Method for mounting and dismounting assembled grounding wire of high-voltage overhead line

Abstract

The invention discloses a high-voltage overhead line assembly type grounding wire mounting and dismounting method, which realizes intelligent mounting and dismounting of a high-voltage overhead line grounding wire through an electric mounting and dismounting device carried by an unmanned aerial vehicle, utilizes an AI visual identification module to accurately position a hanging point, plans an optimal path through a Dijkstra algorithm, and dynamically avoids obstacles in a flight process. The operation safety and efficiency are improved; the flight path, the installation time and the lock catch state are uploaded in real time through the block chain operation recording module, the transparency and traceability of data are guaranteed, the risk of manual climbing is avoided, the manpower and equipment cost is reduced, meanwhile, the emergency processing capacity is improved, and the system can quickly respond to complex or emergency power operation requirements.

Description

Technical Field

[0001] The invention belongs to the field of grounding wire installation and removal, and in particular, relates to a method for installing and removing an assembled grounding wire for a high-voltage overhead line. Background Art

[0002] High-voltage overhead lines play an important role in the power transmission system. In order to ensure the safety of line maintenance and equipment installation, it is usually necessary to install grounding wires on the conductors to prevent residual current on the lines from causing danger to operators. The traditional method of installing grounding wires relies on manual operation. Power workers need to climb poles or use aerial work vehicles to complete installation and removal. This process not only poses safety hazards such as falling and electric shock, but also consumes a lot of time and manpower, and it is difficult to cope with complex or emergency power operation environments. Therefore, combining drone technology and intelligent control systems to install and remove grounding wires has become an efficient and safe new solution.

[0003] The application of drones in power systems is becoming increasingly popular. Drones can carry electric assembly and disassembly devices for remote control, avoiding the risk of manual climbing. At the same time, using AI visual recognition modules and path planning systems, they can accurately identify the shape of wires, adjust the flight path in real time, and avoid obstacles dynamically. The introduction of blockchain technology further ensures the transparency and immutability of operating data, providing reliable support for data management during power maintenance and inspection.

[0004] In view of this, the present invention is proposed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a method for installing and removing an assembled grounding wire for a high-voltage overhead line, thereby solving the problems raised in the above-mentioned background technology.

[0006] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0007] A method for installing and removing an assembled grounding wire for a high-voltage overhead line adopts a ground station, an unmanned aerial vehicle and an electric assembly and disassembly device to realize the installation and removal of the grounding wire, comprising the following steps:

[0008] S1: The drone body carries the electric assembly and disassembly device through the finger cylinder, and activates the camera, LiDAR and ultrasonic sensor, while enabling the AI ​​visual recognition module and path planning system;

[0009] S2: The drone takes off and flies to the target overhead line area, uses the AI ​​visual recognition module to collect wire data through the camera, identifies the wire shape and locates the ground wire hanging point, and then feeds the detection results back to the ground station;

[0010] S3: Based on AI recognition results, the path planning system combines data from LiDAR and ultrasonic sensors, uses the Dijkstra algorithm to calculate the flight path, and dynamically avoids obstacles during flight;

[0011] S4: After the drone arrives at the target location, the control unit drives the rotating screw and the movable buckle ring in the electric assembly and disassembly device to fix the ground wire on the conductor, completing the installation of the ground wire. When disassembling, the control unit drives the electric assembly and disassembly device to release the locking clamp and remove the ground wire;

[0012] S5: During the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, locking status and detection data of the drone in real time and uploads it to the blockchain network.

[0013] Optionally, the ground station initializes the drone and electric device, checks the battery level and sensor status, and starts the AI ​​visual recognition module and data transmission module. After receiving the command, the drone takes off vertically and flies to the target overhead line area along a preset path;

[0014] After the drone arrives at the target area, the camera starts collecting images and video data of the wires, and the AI ​​visual recognition module pre-processes the images to optimize clarity and remove noise;

[0015] The pre-processed image data is passed to the AI ​​visual recognition module, which uses the YOLO algorithm to analyze the shape, position and state of the wire. By analyzing the length, curvature and distance between adjacent wires, the module determines the most suitable hanging point for installing the ground wire.

[0016] After analyzing the shape of the wire, the AI ​​visual recognition module calculates the location of the optimal hanging point in the form of three-dimensional coordinates and connects it to the drone's path planning system.

[0017] Optionally, the steps of using the YOLO algorithm to analyze the shape, position and state of the wire are:

[0018] YOLO divides the image into S×S grids, each of which predicts multiple bounding boxes and their confidences, expressed as Among them, P(C) is the probability that the grid contains a wire, represents the predicted bounding box of grid (i, j), x and y are the center coordinates of the bounding box, w and h are the width and height, p c is the confidence score, and then the non-maximum suppression algorithm is used to retain the bounding box with the highest confidence, which is expressed as: Among them, IoU(B i , B j ) represents two bounding boxes B i and Bj The bounding box will be retained only when the intersection-and-union ratio is less than the threshold;

[0019] Based on the selected valid bounding box, the system further analyzes the curvature of the wire, which is expressed as y=a0+a1x+a2x2+…+a n xn, where a0, a1, ..., a n is the coefficient of the fitting polynomial, which is used to describe the curvature change of the conductor. Finally, the most suitable hanging point for installing the grounding wire is recommended at the key node of the conductor, and the hanging point coordinate expression is generated: (X 挂点 , Y 挂点 , Z 挂点 )=(x GPS ,y GPS ,h 挂点 ), where (X 挂点 , Y 挂点 , Z 挂点 ) is the recommended hanging point coordinate, (x GPS ,y GPS ) is the GPS coordinate of the current position of the drone, h 挂点 is the height of the hanging point.

[0020] Optionally, after receiving these data, the path planning system starts the flight path calculation module to generate an initial flight path for the UAV and ensure that the path remains aligned with the coordinates of the hanging point;

[0021] When the drone is preparing to fly, the LiDAR and ultrasonic sensors begin to synchronously collect data about the surrounding environment and detect potential obstacles in the flight path, such as trees, buildings, or power towers. The path planning system performs a preliminary analysis based on the sensor data to determine the distribution of obstacles on the path.

[0022] Based on the target hanging point coordinates identified by AI and the obstacle data collected by sensors, the path planning system uses the Dijkstra algorithm to calculate the optimal flight path. The algorithm dynamically selects the shortest path according to the node weights and optimizes it based on the initial path.

[0023] The drone flies along the calculated optimal path and updates the environmental data in real time during the flight. LiDAR and ultrasonic sensors continuously detect new obstacles that may appear. Once an obstacle is found blocking the path, the system will instantly update the node weights and recalculate the alternative path using the Dijkstra algorithm.

[0024] After avoiding obstacles, the UAV continues to fly to the hanging point and calibrates the coordinates through the path planning system to ensure that the UAV is in the best staying position when it arrives above the hanging point. At this time, the UAV is ready to enter the installation phase, and the path planning and obstacle avoidance tasks are completed.

[0025] Optionally, the UAV path planning system discretizes the flight area into several nodes and constructs a weighted directed graph G = (V, E), where V represents a node set, E represents directed edges between nodes, and each edge e ij ∈E gives weight w ij , represents the flight cost between node i and node j. The weight is affected by distance, energy consumption and environmental conditions. Its expression is: w ij =d ij +α·C ij , where d ij is the distance between nodes i and j, C ij is the energy consumption cost, α is the energy consumption impact coefficient;

[0026] Next, the UAV path planning system takes the starting point s of the UAV as the initial node, uses the Dijkstra algorithm to gradually select the edge with the smallest weight, updates the minimum path from the starting point to other nodes, and defines D(v) as the shortest path weight from the starting point s to the node v. Initially, D(s) = 0, and the path weights of other nodes are set to ∞. The expression is: Among them, v and v are two adjacent nodes, and the algorithm selects the edge with the smallest weight when updating the path;

[0027] The drone takes off along the optimal path calculated by the Dijkstra algorithm and collects sensor data in real time. LiDAR and ultrasonic sensors monitor obstacles in the flight environment and upload the detected obstacle information to the path planning system. If there are no obstacles on the current path, the system maintains the original flight path.

[0028] When the sensor detects a new obstacle in the flight path, the system adds the weights w of the affected node and its neighboring nodes. ij Adjusted to a higher value to represent the high cost of flying in an obstacle area, the expression is: ij =w ij +β·O ij , where O ij represents the obstacle influence coefficient between nodes i and j, and β is the obstacle influence weight.

[0029] Optionally, when an obstacle makes the path infeasible, the system runs the Dijkstra algorithm again based on the updated node weights, and recalculates an alternative path from the current UAV position to the target position. The new path also guarantees the minimum weight and avoids obstacle areas. Once the alternative path calculation is completed, the system immediately calibrates the flight direction of the UAV so that it continues to fly along the new path. The UAV dynamically adjusts its flight altitude and direction to ensure safe flight to the target position in a complex environment. After the UAV arrives at the target position smoothly according to the planned path, the system records the flight path and obstacle avoidance data, and uploads it to the ground station for confirmation and archiving. At this time, the path planning task is completed, and preparations are made for the installation or removal of the ground wire.

[0030] Optionally, the electric assembly and disassembly device includes a hook, a motor, and a box body, the lower end of the hook is fixed on the box body, a through hole is opened on one side of the hook, the bottom of the inner wall of the box body is fixedly connected to the motor, the output end of the motor is fixedly connected to a rotating screw rod passing through the box body through the through hole, and a movable buckle ring is threadedly connected to the rotating screw rod, the movable buckle ring is arranged opposite to the opening of the hook, and the side wall of the movable buckle ring is tightly fitted on the side wall of the hook, and the movable buckle ring and the hook form the locking clamp.

[0031] Optionally, during installation, pass the grounding wire through the double holes at the lower end of the hook, and ensure that the grounding wire is firmly fixed in the locking clamp, rotate the screw to adjust the opening between the movable buckle ring and the hook, and completely lock the grounding wire in the clamp to prepare for hanging; after the drone adjusts its position, the control unit drives the electric device to rotate the screw to open the movable buckle ring. After the hook is tightly buckled on the wire, the system rotates the screw again, and the movable buckle ring and the hook are closed again, so that the box is firmly hung on the wire; after the installation is completed, the drone detaches from the box and returns to the ground, completing the installation task of the grounding wire. The drone uploads the installation data to the ground station in real time and enters a standby state to prepare for the next task;

[0032] During disassembly, the drone is started to fly to the disassembly point and then reconnected with the box. The drone takes off and flies to the target hanging point to prepare for the disassembly of the grounding wire. After the drone arrives at the hanging point, the electric opening and closing device is started through the control system, and the screw is rotated to adjust the movable buckle ring so that the buckle ring is gradually loosened and separated from the hook. The grounding wire is released from the locking clamp and is ready for recovery. After the movable buckle ring is fully opened, the grounding wire is separated from the wire, and the drone removes the box from the wire through the hook. Finally, the drone carries the box and the removed grounding wire back to the ground station to complete the disassembly task. The system synchronously uploads the disassembly data for review and recording. This application uses a finger cylinder when clamping the box, and its control is wirelessly controlled through the ground station.

[0033] Optionally, during the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, lock status and detection data of the drone in real time and uploads it to the blockchain network in the following steps:

[0034] Before the drone takes off, the blockchain operation recording module is started synchronously with the flight control system and establishes a secure connection with the blockchain network. After the drone takes off, the module continuously collects GPS coordinates and flight path data, and uploads them to the blockchain network at fixed time intervals. Then, when the ground wire is installed at the hanging point, the module records the start and end time of the installation, as well as the status change of the locking clamp. When performing the disassembly task, the module synchronously records the disassembly time and equipment operation status. After completing the flight, installation and disassembly tasks, all data is packaged into blocks and uploaded to the blockchain network.

[0035] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all the advantages described below at the same time:

[0036] The present invention realizes the intelligent installation and removal of the high-voltage overhead line grounding wire by carrying an electric assembly and disassembly device on a drone, accurately locates the hanging point using an AI visual recognition module, and plans the optimal path through the Dijkstra algorithm, dynamically avoids obstacles during flight, and improves the safety and efficiency of the operation; the flight path, installation time and lock status are uploaded in real time through the blockchain operation recording module to ensure the transparency and traceability of the data, avoid the risk of manual climbing, reduce manpower and equipment costs, and at the same time improve the emergency handling capability, so that it can quickly respond to complex or urgent power operation needs.

[0037] The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0039] In the figure:

[0040] Figure 1 This is a flow chart of the ground wire installation and removal method;

[0041] Figure 2 This is one of the schematic diagrams of the three-dimensional structure of the drone and the box;

[0042] Figure 3 This is the second schematic diagram of the three-dimensional structure of the drone and the box.

[0043] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0044] 1. Drone 1; 2. Hook; 3. Box; 4. Rotating screw; 5. Movable buckle ring; 6. Motor.

[0045] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but are intended to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0046] The present invention will now be described in further detail with reference to the accompanying drawings.

[0047] See also Figure 1-3 As shown, in this embodiment, a method for installing and removing an assembled grounding wire for a high-voltage overhead line is provided, which uses a ground station, a drone 1 and an electric assembly and disassembly device to achieve the installation and removal of the grounding wire, including the following steps:

[0048] S1: The main body of drone 1 carries the electric assembly and disassembly device through the finger cylinder, and activates the camera, LiDAR and ultrasonic sensor, while enabling the AI ​​visual recognition module and path planning system;

[0049] S2: Drone 1 takes off and flies to the target overhead line area, uses the AI ​​visual recognition module to collect wire data through the camera, identifies the wire shape and locates the ground wire hanging point, and then feeds the detection results back to the ground station;

[0050] S3: Based on AI recognition results, the path planning system combines data from LiDAR and ultrasonic sensors, uses the Dijkstra algorithm to calculate the flight path, and dynamically avoids obstacles during flight;

[0051] S4: After the drone 1 arrives at the target position, the control unit drives the rotating screw and the movable buckle ring in the electric assembly and disassembly device to fix the ground wire on the conductor, thereby completing the installation of the ground wire. When disassembling, the control unit drives the electric assembly and disassembly device to release the locking clamp and remove the ground wire;

[0052] S5: During the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, locking status and detection data of the drone 1 in real time, and uploads it to the blockchain network.

[0053] In this embodiment, the ground station initializes the drone 1 and the electric device, checks the battery power and sensor status, and starts the AI ​​visual recognition module and the data transmission module. After receiving the command, the drone 1 takes off vertically and flies to the target overhead line area along a preset path;

[0054] After UAV 1 arrives at the target area, the camera starts to collect images and video data of the wire, and the AI ​​visual recognition module pre-processes the image to optimize the clarity and remove noise;

[0055] The pre-processed image data is passed to the AI ​​visual recognition module, which uses the YOLO algorithm to analyze the shape, position and state of the wire. By analyzing the length, curvature and distance between adjacent wires, the module determines the most suitable hanging point for installing the ground wire.

[0056] After analyzing the wire shape, the AI ​​visual recognition module calculates the position of the optimal hanging point in the form of three-dimensional coordinates and connects with the path planning system of UAV 1.

[0057] In this embodiment, the steps of using the YOLO algorithm to analyze the shape, position and state of the wire are as follows:

[0058] YOLO divides the image into S×S grids, each of which predicts multiple bounding boxes and their confidences, expressed as Among them, P(C) is the probability that the grid contains a wire, represents the predicted bounding box of grid (i, j), x and y are the center coordinates of the bounding box, w and h are the width and height, p c is the confidence score, and then the non-maximum suppression algorithm is used to retain the bounding box with the highest confidence, which is expressed as: Among them, IoU(B i , B j ) represents two bounding boxes B i and B j The bounding box will be retained only when the intersection-and-union ratio is less than the threshold;

[0059] Based on the selected valid bounding box, the system further analyzes the curvature of the wire, which is expressed as y=a0+a1x+a2x 2 +…+a n xn, where a0, a1, ..., a n is the coefficient of the fitting polynomial, which is used to describe the curvature change of the conductor. Finally, the most suitable hanging point for installing the grounding wire is recommended at the key node of the conductor, and the hanging point coordinate expression is generated: (X 挂点 , Y 挂点 , Z 挂点 )=(x GPS ,y GPS ,h 挂点 ), where (X 挂点 , Y 挂点 , Z 挂点 ) is the recommended hanging point coordinate, (x GPS ,y GPS) is the GPS coordinate of the current position of UAV 1, h 挂点 is the height of the hanging point.

[0060] It should be noted that: the drone is equipped with an AI visual recognition module and uses the YOLO algorithm to analyze the shape, position and state of the wire, automatically detect the length, curvature and adjacent spacing of the wire, accurately identify and generate the coordinates of the hanging points most suitable for installing the grounding wire, and seamlessly connect with the path planning system to ensure that the drone can fly efficiently and accurately perform operations in complex environments; image preprocessing optimizes clarity and removes noise, ensuring the accuracy of the algorithm in various environments, reducing manual operation and the risk of misjudgment, which not only improves installation efficiency, but also greatly reduces operating costs and safety risks.

[0061] In this embodiment, after receiving these data, the path planning system starts the flight path calculation module to generate an initial flight path for the drone 1 and ensure that the path is aligned with the coordinates of the hanging point.

[0062] When UAV 1 is preparing to fly, the LiDAR and ultrasonic sensors start to synchronously collect data about the surrounding environment and detect potential obstacles in the flight path, such as trees, buildings, or power poles. The path planning system performs a preliminary analysis based on the sensor data to determine the distribution of obstacles on the path.

[0063] Based on the target hanging point coordinates identified by AI and the obstacle data collected by sensors, the path planning system uses the Dijkstra algorithm to calculate the optimal flight path. The algorithm dynamically selects the shortest path according to the node weights and optimizes it based on the initial path.

[0064] Drone 1 flies along the calculated optimal path and updates the environmental data in real time during the flight. LiDAR and ultrasonic sensors continuously detect new obstacles that may appear. Once an obstacle is found blocking the path, the system will instantly update the node weights and recalculate the alternative path using the Dijkstra algorithm.

[0065] After avoiding the obstacle, UAV 1 continues to fly to the hanging point, and calibrates the coordinates through the path planning system to ensure that UAV 1 is in the best staying position when it arrives above the hanging point. At this time, UAV 1 is ready to enter the installation stage, and the path planning and obstacle avoidance tasks are completed. This embodiment receives the hanging point coordinates identified by AI and the obstacle data collected by the sensor through the path planning system, and uses the Dijkstra algorithm to dynamically calculate the optimal flight path to ensure that the UAV flies accurately to the target position; during the flight, LiDAR and ultrasonic sensors monitor the environment in real time, and instantly update the node weights and path planning when obstacles are detected, avoiding flight interruptions and collision risks, and improving the safety and stability of the system; the combination of path planning and coordinate calibration ensures that the UAV stays accurately at the hanging point, providing efficient support for subsequent installation operations, while reducing the risk of manual intervention and flight errors.

[0066] In this embodiment, the path planning system of the drone 1 discretizes the flight area into several nodes and constructs a weighted directed graph G = (V, E), where V represents a node set, E represents a directed edge between nodes, and each edge e ij ∈E gives weight w ij , represents the flight cost between node i and node j. The weight is affected by distance, energy consumption and environmental conditions. Its expression is: w ij =d ij +α·C ij , where d ij is the distance between nodes i and j, C ij is the energy consumption cost, α is the energy consumption impact coefficient;

[0067] Next, the path planning system of UAV 1 takes the starting point s of UAV 1 as the initial node, uses the Dijkstra algorithm to gradually select the edge with the smallest weight, updates the minimum path from the starting point to other nodes, and defines D(v) as the shortest path weight from the starting point s to the node v. Initially, D(s) = 0, and the path weights of other nodes are set to ∞, and the expression is: Among them, u and v are two adjacent nodes, and the algorithm selects the edge with the smallest weight when updating the path;

[0068] Drone 1 takes off along the optimal path calculated by the Dijkstra algorithm and collects sensor data in real time. LiDAR and ultrasonic sensors monitor obstacles in the flight environment and upload the detected obstacle information to the path planning system. If there are no obstacles on the current path, the system maintains the original flight path.

[0069] When the sensor detects a new obstacle in the flight path, the system adds the weights w of the affected node and its neighboring nodes. ij Adjusted to a higher value to represent the high cost of flying in an obstacle area, the expression is:ij =w ij +β·O ij , where O ij represents the obstacle influence coefficient between nodes i and j, and β is the obstacle influence weight. By discretizing the flight area into several nodes and constructing a weighted directed graph, the Dijkstra algorithm is used to dynamically calculate the optimal flight path of the drone, effectively balancing the impact of flight distance, energy consumption and environmental conditions on path selection; during the flight, LiDAR and ultrasonic sensors monitor obstacles in real time and feed back detection data to the path planning system. When new obstacles appear, the system can instantly adjust the node weights and replan the path to ensure the safe flight of the drone in a complex environment; this path planning method not only improves flight accuracy and stability, but also improves the system's adaptability and emergency handling capabilities, providing intelligent support for drone mission execution.

[0070] In this embodiment, when an obstacle makes a path infeasible, the system runs the Dijkstra algorithm again according to the updated node weights, and recalculates an alternative path from the current position of UAV 1 to the target position. The new path also ensures the minimum weight and avoids the obstacle area. Once the alternative path calculation is completed, the system immediately calibrates the flight direction of UAV 1 so that it continues to fly along the new path. UAV 1 dynamically adjusts the flight altitude and direction to ensure safe flight to the target position in a complex environment. After UAV 1 arrives at the target position smoothly according to the planned path, the system records the flight path and obstacle avoidance data, and uploads it to the ground station for confirmation and archiving. At this time, the path planning task is completed, and preparations are made for the installation or removal of the ground wire.

[0071] In this embodiment, the electric assembly and disassembly device includes a hook 2, a motor 6, and a box 3. The lower end of the hook 2 is fixed on the box 3. A through hole is opened on one side of the hook 2. The bottom of the inner wall of the box 3 is fixedly connected to the motor 6. The output end of the motor 6 is fixedly connected to a rotating screw 4 passing through the box 3 through the through hole. The rotating screw 4 is threadedly connected with a movable buckle ring 5. The movable buckle ring 5 is arranged opposite to the opening of the hook 2. The side wall of the movable buckle ring 5 is tightly fitted on the side wall of the hook 2. The movable buckle ring 5 and the hook 2 form the locking clamp. The assembly and disassembly device of this application adopts the patent document with publication number CN116014524A in the prior art.

[0072] In this embodiment, during installation, the grounding wire is passed through the double holes at the lower end of the hook, and the grounding wire is ensured to be firmly fixed in the locking clamp. The screw is rotated to adjust the opening between the movable buckle ring and the hook, and the grounding wire is completely locked in the clamp to prepare for hanging. After the drone 1 has adjusted its position, the control unit drives the electric device to rotate the screw to open the movable buckle ring. After the hook is tightly buckled on the wire, the system rotates the screw again, and the movable buckle ring and the hook are closed again, so that the box is firmly hung on the wire. After the installation is completed, the drone 1 detaches from the box and returns to the ground, completing the installation task of the grounding wire. The drone 1 uploads the installation data to the ground station in real time and enters a standby state to prepare for the next task.

[0073] When disassembling, start the drone 1 to fly to the disassembly point, and then reconnect with the box. The drone 1 takes off and flies to the target hanging point to prepare for the disassembly of the ground wire. After the drone 1 arrives at the hanging point, the electric opening and closing device is started through the control system, and the screw is rotated to adjust the movable buckle ring so that the buckle ring is gradually loosened and separated from the hook. The ground wire is released from the lock-type clamp and is ready for recovery. After the movable buckle ring is fully opened, the ground wire is separated from the wire, and the drone 1 removes the box from the wire through the hook. Finally, the drone 1 flies back to the ground station with the box and the disassembled ground wire to complete the disassembly task. The system synchronously uploads the disassembly data for review and record. This application uses a finger cylinder when clamping the box, and its control is wirelessly controlled by the ground station. In this embodiment, the drone carries an electric assembly and disassembly device to realize the intelligent installation and disassembly of the ground wire, and uses a rotating screw to adjust the opening and closing of the movable buckle ring and the hook to ensure that the ground wire is firmly suspended on the wire, thereby improving the accuracy and reliability of the installation; during the installation and disassembly process, the system is remotely operated by the control unit without manual intervention, reducing the risk of high-altitude operations. When disassembling, the drone reconnects the box and uses an electric device to release the ground wire. After the disassembly is completed, it automatically returns to the ground and uploads the mission data in real time to ensure transparency and traceability of the operation. This design reduces operation time and labor costs, while improving safety and efficiency in complex environments.

[0074] In this embodiment, during the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, locking status and detection data of the drone 1 in real time, and uploads it to the blockchain network in the following steps:

[0075] Before the drone 1 takes off, the blockchain operation recording module is started synchronously with the flight control system and establishes a secure connection with the blockchain network. After the drone 1 takes off, the module continuously collects GPS coordinates and flight path data, and uploads them to the blockchain network at fixed time intervals. Then, when the grounding wire is installed at the hanging point, the module records the start and end time of the installation, as well as the state change of the locking clamp. When performing the disassembly task, the module synchronously records the disassembly time and equipment operation status. After completing the flight, installation and disassembly tasks, all data are packaged into blocks and uploaded to the blockchain network. This embodiment realizes transparent data management of the entire process of flight path, installation and disassembly through the synchronous start of the blockchain operation recording module and the flight control system. The drone collects GPS coordinates and equipment status in real time during the task execution, and uploads key data to the blockchain network at fixed time intervals to ensure that the data cannot be tampered with and is traceable. During the installation and disassembly of the grounding wire, the system accurately records the time and state changes of each step, and packages and uploads all data after the task is completed to achieve remote review and archiving. This design improves the transparency of the operation and the reliability of the operation, provides a complete data management support for the power company, and improves the safety and efficiency of task execution.

[0076] The present invention is not limited to the above-mentioned embodiments. Anyone should be aware that any structural changes made under the enlightenment of the present invention, and any technical solutions that are the same or similar to the present invention, fall within the protection scope of the present invention. The technology, shape, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A method for installing and removing an assembled grounding wire for a high-voltage overhead line, which uses a ground station, an unmanned aerial vehicle (1) and an electric assembly and disassembly device to achieve the installation and removal of the grounding wire, characterized in that: The following steps are involved: S1: The drone (1) carries the electric assembly and disassembly device through the finger cylinder, activates the camera, LiDAR and ultrasonic sensor, and enables the AI ​​visual recognition module and path planning system; S2: The drone (1) takes off and flies to the target overhead line area, uses the AI ​​visual recognition module to collect wire data through the camera, identifies the wire shape and locates the ground wire hanging point, and then feeds the detection results back to the ground station; S3: Based on AI recognition results, the path planning system combines data from LiDAR and ultrasonic sensors, uses the Dijkstra algorithm to calculate the flight path, and dynamically avoids obstacles during flight; S4: After the drone (1) arrives at the target location, the control unit drives the rotating screw and the movable buckle ring in the electric assembly and disassembly device to fix the ground wire on the conductor, thereby completing the installation of the ground wire. When disassembling, the control unit drives the electric assembly and disassembly device to release the locking clamp to remove the ground wire; S5: During the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, locking status and detection data of the drone (1) in real time and uploads it to the blockchain network.

2. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 1, characterized in that: The drone (1) takes off and flies to the target overhead line area, uses the AI ​​visual recognition module to collect wire data through the camera, identifies the wire shape and locates the ground wire hanging point, and then feeds the detection results back to the ground station in the following steps: The ground station initializes the drone (1) and the electric device, checks the battery power and sensor status, and starts the AI ​​visual recognition module and the data transmission module. After receiving the command, the drone (1) takes off vertically and flies to the target overhead line area along a preset path; After the drone (1) arrives at the target area, the camera starts to collect images and video data of the wire, and the AI ​​visual recognition module pre-processes the image to optimize the clarity and remove noise; The pre-processed image data is passed to the AI ​​visual recognition module, which uses the YOLO algorithm to analyze the shape, position and state of the wire. By analyzing the length, curvature and distance between adjacent wires, the module determines the most suitable hanging point for installing the ground wire. After analyzing the wire shape, the AI ​​visual recognition module calculates the location of the optimal hanging point in the form of three-dimensional coordinates and connects with the path planning system of the drone (1).

3. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 2, characterized in that: The steps to use the YOLO algorithm to analyze the shape, position and status of the wire are as follows: YOLO divides the image into S×S grids, each of which predicts multiple bounding boxes and their confidences, expressed as Among them, P(C) is the probability that the grid contains a wire, represents the predicted bounding box of grid (i, j), x and y are the center coordinates of the bounding box, w and h are the width and height, p c is the confidence score, and then the non-maximum suppression algorithm is used to retain the bounding box with the highest confidence, which is expressed as: Among them, IoU(B i , B j ) represents two bounding boxes B i and B j When the intersection-and-union ratio is less than the threshold, the bounding box will be retained; Based on the selected valid bounding box, the system further analyzes the curvature of the wire, which is expressed as y=a0+a1x+a2x 2 +…+a n x n , where a0, a1, ..., a n is the coefficient of the fitting polynomial, which is used to describe the curvature change of the conductor. Finally, it is recommended to install the hanging point of the grounding wire at the key node of the conductor, and generate the hanging point coordinate expression: (X 挂点 , Y 挂点 , Z 挂点 )=(x GPS ,y GPS ,h 挂点 ), where (X 挂点 , Y 挂点 , Z 挂点 ) is the recommended hanging point coordinate, (x GPS ,y GPS ) is the GPS coordinate of the current position of the drone (1), h 挂点 is the height of the hanging point.

4. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 3, characterized in that: Based on the AI ​​recognition results, the path planning system combines the data from LiDAR and ultrasonic sensors, uses the Dijkstra algorithm to calculate the flight path, and dynamically avoids obstacles during flight in the following steps: After receiving these data, the path planning system starts the flight path calculation module to generate an initial flight path for the UAV (1) and ensure that the path is aligned with the coordinates of the hanging point; When the drone (1) is preparing to fly, the LiDAR and ultrasonic sensors begin to synchronously collect data about the surrounding environment and detect potential obstacles in the flight path. The path planning system performs a preliminary analysis based on the sensor data to determine the distribution of obstacles on the path. Based on the target hanging point coordinates identified by AI and the obstacle data collected by sensors, the path planning system uses the Dijkstra algorithm to calculate the optimal flight path. The algorithm dynamically selects the shortest path according to the node weights and optimizes it based on the initial path. The drone (1) flies along the calculated optimal path and updates the environmental data in real time during the flight. The LiDAR and ultrasonic sensors continuously detect new obstacles. Once an obstacle is found blocking the path, the system will immediately update the node weights and recalculate the alternative path using the Dijkstra algorithm. After avoiding the obstacle, the UAV (1) continues to fly to the hanging point and performs coordinate calibration through the path planning system to ensure that the UAV (1) is in the best staying position when it arrives above the hanging point. At this time, the UAV (1) is ready to enter the installation phase, and the path planning and obstacle avoidance tasks are completed.

5. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 4, characterized in that: The path planning system uses the Dijkstra algorithm to calculate the optimal flight path. The algorithm dynamically selects the shortest path based on the node weights as follows: The UAV (1) path planning system discretizes the flight area into several nodes and constructs a weighted directed graph G = (V, E), where V represents the node set, E represents the directed edges between the nodes, and each edge e ij ∈E gives weight w ij , represents the flight cost between node i and node j. The weight is affected by distance, energy consumption and environmental conditions. Its expression is: w ij =d ij +α·C ij , where d ij is the distance between nodes i and j, C ij is the energy consumption cost, α is the energy consumption impact coefficient; Next, the UAV (1) path planning system takes the starting point s of the UAV (1) as the initial node, uses the Dijkstra algorithm to gradually select the edge with the smallest weight, updates the minimum path from the starting point to other nodes, and defines D(υ) as the shortest path weight from the starting point s to the node υ. Initially, D(s) = 0, and the path weights of other nodes are set to ∞. The expression is: Among them, u and υ are two adjacent nodes; The drone (1) takes off along the optimal path calculated by the Dijkstra algorithm and collects sensor data in real time. The LiDAR and ultrasonic sensors monitor obstacles in the flight environment and upload the detected obstacle information to the path planning system. If the current path is obstacle-free, the system maintains the original flight path.

6. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 5, characterized in that: Once an obstacle is found blocking the path, the system will immediately update the node weights and use the Dijkstra algorithm to recalculate the alternative path as follows: When the sensor detects a new obstacle in the flight path, the system adds the weights w of the affected node and its neighboring nodes. ij Adjusted to a higher value to represent the high cost of flying in an obstacle area, the expression is: ij =w ij +β·O ij , where O ij represents the obstacle influence coefficient between nodes i and J, β is the obstacle influence weight; When an obstacle makes the path infeasible, the system runs the Dijkstra algorithm again based on the updated node weights to recalculate an alternative path from the current position of the drone (1) to the target position. The new path also ensures the minimum weight and avoids the obstacle area. Once the alternative path calculation is completed, the system immediately calibrates the flight direction of the drone (1) so that it continues to fly along the new path. The drone (1) dynamically adjusts the flight altitude and direction to ensure safe flight to the target position in a complex environment. After the drone (1) successfully arrives at the target position according to the planned path, the system records the flight path and obstacle avoidance data and uploads it to the ground station for confirmation and archiving. At this time, the path planning task is completed and preparations are made for the installation or removal of the ground wire.

7. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 6, characterized in that: The electric assembly and disassembly device comprises a hook (2), a motor (6), and a box (3). The lower end of the hook (2) is fixed on the box (3). A through hole is opened on one side of the hook (2). The bottom of the inner wall of the box (3) is fixedly connected to the motor (6). The output end of the motor (6) is fixedly connected to a rotating screw (4) passing through the box (3) through the through hole. A movable buckle ring (5) is threadedly connected to the rotating screw (4). The movable buckle ring (5) is arranged opposite to the opening of the hook (2). The side wall of the movable buckle ring (5) is tightly fitted on the side wall of the hook (2). The movable buckle ring (5) and the hook (2) form the locking clamp.

8. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 7, characterized in that: After the drone (1) reaches the target position, the control unit drives the rotating screw (4) and the movable buckle ring (5) in the electric assembly and disassembly device to fix the ground wire on the conductor, thereby completing the installation of the ground wire. When disassembling, the control unit drives the electric assembly and disassembly device to release the locking clamp. The steps for disassembling the ground wire are as follows: During installation, the grounding wire is passed through the double holes at the lower end of the hook (2), and the grounding wire is ensured to be firmly fixed in the locking clamp. The screw rod (4) is rotated to adjust the opening between the movable buckle ring (5) and the hook (2), and the grounding wire is completely locked in the clamp to prepare for hanging. After the drone (1) has adjusted its position, the control unit drives the electric device to rotate the screw rod (4) to open the movable buckle ring (5). After the hook (2) is tightly buckled on the wire, the system rotates the screw rod (4) again, and the movable buckle ring (5) and the hook (2) are closed again, so that the box (3) is firmly hung on the wire. After the installation is completed, the drone (1) is separated from the box (3) and returns to the ground, completing the installation task of the grounding wire. The drone (1) uploads the installation data to the ground station in real time and enters a standby state to prepare for the next task. During disassembly, the drone (1) is started to fly to the disassembly point, and then reconnected with the box (3). The drone (1) takes off and flies to the target hanging point to prepare for the disassembly of the grounding wire. After the drone (1) arrives at the hanging point, the electric opening and closing device is started through the control system, and the screw (4) is rotated to adjust the movable buckle ring (5), so that the buckle ring is gradually loosened and separated from the hook (2), and the grounding wire is released from the locking clamp and is ready for recovery. After the movable buckle ring (5) is fully opened, the grounding wire is separated from the wire, and the drone (1) removes the box (3) from the wire through the hook (2). Finally, the drone (1) carries the box (3) and the disassembled grounding wire back to the ground station to complete the disassembly task. The system simultaneously uploads the disassembly data for review and record.

9. A method for installing and removing an assembled grounding wire for a high-voltage overhead line according to claim 1, characterized in that: During the installation, disassembly and flight process, the blockchain operation recording module records the flight path, installation time, locking status and detection data of the drone (1) in real time, and uploads it to the blockchain network in the following steps: Before the drone (1) takes off, the blockchain operation recording module is started synchronously with the flight control system and establishes a secure connection with the blockchain network. After the drone (1) takes off, the module continuously collects GPS coordinates and flight path data, and uploads them to the blockchain network at fixed time intervals. Then, when the ground wire is installed at the hanging point, the module records the start and end time of the installation, as well as the state change of the locking clamp. When performing a disassembly task, the module synchronously records the disassembly time and the equipment operation status. After completing the flight, installation and disassembly tasks, all data are packaged into blocks and uploaded to the blockchain network.

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