blade tip in the direction the wind turbine blades face. w11 P w22 P w33 .

[0090] like Figure 3 and Figure 5 As shown, step S4 specifically includes:

[0091] 1. Based on the calculated coordinates of key points at the blade root and blade tip, perform safety distance dilation to initially calculate the critical flight points for UAV inspection, from P1 to P... 12 There are a total of 12 key waypoints;

[0092] 2. Specify the attitude, speed, and other parameters of the UAV and gimbal for each trackpoint based on the wind turbine's shape and angle. Specifically, set the UAV to fly in a straight line from the blade root to the blade tip (or from the blade tip to the blade root), and set it to fly in a curve when transitioning from one blade surface to another at the blade tip. Calculate the camera's pitch angle based on the blade angle corresponding to the specified trackpoint.

[0093] ;

[0094] θ c1 θ c2 θ c3 The angle between the fitted blade direction and the horizontal line of the image is θ1. c1 The corresponding camera pitch angle, θ2 is θ c2 The corresponding camera pitch angle, θ3 is θ c3 The corresponding camera tilt angle, Figure 3 This is a schematic diagram obtained from the upward angle of the wind turbine.

[0095] 3. The UAV loads the planned waypoints and begins inspection according to the waypoint parameters. The inspection is completed when the last waypoint is reached. The UAV then returns to the designated location according to the preset instructions and ends the inspection.

[0096] In this embodiment, there are three blades. Two, four, or more blades can also be used, but the three-blade configuration achieves the best balance between cost and benefit, so three blades are chosen in this embodiment. The drone identifies the hub and blades, locates key points of the wind turbine, and calculates their coordinates. Then, it calculates the wind turbine orientation and blade-to-wind turbine angle. Based on the wind turbine orientation, blade-to-wind turbine angle, blade root coordinates, and blade length, it calculates the blade tip coordinates. Next, based on the blade root and blade tip coordinates, it calculates the coordinates of the key navigation points. Finally, it controls the drone to perform inspections along a predetermined path, eliminating the need for manual intervention for point-marking flights. This reduces personnel input and operational risks, overcomes the limitations of manual drone point-marking inspections, and enables inspection path planning based on automatically acquired actual key coordinates of the wind turbine, thus improving the inspection efficiency of wind turbine blades.

[0097] Finally, it should be noted that the above embodiments are intended to illustrate the present invention more clearly, and are not intended to limit the scope of the present invention. After reading the present invention, any modifications of the present invention by those skilled in the art in various equivalent forms fall within the scope defined by the appended claims.

Claims

1. A method for automatic inspection path planning of wind turbines, characterized in that, Includes the following steps: S1: Wind turbine identification is performed using a drone. The wind turbine identification is obtained by identifying the hub and blades in the drone image, wherein there are several blades that are evenly distributed along the hub. S2: Locate the key points of the wind turbine and calculate the position coordinates of the key points of the wind turbine. The key points of the wind turbine include the hub key point and the blade root key point. The hub key point is the center of the hub, and the blade root key point is the lateral center of the blade root. S3: Calculate the wind turbine orientation and the angle between the blade and the horizontal direction based on the position coordinates of the key points at the hub and the blade root. Calculate the blade tip position coordinates based on the wind turbine orientation, the angle between the blade and the horizontal direction, the position coordinates of the key points at the blade root, and the blade length. The wind turbine orientation is obtained as follows: with the key point at the wind turbine hub located at the center of the camera image, control the gimbal to perform pitch and lateral movements, collect three-dimensional coordinate information of multiple blade roots, and perform planar fitting on the collected three-dimensional coordinate information to obtain the wind turbine orientation. S4: Calculate the position coordinates of the cruise key points based on the position coordinates of the key points at the blade root and the blade tip; S5: Control the drone to perform inspections along the prescribed path; Step S2 includes: S21: Process the detected images of the hub and blades, extract image features, and calculate the coordinates of key points at the hub and the root of the blades based on the image features. S22: Calculate the pixel difference between the key point coordinates of the wind turbine hub and the image center, convert the pixel difference into the displacement of the drone, control the movement of the drone, and control the gimbal to center the wind turbine hub while making the wind turbine hub the center of the camera image, and the drone pitch angle is 0°. S23: Activate the drone laser rangefinder function, measure the distance L from the gimbal to the key point, record the drone pose and gimbal pose when the key point of the wind turbine hub is located at the center of the image, and calculate the position coordinates of the hub. S24: Repeat steps S22 and S23 to place the key points at the root of the leaf at the center of the camera image, and then calculate the position coordinates of the key points at the root of the leaf.

2. The automatic inspection path planning method for wind turbines according to claim 1, characterized in that, Step S1 includes: The S11 controls the wind turbine to be inspected to stop, places the drone equipped with a camera, laser rangefinder and onboard computer in front of the wind turbine, controls the drone to take off, keeps the camera gimbal centered during the hub blade identification process, and controls the drone's pitch angle to 0°. S12: The onboard computer of the UAV is pre-deployed with a target detection module for the wind turbine hub and blades. It acquires camera video streams in real time during the UAV's ascent and detects the wind turbine hub and blades through the camera video streams. S13: After detecting the wind turbine hub and blade roots, the position of the UAV is finely adjusted so that the blade roots are all within the field of view, and key points of the wind turbine hub and blades are located by laser ranging.

3. The automatic inspection path planning method for wind turbines according to claim 1, characterized in that, Step S3 includes: S31: When the key point of the wind turbine hub is located at the center of the camera image, control the gimbal to pitch and pan, collect the three-dimensional coordinate information of the blade root, and perform plane fitting on the collected three-dimensional coordinates to obtain the wind turbine orientation angle. S32: Process the image where the hub key points are located at the center of the image, extract its line features, and calculate the angle between the blades and the angle between the blades and the horizontal direction; S33: Based on the relationship between the coordinates, convert the angle between the blade and the horizontal direction and the fan orientation into the actual orientation of the blade; S34: Starting from the position coordinates of the key point at the root of the blade, and using the actual length of the blade as the distance, calculate the actual coordinates of the blade tip in the direction in which the wind turbine blades face.

4. The automatic inspection path planning method for wind turbines according to claim 1, characterized in that, Step S4 includes: S41: Based on the calculated coordinates of the key points at the blade root and the blade tip, a safe distance expansion is performed to obtain the cruise key points. At the cruise key points, the drone's turning behavior and camera video acquisition switching behavior need to be controlled. S42: Specify the attitude and velocity parameters of the UAV and gimbal for each flight point based on the wind turbine's shape and angle. Specifically, the direction connecting the blade root and blade tip is set for straight flight, while the transition from one blade surface to another at the blade tip is set for curved flight. The camera's pitch angle... It is based on the angle between the blade corresponding to the specified track point and the horizontal direction. Calculated; S43: The UAV loads the planned waypoints and begins inspection according to the waypoint parameters. The inspection is completed when the last waypoint is reached. The UAV then returns to the designated position according to the preset instructions and ends the inspection.

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