A method and device for take-off and landing control of a power line inspection drone

Abstract

This invention discloses a take-off and landing control method and device for a power line inspection drone, belonging to the field of power line inspection technology. This invention achieves comprehensive coverage of power inspection points by automating the drone's power inspection tasks, avoiding omissions and errors inherent in manual inspections. The drone can autonomously plan its path based on real-time data and acquire inspection data using high-precision sensors, improving the efficiency and accuracy of power equipment monitoring and fault diagnosis. Employing a Vivaldi antenna as a communication method effectively addresses electromagnetic interference in the power line inspection environment, ensuring stable communication signals even in complex conditions. By acquiring and analyzing images in real-time through a camera unit, the patrol drone can quickly identify equipment anomalies and guide the responding drone to the fault location for continuous monitoring via electronic pheromones, enabling timely fault handling and reducing power outage time and maintenance costs.

Description

Technical Field

[0001] This invention relates to a take-off and landing control method and device for a power line inspection drone, belonging to the field of power line inspection technology. Background Technology

[0002] Currently, power line inspection work typically relies on manual inspection and traditional testing equipment. This is especially true in complex environments such as high-voltage power lines and substations, where traditional inspection methods face significant challenges. First, manual inspection not only poses safety risks but is also inefficient, unable to monitor every detail in real time, hindering dynamic monitoring and fault early warning of power facilities. Second, existing power line inspection equipment generally suffers from strong electromagnetic interference. The electromagnetic environment around power facilities such as substations is highly complex, and existing equipment exhibits poor stability in this environment, often leading to signal interruptions or interference, thus affecting inspection quality and efficiency. Third, during drone inspections, electromagnetic interference can easily cause abnormal positioning data, potentially leading to collisions with power equipment and significant damage.

[0003] To address the aforementioned issues, Chinese Patent No. CN113554775A discloses a drone-based power line inspection system. Its key technical features include: data transmission via a communication module between a cloud server and the drone; the cloud server receiving inspection task information and planning the drone's flight path based on task priority; and generating flight commands based on environmental data to optimize inspection efficiency. Furthermore, the system utilizes the Dubins path planning algorithm to achieve optimal flight path planning and supports merging multiple drone mission flight paths, thereby improving work efficiency.

[0004] The above solution addresses the issues of UAV mission planning and route optimization, improving inspection efficiency and saving flight time in multi-mission scenarios. However, because the system relies on cloud servers for mission scheduling and path planning, it suffers from high latency. This is particularly problematic during power grid inspections, where the cloud server's computational burden is heavy, potentially affecting the system's real-time performance. Furthermore, while information sharing has been improved, it remains limited by the cloud server's communication network and electromagnetic interference from the power system, potentially leading to interruptions in remote control and data transmission.

[0005] Therefore, a new solution is needed to address this problem. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a take-off and landing control method and device for a power inspection drone, including a take-off and landing control method and a take-off and landing control device for a power inspection drone, which solves the problem of interruption of remote control and data transmission in the prior art.

[0007] In a first aspect, the present invention provides a take-off and landing control method for a power line inspection drone, comprising the following steps:

[0008] Step S100: Deployment of UAVs and identification of power inspection points;

[0009] By capturing response signals generated by RFID radio frequency identification chips using the Vivaldi antenna of a drone, power inspection points are identified, and a discrete swarm of inspection drones is generated around these points. The location coordinates of relay drones are determined based on the location information of the inspection drone swarm. The discrete inspection drone swarm is then connected in series using relay drones to form a drone-based power inspection network.

[0010] The command drone transmits radio frequency signals at a preset frequency via its onboard Vivaldi antenna while flying along a preset path, and captures the response signals of the RFID radio frequency identification chips at each power inspection point in real time.

[0011] After capturing the response signal of the radio frequency signal, the response signal is decoded to obtain the serial number, location coordinates, and geometric information of the power inspection point where the radio frequency identification chip is located.

[0012] The location coordinates of each power inspection point are determined based on the RFID signals received by the drone, and then a swarm of inspection drones is deployed within a preset range near each power inspection point.

[0013] The various inspection drone groups share a common flight altitude, which is specifically the altitude classification in the RFID chip position coordinates corresponding to the inspection drone group number i plus a preset safe flight altitude.

[0014] In a preferred embodiment of the present invention, the position coordinates of relay drones between the various inspection drone groups are determined based on the location information of the inspection drone groups. The discrete inspection drone groups are then connected in series using relay drones to obtain a drone power line inspection network. The placement and number of relay drones between adjacent inspection drone groups are obtained through quality assessment and distance assessment. The specific process is as follows:

[0015] Obtain any two adjacent inspection drone swarms and their corresponding location coordinates, and calculate the center distance between the two adjacent inspection drone swarms. Determine the number of relay drones between the two adjacent inspection drone swarms based on the center distance.

[0016] In a preferred embodiment of the present invention, the position of each relay drone is determined based on the center distance between two adjacent inspection drone groups and the number of relay drones. The position coordinates of each relay drone are obtained by differential calculation, so that each relay drone is evenly distributed along the line connecting the inspection drone groups.

[0017] Step S200, UAV relay gain;

[0018] Based on the Vivaldi antenna in the relay drone, resistance loading and choke slot loading are performed to improve signal gain and frequency response in the low-frequency band, providing communication signals and GPS reference positioning for drone take-off and landing control for the entire drone power inspection network.

[0019] As a preferred embodiment of the present invention, by applying a preset resistance to the end of the slot of the Vivaldi antenna arranged on the relay UAV, the low-frequency response region of the Vivaldi antenna is extended to cope with electromagnetic interference in the substation environment and optimize the transmission quality of communication signals and GPS positioning signals.

[0020] As a preferred embodiment of the present invention, high-frequency noise is suppressed by choke slot loading, edge effects are limited, and energy is concentrated in the slot line region, thereby improving low-frequency gain.

[0021] Step S300: Drone grouping and safe altitude planning;

[0022] The inspection drone swarm is divided into patrol drones and response drones. A long-term monitoring motion model of the patrol drones is obtained using 3D models of each power inspection point. The motion model of the patrol drones is used to limit their altitude and prevent collisions caused by drones getting too close to the power inspection points.

[0023] The initial grouping process involves dividing the various inspection drone groups into patrol drones and response drones according to a preset ratio, and establishing a motion model for the patrol drones. The specific process is as follows:

[0024] Each inspection drone swarm obtains its own position coordinates in the world coordinate system through relay drones. Using the position coordinates of each RFID chip as the origin, a three-dimensional sub-coordinate system of the inspection point in the world coordinate system is established. The three-dimensional sub-coordinate system of the inspection point is then rasterized and divided into multiple cubic blocks of preset size.

[0025] Obtain the geometric shape information of the power inspection points corresponding to each RFID chip, including the geometric center coordinates of each power inspection point, the maximum radius from the geometric center to the edge, the minimum radius, the maximum height zmax, and the maximum surface tilt angle.

[0026] The patrol drone is treated as a point mass moving in a straight line between the corners of a gridded cube in three-dimensional space. Ignoring its turning angle and climb angle, a motion model of the images taken by a single patrol drone around a single power inspection point is established based on the geometric information of the power inspection point. The flight altitude of each patrol drone at each location is controlled to prevent the patrol drone from colliding with the power inspection point.

[0027] Step S400: Drone patrol and continuous monitoring;

[0028] Patrol drones collect image information from power line inspection points, identify anomalies based on changes in the image information, and generate electronic pheromones. These electronic pheromones then guide response drones for long-term monitoring.

[0029] Each patrol drone is commanded to fly around the power inspection point according to the trajectory information contained in the patrol drone's motion model, and to collect image information of the power inspection point in real time. When a patrol drone detects a change in the image information of the power inspection point, it records the coordinates of the patrol drone's location and generates an electronic pheromone at that coordinate. The electronic pheromone is specifically a position coordinate signal whose intensity decays over time, and attracts responding drones to continuously monitor the coordinates based on the intensity.

[0030] As a preferred embodiment of the present invention, the attraction index is used to determine whether the responding drone is attracted by the electronic pheromone. Whenever a patrol drone generates an electronic pheromone, the distance between the responding drones in the patrol drone group and the corresponding coordinates of the electronic pheromone is immediately obtained, and the attraction index is calculated by substituting the distance between the responding drones and the electronic pheromone in the formula for the intensity attenuation of the electronic pheromone.

[0031] In a preferred embodiment of the present invention, the attraction index is directly proportional to the pheromone intensity, directly proportional to the distance between the responding drone and the coordinates of the electronic pheromone, and inversely proportional to the number of responding drones already attracted by the electronic pheromone. If the attraction index of a responding drone is detected to be greater than a preset maximum attraction threshold, it is determined that the responding drone is attracted by the electronic pheromone. The responding drone is then directed to the coordinates of the electronic pheromone's location, continuously acquiring image information of the power line inspection point at those coordinates, and incrementing the count of responding drones already attracted by the electronic pheromone by one. Simultaneously, the pheromone intensity is allowed to decay over time until it reaches zero.

[0032] As a preferred embodiment of the present invention, a take-off and landing control device for a power line inspection drone includes a ground communication base station and a drone swarm.

[0033] Among them, ground communication base stations provide reference coordinates and wireless communication relays for UAVs.

[0034] The drone swarm includes relay drones and inspection drones, with each relay drone equipped with a Vivaldi antenna. The inspection drone swarm includes patrol drones and response drones, both of which are equipped with Vivaldi antennas, inertial measurement units (IMUs), lidar units, and camera units.

[0035] The Vivaldi antenna provides stable communication signals and data transmission for the drones, and uses its wide bandwidth and high gain to capture and transmit RFID signals, enabling the inspection drones to receive RFID response signals from power inspection points in real time, thereby determining the location and relevant information of the inspection points. Furthermore, the Vivaldi antenna acts as a wireless communication relay during power inspections, maintaining communication links between different drone swarms.

[0036] The IMU (Inertial Measurement Unit) in a drone is responsible for providing accurate flight attitude and position data, and for calculating the drone's location, three-dimensional attitude, and trajectory information in real time.

[0037] The lidar unit scans the surrounding environment with a laser beam and receives reflected signals to generate high-resolution three-dimensional point cloud data, helping drones perceive the precise location of surrounding obstacles and power facilities.

[0038] The camera unit is responsible for collecting images and video information during power line inspections, monitoring the status of power facilities in real time, and helping maintenance personnel to detect potential faults or anomalies. Furthermore, during the coordination between patrol drones and response drones, the camera unit generates electronic pheromones containing location coordinate information based on changes in image information, guiding the response drones to conduct continuous monitoring.

[0039] The beneficial effects of this invention are as follows: By entrusting inspection tasks to automated drones, this invention achieves comprehensive coverage of power inspection points. The drones can autonomously plan their paths and automatically adjust their positions based on real-time data, avoiding omissions and errors that may occur during manual inspections. Real-time acquisition of inspection data ensures more efficient and accurate monitoring and troubleshooting of power equipment. This invention uses a Vivaldi antenna as the primary communication method, effectively addressing electromagnetic interference in the power inspection environment. The wide bandwidth and high gain characteristics of the Vivaldi antenna ensure stable communication signals even in complex electromagnetic environments. Through image information acquired by the camera unit and real-time data analysis, the patrol drone can quickly identify abnormalities in power equipment and guide the responding drone to the fault location for further monitoring and processing via electronic pheromones. This allows for timely handling of power facility failures, reducing power outage time and maintenance costs. Attached Figure Description

[0040] Figure 1 This is a flowchart of a method for controlling the take-off and landing of a power line inspection drone as proposed in an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of the UAV power line inspection network proposed in the embodiments of the present invention;

[0042] Figure 3 This is a schematic diagram of the Vivaldi antenna proposed in the embodiments of the present invention;

[0043] Figure 4 This is a system block diagram of a take-off and landing control device for a power line inspection drone proposed in an embodiment of the present invention. Detailed Implementation

[0044] To facilitate a clear understanding of the technical means, creative features, objectives, and effects of this invention, the invention will be further described below in conjunction with specific illustrations.

[0045] like Figure 1 As shown, a take-off and landing control method for a power line inspection drone includes the following steps:

[0046] Step S100: Deployment of UAVs and identification of power inspection points;

[0047] By capturing response signals from RFID chips deployed at various power line inspection points using the Vivaldi antenna of a drone, a discrete swarm of inspection drones is generated around each inspection point. The hovering height of the inspection drone swarm is limited by the position coordinates contained in the RFID chips. The position coordinates of relay drones between the inspection drone swarms are determined based on the position information of the inspection drone swarms. The discrete inspection drone swarms are then connected in series using relay drones to form a drone power line inspection network.

[0048] The command drone transmits radio frequency signals at a preset frequency via its onboard Vivaldi antenna while flying along a preset path, and captures the response signals of the RFID radio frequency identification chips at each power inspection point in real time.

[0049] After capturing the response signal of the radio frequency signal, the response signal is decoded to obtain the serial number i of the radio frequency identification chip, the location coordinates (xi, yi, zi), and the geometric information of the power inspection point where the radio frequency identification chip is located.

[0050] Where i = 1, 2, ..., n; n is the total number of power inspection points.

[0051] The location coordinates of each power inspection point are determined based on the RFID signals received by the drones. A swarm of inspection drones is then deployed within a predetermined range near each power inspection point. The identifier for each inspection drone swarm is set to match the identifier of the power inspection point; that is, the identifier for the inspection drone swarm is i, where i = 1, 2, ..., n.

[0052] The various inspection drone groups i share a common flight altitude, which is specifically the altitude classification zi in the RFID chip position coordinates corresponding to the inspection drone group number i plus a preset safe flight altitude H0.

[0053] It should be noted that the effective working distance of RFID technology is typically short, usually requiring a distance of several meters to tens of meters to read a tag. Therefore, by capturing the response signal of the RFID radio frequency identification chip, the approximate location range of the power inspection point can be automatically identified.

[0054] like Figure 2 As shown, the position coordinates of relay drones between inspection drone groups are determined based on their location information. The discrete inspection drone groups are then connected in series using relay drones to form a drone power line inspection network. The placement and number of relay drones between adjacent inspection drone groups are obtained through quality and distance assessments. The specific process is as follows:

[0055] Obtain the position coordinates of any two adjacent inspection drone swarms i and i+1. and Calculate the center distance between the two adjacent inspection drone swarms i and i+1: By using a preset formula: Determine the number of relay drones between the two adjacent inspection drone groups i and i+1. .in This is the maximum communication range that a single relay drone can effectively support, where... Represents center distance With maximum communication range The quotient is rounded up.

[0056] In a preferred embodiment of the present invention, the position of each relay drone is determined based on the center distance between the two adjacent inspection drone groups i and i+1 and the number of relay drones. The position coordinates of each relay drone are obtained by differential calculation, and the relay drones are evenly distributed along the line connecting inspection drone groups i and i+1.

[0057] Specifically, the coordinates of the k-th relay drone between the two adjacent inspection drone groups i and i+1. for: Where k is the sequential number of the relay UAV, k=1,2,... .

[0058] It should be noted that the electromagnetic interference in substation environments is extremely strong, which typically leads to a decrease in communication quality between drones, thereby affecting data transmission between all inspection drone swarms. Furthermore, strong electromagnetic fields can affect the GPS positioning signals of drone electronic equipment, impacting the stability of the flight control system. Therefore, relay drones are needed to provide signal relay base stations between various inspection drone swarms to reduce electromagnetic interference.

[0059] Step S200, UAV relay gain;

[0060] Based on the Vivaldi antenna in the relay drone, resistance loading and choke slot loading are performed to improve signal gain and frequency response in the low-frequency band, providing communication signals and GPS reference positioning for drone take-off and landing control for the entire drone power inspection network.

[0061] like Figure 3 As shown, the Vivaldi antenna is an end-fire traveling-wave antenna with an exponentially tapered slot. Its design is based on the scaling principle and the traveling-wave antenna principle. The Vivaldi antenna consists of three parts: a feed structure, a dielectric substrate, and a radiating arm. During operation, electromagnetic energy is transferred through the impedance-matching coupling topology of the microstrip-slot line conversion structure. The feed structure comprises a fan-shaped microstrip stub and a circular resonant cavity. When energy is injected into the microstrip feed line, it is guided into the slot line transmission channel through electromagnetic coupling. The energy exhibits bidirectional transmission characteristics within the slot line: the main energy flow propagates along the exponentially tapered slot line, while the secondary energy flow propagates in the opposite direction to the short-circuit terminal, where it is reflected back into the main transmission path by the electromagnetic reflection of the circular resonant cavity. The Vivaldi antenna's design is based on the scaling principle and the traveling-wave antenna principle. Its structure allows electromagnetic waves to propagate along the antenna's slot line in a tapered manner, thus achieving a response to different frequencies. The Vivaldi antenna achieves broadband transmission through a tapered slot line structure, enabling it to cover a wide range of operating frequencies. The Vivaldi antenna comprises a feed structure, a dielectric substrate, radiating arms, slotted wires, short-circuit terminals, and a circular resonant cavity. Applying different resistance values ​​to the slotted wire portion of the Vivaldi antenna creates different frequency response curves. This allows the Vivaldi antenna to enhance signal transmission capabilities within specific frequency bands, helping relay drones effectively transmit data and location information.

[0062] By applying a pre-defined loading resistor to the end of the slot of the Vivaldi antenna deployed on the relay drone, the low-frequency response region of the Vivaldi antenna is extended to cope with electromagnetic interference in the substation environment and optimize the transmission quality of communication signals and GPS positioning signals.

[0063] As a preferred embodiment of the present invention, high-frequency noise is suppressed by choke slot loading, edge effects are limited, and energy is concentrated in the slot line region, thereby improving low-frequency gain.

[0064] The total antenna gain after being loaded by the choke slot is: in The total antenna gain is where This represents the original Vivaldi antenna gain. For gain applied to the resistor, To load the gain of the choke slot, where For communication frequency, The center frequency of the frequency band is where The scope of bandwidth expansion.

[0065] It should be noted that resistive loading and choke loading techniques improve low-frequency gain and signal transmission quality by altering the impedance matching and frequency response characteristics of the Vivaldi antenna. Specifically, resistive loading effectively extends the low-frequency bandwidth, while choke loading creates a capacitive load in the current path, optimizing the electromagnetic wave radiation pattern.

[0066] Step S300: Drone grouping and safe altitude planning;

[0067] The inspection drone swarm is divided into patrol drones and response drones. A long-term monitoring motion model of the patrol drones is obtained using 3D models of each power inspection point. The motion model of the patrol drones is used to limit their altitude and prevent collisions caused by drones getting too close to the power inspection points.

[0068] The initial grouping is performed by dividing each inspection drone group i into patrol drones and response drones in a 1:1 ratio, and establishing the motion model of the patrol drones. The specific process is as follows:

[0069] Each inspection drone swarm obtains its own position coordinates in the world coordinate system through relay drones. Taking the position coordinates (xi, yi, zi) of each RFID chip as the origin, a three-dimensional sub-coordinate system of the inspection point in the world coordinate system is established. The three-dimensional sub-coordinate system of the inspection point is rasterized and divided into multiple AxAxA cubic blocks, where A is a preset subdivision factor.

[0070] Obtain the geometric shape information of the power inspection points corresponding to each RFID chip, including the geometric center coordinates (x0, y0, z0) of each power inspection point, the maximum radius rmax from the geometric center to the edge, the minimum radius rmin, the maximum height zmax, and the maximum surface tilt angle umax.

[0071] Treating the patrol drone as a point mass moving in a straight line between the corners of a gridded cube in three-dimensional space, ignoring its turning and climbing angles, a motion model is established for a single patrol drone capturing images around a single power inspection point: Control the flight altitude z(x,y) of each patrol drone at each position (x,y) to prevent the patrol drone from colliding with the power inspection point, where x and y are the x-axis and y-axis components of the position coordinates of the patrol drone, and a, b and c are preset constant coefficients.

[0072] The constraints of the motion model of the patrol drone are: The maximum height of equipment at ZMAX power inspection points; d is the ground elevation of the location of the power inspection point; d is the preset safety distance.

[0073] Step S400: Drone patrol and continuous monitoring;

[0074] Patrol drones collect image information from power line inspection points, identify anomalies based on changes in the image information, and generate electronic pheromones. These electronic pheromones then guide response drones for long-term monitoring.

[0075] Each patrol drone is commanded to fly around the power inspection point according to the trajectory information contained in the patrol drone's motion model, and to collect image information of the power inspection point in real time. When a patrol drone detects a change in the image information of the power inspection point, it records the coordinates of the patrol drone's location and generates an electronic pheromone at that coordinate. The electronic pheromone is specifically a position coordinate signal whose intensity decays over time, and attracts responding drones to continuously monitor the coordinates based on the intensity.

[0076] The formula for the intensity decay of electron pheromones is: in The attraction index represents the willingness to respond to drones being attracted by electronic pheromones, among which For pheromone intensity, represents the distance between the responding drone and the coordinates of the electronic pheromone, and m is the number of responding drones already attracted by the electronic pheromone. The preset initial intensity of the electron pheromone. t is the preset decay coefficient of the electron pheromone, and t is time.

[0077] Whenever an inspection drone generates an electronic pheromone, the distance between all responding drones in the patrol drone swarm and the coordinates corresponding to the electronic pheromone is immediately obtained. Substituting the values ​​into the formula for the intensity decay of electron pheromones, the attraction index is calculated. When the attractiveness index of the responding drone is identified Greater than the preset maximum attraction threshold If the pheromone attracts the responding drone, it is determined that the drone is attracted to the pheromone. The drone then moves to the coordinates of the pheromone's location and continuously acquires image information of the power line inspection point at those coordinates. Simultaneously, the number of responding drones (m) attracted by the pheromone is incremented by one. At the same time, the pheromone intensity is... It decays over time until it decays to 0.

[0078] It should be noted that patrol drones are primarily responsible for regularly flying around power inspection points, collecting image information, and monitoring changes in the status of power facilities. Their task is to continuously monitor the inspection points and ensure the timely detection of potential anomalies or faults. When a patrol drone detects a change in the image information of a power inspection point, it records its current location and generates electronic pheromones, thereby guiding a response drone to perform further monitoring tasks. The response drone's task is to travel to a specific location for detailed monitoring based on the electronic pheromone signals generated by the patrol drone. The response drone determines whether it is attracted to a certain location based on the intensity and attraction index of the electronic pheromone, and continuously collects images and data at that location. The main task of the response drone is to further confirm and track anomalies identified by the patrol drone, and to conduct long-term continuous monitoring of the locations where potential anomalies or faults are found.

[0079] like Figure 4 As shown, a take-off and landing control device for a power line inspection drone includes a ground communication base station and a drone swarm.

[0080] Among them, ground communication base stations provide reference coordinates and wireless communication relays for UAVs.

[0081] The drone swarm includes relay drones and inspection drones, with each relay drone equipped with a Vivaldi antenna. The inspection drone swarm includes patrol drones and response drones, both of which are equipped with Vivaldi antennas, inertial measurement units (IMUs), lidar units, and camera units.

[0082] The Vivaldi antenna provides stable communication signals and data transmission for the drones, and uses its wide bandwidth and high gain to capture and transmit RFID signals, enabling the inspection drone swarm to receive RFID response signals from power inspection points in real time, thereby determining the location and relevant information of the inspection points. Furthermore, the Vivaldi antenna acts as a wireless communication relay during power inspections, maintaining communication links between different drone swarms.

[0083] The IMU (Inertial Measurement Unit) in a drone is responsible for providing accurate flight attitude and position data, and for calculating the drone's location, three-dimensional attitude, and trajectory information in real time.

[0084] The lidar unit scans the surrounding environment with a laser beam and receives reflected signals to generate high-resolution three-dimensional point cloud data, helping drones perceive the precise location of surrounding obstacles and power facilities.

[0085] The camera unit is responsible for collecting images and video information during power line inspections, monitoring the status of power facilities in real time, and helping maintenance personnel to detect potential faults or anomalies. Furthermore, during the coordination between patrol drones and response drones, the camera unit generates electronic pheromones containing location coordinate information based on changes in image information, guiding the response drones to conduct continuous monitoring.

[0086] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention, all of which fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A take-off and landing control method for a power line inspection drone, characterized in that, Includes the following steps: By capturing the response signal generated by the RFID radio frequency identification chip using the Vivaldi antenna of the drone, the power inspection point is identified, and a discrete inspection drone swarm is generated around the power inspection point; the position coordinates of the relay drone are determined based on the position information of the inspection drone swarm; and the discrete inspection drone swarm is connected in series by the relay drone to obtain the drone power inspection network. Based on the Vivaldi antenna in the relay drone, resistance loading and choke slot loading are performed to improve signal gain and frequency response in the low-frequency band, providing communication signals and GPS reference positioning for drone take-off and landing control for the entire drone power inspection network. The drone swarm in the power grid inspection network is divided into patrol drones and response drones; a motion model of the patrol drones is established based on GPS reference positioning; the motion model of the patrol drones is used to limit the movement altitude of the patrol drones to prevent the drones from colliding with the power grid inspection points due to excessive close proximity. By collecting image information from power inspection points through patrol drones, abnormal situations can be identified based on changes in the image information, and electronic pheromones can be generated; the electronic pheromones can then guide response drones for long-term monitoring.

2. The take-off and landing control method for a power line inspection drone according to claim 1, characterized in that, The specific process for identifying power inspection points is as follows: The command drone transmits radio frequency signals at a preset frequency through its onboard Vivaldi antenna while flying along a preset path, and captures the response signals of the RFID radio frequency identification chips at each power inspection point to the radio frequency signals in real time. After capturing the response signal of the radio frequency signal, the response signal is decoded to obtain the serial number, location coordinates, and geometric information of the power inspection point where the radio frequency identification chip is located. The location coordinates of each power inspection point are determined based on the RFID signals received by the drone, and then a swarm of inspection drones is deployed within a preset range near each power inspection point.

3. The take-off and landing control method for a power line inspection drone according to claim 2, characterized in that: The various inspection drone groups share a common flight altitude, which is specifically the altitude classification in the RFID chip position coordinates corresponding to the inspection drone group number i plus a preset safe flight altitude.

4. The take-off and landing control method for a power line inspection drone according to claim 1, characterized in that, The specific process of obtaining the drone power line inspection network is as follows: The location coordinates of relay drones between the various inspection drone groups are determined based on the location information of the inspection drone groups; the discrete inspection drone groups are connected in series by relay drones to obtain a drone power line inspection network. The location and number of relay drones between adjacent inspection drone groups are determined by distance assessment. Obtain any two adjacent inspection drone groups and their corresponding location coordinates, calculate the center distance between the two adjacent inspection drone groups, and determine the number of relay drones between the two adjacent inspection drone groups based on the center distance. The position of each relay drone is determined based on the center distance between two adjacent inspection drone groups and the number of relay drones; the position coordinates of each relay drone are obtained by differential calculation, and each relay drone is evenly distributed on the line connecting the inspection drone groups.

5. The take-off and landing control method for a power line inspection drone according to claim 1, characterized in that, The specific process of adjusting signal gain and frequency response in the low-frequency band is as follows: By applying a pre-set load resistor to the end of the slot of the Vivaldi antenna deployed on the relay drone, the low-frequency response region of the Vivaldi antenna is extended to cope with electromagnetic interference in the substation environment and optimize the transmission quality of communication signals and GPS positioning signals. High-frequency noise is suppressed by choke slot loading, edge effects are limited, and energy is concentrated in the slot line region, thereby improving low-frequency gain.

6. The take-off and landing control method for a power line inspection drone according to claim 1, characterized in that, The specific process of establishing the motion model of the patrol drone is as follows: Grouping initialization is performed, and each inspection drone group is divided into patrol drones and response drones according to a preset number ratio. Each inspection drone group obtains its own position coordinates in the world coordinate system through relay drones. Taking the position coordinates of each RFID chip as the origin, a three-dimensional sub-coordinate system of inspection points in the world coordinate system is established. The three-dimensional sub-coordinate system of inspection points is rasterized and divided into multiple cubic blocks of preset size. Obtain the geometric shape information of the power inspection points corresponding to each radio frequency identification chip, including the geometric center coordinates of each power inspection point, the maximum radius from the geometric center to the edge, the minimum radius, the maximum height zmax, and the maximum surface tilt angle; The patrol drone is treated as a point mass moving in a straight line between the corners of a gridded cube in three-dimensional space. Ignoring its turning angle and climb angle, a motion model of the images taken by a single patrol drone around a single power inspection point is established based on the geometric information of the power inspection point. The flight altitude of each patrol drone at each location is controlled to prevent the patrol drone from colliding with the power inspection point.

7. The take-off and landing control method for a power line inspection drone according to claim 1, characterized in that, The specific process for identifying anomalies based on changes in image information is as follows: The drone performs inspection flights and collects image information of power inspection points in real time. When a patrol drone detects a change in the image information of a power inspection point, it records the coordinates of the patrol drone's location and generates an electronic pheromone at that coordinate. The electronic pheromone is a position coordinate signal whose intensity decreases over time, and attracts responding drones to continuously monitor the coordinates based on the intensity. The attraction index is used to determine whether the responding drone is attracted by the electronic pheromone. Whenever a patrol drone generates an electronic pheromone, the distance between the responding drones in the patrol drone group and the corresponding coordinates of the electronic pheromone is immediately obtained, and the distance is substituted into the formula for the intensity decay of the electronic pheromone to calculate the attraction index.

8. The take-off and landing control method for a power line inspection drone according to claim 7, characterized in that: The attraction index is directly proportional to the pheromone intensity, inversely proportional to the distance between the responding drone and the electronic pheromone, and inversely proportional to the number of responding drones already attracted by the electronic pheromone. If the attraction index of a responding drone is found to be greater than the preset maximum attraction threshold, it is determined that the responding drone is attracted by the electronic pheromone. The responding drone is then directed to the coordinates of the location of the electronic pheromone. At the coordinates, image information of the power inspection point is continuously acquired, and the number of responding drones attracted by the electronic pheromone is increased by one. At the same time, the pheromone intensity is allowed to decay over time until it decays to 0.

9. A take-off and landing control device for a power line inspection drone, used to implement the take-off and landing control method for a power line inspection drone as described in any one of claims 1-8, characterized in that: This includes ground communication base stations and drone swarms; Among them, ground communication base stations provide reference coordinates and wireless communication relay for UAVs; The drone swarm includes relay drones and inspection drones. Each drone in the relay drone swarm is equipped with a Vivaldi antenna. The inspection drone swarm includes patrol drones and response drones. Both patrol drones and response drones are equipped with Vivaldi antennas, IMU inertial measurement units, lidar units, and camera units. The Vivaldi antenna is responsible for providing stable communication signals and data transmission for the drones. Through its wide bandwidth and high gain characteristics, it completes RFID signal capture and transmission, enabling the inspection drones to receive RFID response signals from power inspection points in real time, thereby determining the location and relevant information of the inspection points. In addition, the Vivaldi antenna completes wireless communication relay during power inspection, maintaining the communication link between various drone groups. The IMU (Inertial Measurement Unit) in a drone is responsible for providing accurate flight attitude and position data, and for calculating the drone's location, three-dimensional spatial attitude, and trajectory information in real time. The lidar unit scans the surrounding environment with a laser beam and receives reflected signals to generate high-resolution three-dimensional point cloud data, helping the drone to perceive the precise location of surrounding obstacles and power facilities. The camera unit is responsible for collecting images and video information during power inspections, monitoring the status of power facilities in real time, and helping maintenance personnel to discover potential faults or anomalies. In addition, during the coordination between patrol drones and response drones, the camera unit generates electronic pheromones containing location coordinate information based on changes in image information, guiding the response drones to conduct continuous monitoring.

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