An unmanned aerial vehicle autonomous inspection route automatic generation method suitable for ground wire sag change

Abstract

The application discloses a kind of unmanned plane autonomous inspection route automatic generation method suitable for ground wire sag variation, comprising: based on catenary equation, the vectorization analysis calculation of classified ground wire is carried out, and first vectorization ground wire is obtained;Simulate the sag variation of ground wire under different temperature conditions, obtain the second vectorization ground wire under different temperature conditions;First vectorization ground wire and second vectorization ground wire are interpolated, and complete ground wire point cloud data is generated;Based on ground wire point cloud data, obtain the relative position relationship of ground wire endpoint and tower, and then calculate the starting point and endpoint of ground wire;Calculate the distance between waypoints;From the starting point of ground wire, the position of waypoint is calculated with the distance between waypoints, photograph direction and compensation distance;Add exit waypoint, and generate route;Based on the number of waypoints, route length, unmanned plane performance carries out route splitting.The application can realize based on ground wire sag variation, so that unmanned plane carries out equidistance inspection for ground wire.

Description

Technical Field

[0001] This invention belongs to the field of power transmission line operation and maintenance technology, and in particular relates to an automatic generation method for autonomous inspection routes of UAVs applicable to conductor and ground wire sag changes. Background Technology

[0002] Overhead conductor and ground wire breaks have always been a significant threat to the safe and stable operation of power transmission networks, and such incidents occur frequently. Corrosion of the steel core due to loose strands in the conductor and ground wire can lead to breaks even under normal operating conditions. Before a conductor and ground wire breaks, there are usually varying degrees of defects such as broken strands, loose strands, and corrosion. Broken strands and loose strands are particularly common, and their causes are diverse.

[0003] For operational safety and accident prevention reasons, conductors and ground wires with severe corrosion, loose strands, or broken strands must be replaced. During routine inspections, frontline teams occasionally discover broken or loose strands in conductors and ground wires using traditional methods. However, these discoveries are somewhat accidental, and often involve critical defects such as loose or broken strands. Many other broken or loose strand issues are missed by traditional inspection methods, and numerous minor problems go undetected. Therefore, conducting close-range, detailed, and autonomous inspections of conductors and ground wires using drones is of significant practical importance. This allows for parallel, equidistant, efficient, complete, and standardized image acquisition of conductors and ground wires, which is crucial for preventing wire breakage accidents.

[0004] Autonomous drone inspection technology has been widely used in the power transmission field, but it mainly focuses on detailed inspection of towers and cannot meet the actual needs of conductor and ground wire inspection. Current intelligent drone inspection solutions for overhead conductors and ground wires have not yet achieved equidistant inspection technology based on conductor and ground wire sag changes. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide an automatic generation method for autonomous inspection routes of UAVs that is suitable for changes in conductor sag, so as to realize autonomous inspection of UAVs that is suitable for changes in conductor sag.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] An automatic generation method for autonomous inspection routes of unmanned aerial vehicles (UAVs) suitable for changes in conductor sag includes the following steps:

[0008] Step 1: Based on the catenary equation, perform vectorization analysis and calculation on the classified conductors and ground wires to obtain the first vectorized conductor and ground wire;

[0009] Step 2: Simulate the sag of the ground conductor under different temperatures to obtain the second vectorized ground conductor under different temperature conditions;

[0010] Step 3: Interpolate the first vectorized conductor obtained in Step 1 to generate a discrete point cloud, fill in the missing parts on the original collected conductor point cloud, and generate complete conductor point cloud data; interpolate the second vectorized conductor generated in Step 2 at different temperatures to generate complete conductor point cloud data under different temperature conditions.

[0011] Step 4: Based on the point cloud data of the conductor and ground wire obtained in Step 3, obtain the relative positional relationship between the endpoints of the conductor and ground wire and the tower, and then calculate the starting point and ending point of the conductor and ground wire to generate conductor and ground wire ledger information;

[0012] Step 5: Calculate the waypoint spacing based on the camera parameters, shooting distance, and overlap rate of the inspection drone;

[0013] Step 6: Starting from the ground wire starting point obtained in Step 4, calculate the waypoint position using the waypoint spacing, photographing direction, and compensation distance parameters;

[0014] Step 7: Add inbound and outbound waypoints at appropriate locations near the start and end points of the guide wire to generate the flight path;

[0015] Step 8: Split the route generated in Step 7 based on the number of waypoints, route length, and UAV performance.

[0016] Furthermore, step 1 specifically includes:

[0017] The characteristics of key categories of power transmission channel point clouds are analyzed. These key categories include towers, conductors and ground wires, insulators, ground channels, and buildings. Based on the classification standards of lidar scanning data in the power industry, a deep learning model suitable for the classification of conductor and ground wire point clouds of power transmission lines is determined to achieve conductor and ground wire point cloud classification. The vector line of the catenary equation of the conductor and ground wire is fitted and calculated to obtain the first vectorized conductor and ground wire.

[0018] Furthermore, step 2 specifically includes:

[0019] Assume (1) the overhead conductor is a perfectly elastic body, that is, it only undergoes elastic deformation when subjected to force, can be completely restored when the external force is removed, and there is no plastic deformation, and the elastic coefficient remains unchanged; (2) the overhead conductor is an ideal flexible line, and there is no stiffness effect; (3) the load is uniformly distributed on the overhead conductor.

[0020] Suppose the original length of the overhead conductor is L0, the manufacturing temperature is t0 and there is no stress, the span between the two suspension points is l and the height difference is h. At this time, the length of the conductor suspension curve is L, the temperature is t, the specific load is γ, and the axial stress is σ. x The average stress of the overhead conductor is σ cp The relationships between the parameters are shown below:

[0021]

[0022] If, under a certain temperature condition, i.e., in state I, the parameters in the plane containing the overhead conductor and ground wire are l1, h1, t1, γ1, σ1, σ cp1 L1, another temperature state, namely state II, has parameters l2, h2, t2, γ2, σ2, σ cp2 L2, since the length of the overhead conductor suspension curve is the same when converted to the original length under the same original state y=a in both states, the parameter relationship of the overhead conductor in the two states is as follows:

[0023]

[0024] Substitute the line length as L and the average stress as σ cp The equations for the catenary under the given conditions are given below:

[0025]

[0026] σ 01 and σ 02 L represents the stress at the lowest point of the sag under both conditions; l1 and l2 represent the spans under both conditions; L 01 and L 02 t1 and t2 represent the lengths of the overhead conductors without considering the elevation difference in the two states; β1 and β2 represent the elevation difference angles in the two states, tgβ1 = h1 / l1, tgβ2 = h2 / l2; t1 and t2 are the temperatures in the two states; the manufacturing temperature t0 is generally taken as 15℃.

[0027] To simplify the calculation, assume the suspension points are at the same height, i.e., the height difference is 0. In this case, h1 = 0, h2 = 0, tgβ1 = 0, tgβ2 = 0, and the above formula can be simplified to:

[0028]

[0029] Using the state equations, from the parameters l1, γ1, σ of state I 01 , t1, calculate the relevant parameters l2, γ2, σ for state II. 02 , t2, thus obtaining the catenary equation model under different temperature conditions, i.e., state II, thereby simulating the sag change under different temperature conditions, and thus obtaining the second vectorized ground conductor under different temperature conditions.

[0030] Further, step 4 specifically includes: obtaining the GPS positions of the towers at both ends of the overhead conductor and ground wire, setting the inspection direction to start from the smaller tower and end at the larger tower; manually controlling the drone to fly directly above the two towers and obtaining the latitude and longitude information of the towers via remote control; marking different conductor and ground wires between the towers during the flight; determining the center point coordinates of the two towers based on the obtained GPS positions of the two towers, using this as the center to detect the conductor and ground wire point cloud and vector lines within a 20m radius, manually selecting the matching vector line or point cloud, and the endpoint of the nearest detected conductor and ground wire point cloud or vector line is the starting point or ending point of that conductor and ground wire segment; generating conductor and ground wire ledger information based on this result, the conductor and ground wire ledger information includes tower number, tower base and tower top elevation, latitude and longitude information, tower spacing, span, and turning angle information.

[0031] Furthermore, step 5 specifically includes:

[0032] When the camera takes a picture, the width of the photo coverage is the actual length of the photo, and the shooting distance is the distance from the phase center to the ground wire;

[0033] Based on the trigonometric relationships between the field of view angle α, the shooting distance h, and the coverage width L, the following formula is derived:

[0034]

[0035] Based on the above formula, the parameters of commonly used inspection drone cameras are statistically analyzed, and the relationship between the shooting distance and coverage width of commonly used cameras and the coverage height at the corresponding shooting distance are calculated.

[0036] Based on the above method, the correspondence between commonly used camera shooting distances and coverage width and height is calculated. Since the waypoint spacing and the photographic coverage width have the following correspondence:

[0037] Waypoint spacing = Photo coverage width × Overlap rate

[0038] Based on this correspondence and the overlap rate and other parameters required for actual inspections, the required waypoint spacing under different overlap rate requirements is calculated when performing actual inspection tasks.

[0039] Furthermore, step 6 specifically includes: based on the waypoint spacing calculated in step 5, the center points of the photographs are evenly distributed from the starting point of the guide line to the ending point of the guide line, and the waypoint positions in three-dimensional space are calculated based on the photographing direction and compensation distance parameters.

[0040] The present invention has the following beneficial effects:

[0041] This invention simulates the sag variation of conductors and ground wires under different temperatures based on the catenary equation. It aims to correct the mismatch between the original conductor / ground wire point cloud position and the actual conductor / ground wire position caused by temperature changes, ensuring that the UAV can fly parallel and equidistantly along the conductor / ground wire and acquire high-quality images. By simulating the sag variation of the conductor / ground wire under actual operating conditions, a flight path matching the actual conductor / ground wire position is generated. This ensures that the UAV can acquire images parallel, equidistantly, efficiently, completely, and systematically along the conductor / ground wire, improving the efficiency and accuracy of UAV applications in fields such as power line inspection. Actual flight results verify that the simulated sag variation of the conductor / ground wire under different temperatures matches the actual situation. Attached Figure Description

[0042] Figure 1 This is a flowchart of one embodiment of the automatic generation method for autonomous inspection routes of UAVs applicable to changes in conductor sag proposed in this invention;

[0043] Figure 2 This is a flowchart illustrating the conductor vectorization technology according to an embodiment of the present invention.

[0044] Figure 3 This invention provides a simulation of the comparison between vectorized conductors and actual collected conductor point clouds at different temperatures in an embodiment of the invention.

[0045] Figure 4 The three-view diagrams are for the camera shooting principle of an embodiment of the present invention. Detailed Implementation

[0046] This invention discloses an automatic generation method for autonomous inspection routes of unmanned aerial vehicles (UAVs) applicable to changes in conductor sag. To make the objectives, technical solutions, and advantages of this invention clearer, the following describes the invention in further detail with reference to the accompanying drawings and embodiments.

[0047] like Figure 1 As shown, this embodiment of the invention provides a method for automatically generating autonomous inspection routes for UAVs based on conductor sag variations, comprising the following steps:

[0048] Step S401: Based on the catenary equation, perform vectorization analysis and calculation on the classified conductors and ground wires to obtain the first vectorized conductor and ground wire. Specifically, this includes:

[0049] The electric field lines are fitted using the catenary equation as the model basis. The catenary equation is as follows:

[0050]

[0051] Using the iterative least squares method, the parameters of the catenary model are solved from discrete points in the point cloud data acquired by lidar, thereby realizing the curve vector reconstruction and output of the overhead conductor and ground wire. Since the catenary equation lies in the plane, the optimal parameters of the conductor and ground wire generally need to be solved using a function approximation method in the Z-axis plane, and the fitted catenary model is then transformed to a three-dimensional coordinate system. The technical approach is as follows: Figure 2 As shown.

[0052] Step S402: Simulate the sag change of the conductor under different temperature conditions to obtain the second vectorized conductor under different temperature conditions.

[0053] The embodiments of the present invention simulate the sag change of the conductor under different temperature conditions to obtain the vectorized conductor under different temperature conditions. It is assumed that: (1) the overhead conductor is a perfectly elastic body, that is, it only undergoes elastic deformation when subjected to force, and can be completely restored when the external force is removed, while there is no plastic deformation and the elastic coefficient remains unchanged; (2) the overhead conductor is an ideal flexible line and there is no stiffness influence; (3) the load is uniformly distributed on the overhead conductor.

[0054] Suppose the original length of the overhead conductor is L0, the manufacturing temperature is t0 and there is no stress, the span between the two suspension points is l and the height difference is h. At this time, the length of the conductor suspension curve is L, the temperature is t, the specific load is γ, and the axial stress is σ. x The average stress of the overhead conductor is σ. cp The relationships between the parameters are shown below:

[0055]

[0056] As can be seen from the above formula, the original length of the overhead conductor within the span can be obtained by subtracting the elastic elongation and thermal elongation from the suspension length L of the overhead conductor. If the parameters in the plane containing the overhead conductor under a certain meteorological condition (State I) are l1, h1, t1, γ1, σ1, σ... cp1 L1, another meteorological state (state II) has the following parameters: l2, h2, t2, γ2, σ2, σ cp2 L2. Since the length of the overhead conductor suspension curve is the same when converted to the original length under the same initial condition in both states, the parameter relationship of the overhead conductor under the two states is as follows:

[0057]

[0058] Substitute the line length as L and the average stress as σ cp The equations for the catenary in the given state can be obtained as follows:

[0059]

[0060] σ 01 and σ 02 L represents the stress at the lowest point of the sag under both conditions; l1 and l2 represent the spans under both conditions; L 01 and L 02 The lengths of the overhead conductors are given under two conditions without considering the elevation difference (h1 = h2 = 0); β1 and β2 represent the elevation difference angles under the two conditions, tgβ1 = h1 / l1, tgβ2 = h2 / l2; t1 and t2 are the temperatures under the two conditions; the manufacturing temperature t0 is generally taken as 15℃.

[0061] To simplify the calculation, assume the suspension points are at the same height, i.e., the height difference is 0. In this case, h1 = 0, h2 = 0, tgβ1 = 0, tgβ2 = 0, and the above formula can be simplified to:

[0062]

[0063] Using the state equations, the parameters l1, γ1, and σ of state I can be derived. 01 t1, calculate the relevant parameters l2, γ2, σ of state II. 02 t2, thus obtaining the catenary equation model under different temperature conditions (state II), thereby simulating the sag change under different temperature conditions, and thus obtaining the second vectorized ground conductor under different temperature conditions. Figure 3 As shown in the figure, the vectorized conductors simulated at different temperatures in this embodiment have a good fit with the actual collected conductor point cloud.

[0064] Step S403: Interpolate the obtained first vectorized conductor ground line to further generate a discrete point cloud, fill in the missing parts on the original collected conductor ground line point cloud, generate complete conductor ground line point cloud data, and ensure the integrity of the conductor ground line point cloud; at the same time, interpolate the generated second vectorized conductor ground line at different temperatures to generate complete conductor ground line point cloud data under different temperature conditions.

[0065] Step S404: Based on the conductor / ground wire point cloud data obtained in step S403, acquire the relative positional relationship between the conductor / ground wire endpoints and the tower, then calculate the starting and ending points of the conductor / ground wire, and generate conductor / ground wire ledger information. Step S404 specifically includes:

[0066] Obtain the GPS positions of the towers at both ends of the overhead conductor and ground wire, with the inspection direction starting from the smaller tower and ending at the larger tower. A manually controlled drone flies directly above each tower and acquires their latitude and longitude information via remote control. During flight, different conductor and ground wire sections between the towers are marked. Based on the acquired GPS positions of the two towers, determine their center point coordinates. Using this as the center, detect the conductor and ground wire point cloud and vector lines within a 20m radius. Manually select the matching vector line or point cloud; the nearest detected endpoint of the conductor and ground wire point cloud or vector line is the start or end point of that section. Based on this result, generate relevant information about the conductor and ground wire, including but not limited to tower number, tower base and top elevation, latitude and longitude information, tower spacing, span, and turning angle.

[0067] Step S405: Calculate the waypoint spacing based on the camera parameters, shooting distance, and overlap rate of the inspection drone.

[0068] Based on the trigonometric relationship between the camera's field of view α, shooting distance h, and coverage width L, the relationship between the shooting distance and coverage width of commonly used inspection drone cameras can be calculated. Since the image pixel ratio is fixed, the ratio of the image coverage width to the coverage height is the same as the pixel ratio, allowing the calculation of the correspondence between shooting distance and coverage height. By statistically analyzing the parameters of commonly used inspection drone cameras, the correspondence between shooting distance and coverage width / height can be calculated. Based on the correspondence between waypoint spacing and image coverage width: waypoint spacing = image coverage width × overlap rate, the required waypoint spacing for actual inspection tasks can be calculated.

[0069] In this embodiment of the invention, taking a 4.2-meter shooting distance as an example, in a section of a certain route with a span of 1000 meters, the drone uses the camera parameters of the DJI Phantom 4RTK as a reference. Since a higher overlap rate results in a shorter waypoint spacing, more waypoints are photographed, and a longer flight time, shooting was conducted with different overlap rates of 1%, 2%, 5%, and 10%. It was found that adjacent photos taken with a 1% overlap rate do not miss conductor / ground wire information, ensuring the integrity of the route. Therefore, it is recommended to set the photo overlap rate to 1% during conductor / ground wire inspection.

[0070] In this embodiment of the invention, flight paths with shooting distances of 3.5 meters, 4.2 meters, and 5.0 meters are planned for a certain flight path with a span of 1000 meters. According to the camera parameters of the DJI Phantom 4 RTK drone, at a shooting distance of 3.5 meters, the waypoint spacing is 4.99 meters, and the number of waypoints is 196; at a shooting distance of 4.2 meters, the waypoint spacing is 5.9 meters, and the number of waypoints is 168; at a shooting distance of 5.0 meters, the waypoint spacing is 7.13 meters, and the number of waypoints is 136. Based on the photos taken under the above conditions, it was found that a shooting distance of 4-4.2 meters is optimal. This shooting distance meets the requirements for finding defects in the ground wire, and the photos can clearly show the texture and defects of the ground wire; at the same time, it can reduce the number of waypoints and improve the efficiency of flight operations; moreover, when the ground wire changes due to wind drift or sag in the point cloud, especially in areas with large spans and large sag, it can also increase flight safety and avoid crashes caused by shooting too close due to point cloud conditions.

[0071] Step S406: Starting from the ground wire starting point obtained in step S404, calculate the waypoint position using waypoint spacing, photographing direction, and compensation distance parameters;

[0072] Specifically, starting from the ground guide line and continuing to its endpoint, the center points for taking photos are evenly distributed according to the waypoint spacing. The waypoint positions in three-dimensional space are calculated based on parameters such as the shooting direction and compensation distance. The lighting conditions are predicted by the sun's position during the planned inspection time, and the shooting direction is adjusted in a timely manner to ensure that the actual photo results are clear and complete.

[0073] Step S407: Taking into full account the safe distance between the flight path and surrounding features or environment, add the start and end waypoints of the inbound and outbound flight paths to generate the UAV autonomous inspection flight path.

[0074] Step S408: Based on the number of waypoints, the length of the route, and the performance of the selected drone, the generated route is split. For example, the DJI Phantom 4 RTK drone generally ensures that there are about 150 waypoints on a single inspection route.

[0075] Following the above implementation method, after completing the safety check, the generated flight path is executed to perform the drone's autonomous inspection task.

[0076] This invention enables UAVs to perform equidistant inspections of ground wires based on the sag variation of the ground wire.

[0077] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0079] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0081] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for automatically generating autonomous inspection routes for unmanned aerial vehicles (UAVs) suitable for variations in conductor sag, characterized by its method. Includes the following steps: Step 1: Based on the catenary equation, perform vectorization analysis and calculation on the classified conductors and ground wires to obtain the first vectorized conductor and ground wire; Step 2: Simulate the sag of the ground conductor under different temperatures to obtain the second vectorized ground conductor under different temperature conditions; Step 3: Interpolate the first vectorized conductor obtained in Step 1 to generate a discrete point cloud, fill in the missing parts on the original collected conductor point cloud, and generate complete conductor point cloud data; interpolate the second vectorized conductor generated in Step 2 at different temperatures to generate complete conductor point cloud data under different temperature conditions. Step 4: Based on the conductor and ground wire point cloud data obtained in Step 3, obtain the relative positional relationship between the conductor and ground wire endpoints and the tower, and then calculate the starting point and ending point of the conductor and ground wire to generate conductor and ground wire ledger information; Step 5: Calculate the waypoint spacing based on the camera parameters, shooting distance, and overlap rate of the inspection drone; Step 6: Starting from the ground wire starting point obtained in Step 4, calculate the waypoint position using the waypoint spacing, photographing direction, and compensation distance parameters; Step 7: Add inbound and outbound waypoints at appropriate locations near the start and end points of the guide wire to generate the flight path; Step 8: Split the route generated in Step 7 based on the number of waypoints, route length, and UAV performance.

2. The method for automatically generating autonomous inspection routes for UAVs applicable to changes in conductor sag, as described in claim 1, is characterized in that: Step 1 specifically includes: The characteristics of key categories of power transmission channel point clouds are analyzed. These key categories include towers, conductors and ground wires, insulators, ground channels, and buildings. Based on the classification standards of lidar scanning data in the power industry, a deep learning model suitable for the classification of conductor and ground wire point clouds of power transmission lines is determined to achieve conductor and ground wire point cloud classification. The vector line of the catenary equation of the conductor and ground wire is fitted and calculated to obtain the first vectorized conductor and ground wire.

3. The method for automatically generating autonomous inspection routes for UAVs applicable to changes in conductor sag, as described in claim 1, is characterized in that: Step 2 specifically includes: Assume (1) the overhead conductor is a perfectly elastic body, that is, it only undergoes elastic deformation when subjected to force, can be completely restored when the external force is removed, and there is no plastic deformation, and the elastic coefficient remains unchanged; (2) the overhead conductor is an ideal flexible line, and there is no stiffness effect; (3) the load is uniformly distributed on the overhead conductor. Suppose the original length of the overhead conductor is L0, the manufacturing temperature is t0 and there is no stress, the span between the two suspension points is l and the height difference is h. At this time, the length of the conductor suspension curve is L, the temperature is t, the specific load is γ, and the axial stress is σ. x The average stress of the overhead conductor is σ cp The relationships between the parameters are shown below: ； If, under a certain temperature condition, i.e., in state I, the parameters in the plane containing the overhead conductor and ground wire are l1, h1, t1, γ1, σ1, σ cp1 L1, another temperature state, namely state II, has parameters l2, h2, t2, γ2, σ2, σ cp2 L2, since the length of the overhead conductor suspension curve is the same when converted to the original length in the same original state in both states, the parameter relationship of the overhead conductor in the two states is as follows: ； Substitute the line length as L and the average stress as σ cp The equations for the catenary under the given conditions are given below: ； ； σ 01 and σ 02 L represents the stress at the lowest point of the sag under both conditions; l1 and l2 represent the spans under both conditions; L 01 and L 02 t1 and t2 represent the lengths of the overhead conductors without considering the elevation difference in the two states; β1 and β2 represent the elevation difference angles in the two states, tgβ1=h1 / l1, tgβ2=h2 / l2; t1 and t2 are the temperatures in the two states; the manufacturing temperature t0 is taken as 15℃. To simplify the calculation, assume the suspension points are at the same height, i.e., the height difference is 0. In this case, h1=0, h2=0, tgβ1=0, tgβ2=0, and the above formula can be simplified to: ； Using the state equations, from the parameters l1, γ1, σ of state I 01 , t1, calculate the relevant parameters l2, γ2, σ of state II. 02 , t2, thus obtaining the catenary equation model under different temperature conditions, i.e., state II, thereby simulating the sag change under different temperature conditions, and thus obtaining the second vectorized ground conductor under different temperature conditions.

4. The method for automatically generating autonomous inspection routes for UAVs applicable to changes in conductor sag, as described in claim 1, is characterized in that: Step 4 specifically includes: obtaining the GPS positions of the towers at both ends of the overhead conductor and ground wire, with the inspection direction starting from the smaller tower and ending at the larger tower; manually controlling the drone to fly directly above the two towers and obtaining the latitude and longitude information of the towers via remote control; marking different conductor and ground wires between the towers during the flight; determining the center point coordinates of the two towers based on the obtained GPS positions of the two towers, using this as the center to detect the conductor and ground wire point cloud and vector lines within a 20m radius, manually selecting the matching vector line or point cloud, and the endpoint of the nearest detected conductor and ground wire point cloud or vector line is the starting point or ending point of that conductor and ground wire segment; generating conductor and ground wire ledger information based on this result, which includes tower number, tower base and tower top elevation, latitude and longitude information, tower spacing, span, and turning angle information.

5. The method for automatically generating autonomous inspection routes for UAVs applicable to changes in conductor sag, as described in claim 1, is characterized in that: Step 5 specifically includes: When the camera takes a picture, the width of the photo coverage is the actual length of the photo, and the shooting distance is the distance from the phase center to the ground wire; Based on the trigonometric relationships between the field of view angle α, the shooting distance h, and the coverage width L, the following formula is derived: ； Based on the above formula, the parameters of commonly used inspection drone cameras are statistically analyzed, and the relationship between the shooting distance and coverage width of commonly used cameras and the coverage height at the corresponding shooting distance are calculated. Based on the above method, the correspondence between commonly used camera shooting distances and coverage width and height is calculated. Since the waypoint spacing and the photographic coverage width have the following correspondence: Waypoint spacing = Photo coverage width × Overlap rate; Based on this correspondence and the overlap rate parameter requirements of actual inspections, the required waypoint spacing under different overlap rate requirements when performing actual inspection tasks is calculated.

6. The method for automatically generating autonomous inspection routes for UAVs applicable to changes in conductor sag, as described in claim 1, is characterized in that: Step 6 specifically includes: based on the waypoint spacing calculated in Step 5, the center points of the photographs are evenly distributed from the starting point of the guide line to the ending point of the guide line, and the waypoint positions in three-dimensional space are calculated based on the photographing direction and compensation distance parameters.

Images