Control method of flying robot for live working of power transmission line

Abstract

The invention discloses a control method of a flying robot for live-line work of a power transmission line, and belongs to the technical field of live-line work of the power transmission line. Selecting an optimal on-line position, generating an on-line instruction to control the flying robot to be on line at the optimal on-line position, collecting a power transmission line image, processing the collected power transmission line image, and adjusting the flying state and the line falling mode of the flying robot based on the processed image. The flight robot can find the optimal working environment in the complex environment, so that the influence of the external environment on work is reduced, the working stability of the flight robot is improved, the image of the power transmission line is collected and optimized, the accuracy of obtaining the position of the power transmission line is improved, and the working efficiency is improved. Therefore, the falling precision of the flying robot is improved, and the maintenance efficiency of the power transmission line is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of live-line working on power transmission lines, and in particular to a method for controlling a flying robot for live-line working on power transmission lines. Background Art

[0002] As the number of large-capacity and long-distance transmission lines continues to increase, conventional live-line operation methods for line maintenance operations not only fail to meet the needs of modern line maintenance, but also consume a lot of time and waste a lot of human resources, which brings many difficulties to the safe and stable operation of the line. It can be seen that the normal operation, maintenance, repair and live-line operation of transmission lines require advanced technology as support. In order to meet the safe operation of transmission lines, helicopter power operation and drone power operation technology came into being.

[0003] In recent years, with the continuous development of drone and robot technology, some flying robots have begun to be used in power inspection. However, in practical applications, these flying robots still face many challenges. For example, how to accurately evaluate and select the appropriate online location to ensure that the flying robot can operate stably in a complex electromagnetic environment, variable wind speed and obstacles is an urgent problem to be solved. In addition, since transmission lines are usually in complex environments, the collected transmission line images may be deformed. How to effectively correct the images to obtain accurate transmission line location information and achieve precise landing is also a major problem that current technology needs to overcome.

[0004] Chinese patent, publication number: CN114397904A, publication date: April 6, 2022, discloses a system, method and storage medium for drone landing on an overhead power transmission line, which controls the drone to navigate to the target position above the power transmission line; uses a camera to shoot the environment around the drone to obtain a shot video; uses a remote control to control the drone's posture on the ground according to the shot video; uses a laser radar to detect obstacle information in the environment; obtains obstacle information detected by the laser radar and the scanning parameters of the laser radar through a remote control; controls the drone for positioning and navigation according to the obstacle information and scanning parameters; after the drone reaches the target position, controls the drone to land on the conductor of the power transmission line; uses a fastening structure to fasten the conductor when the drone lands on the conductor of the power transmission line, and uses the camera, laser radar and fastening structure of the drone payload to achieve the landing of the drone on the conductor of the overhead power transmission line, but it is difficult to meet the accuracy of the drone going online and offline in complex and harsh environments. Summary of the invention

[0005] The present invention aims at the problem that the existing live working flight detection equipment is difficult to select a suitable working position in a complex environment and it is difficult to accurately select a landing position in a complex environment, resulting in low efficiency of live working. A control method for a flying robot for live working on a transmission line is provided. The method comprises the following steps: comprehensively analyzing the geographical parameters of the area around the transmission line and the configuration parameters of the flying robot, selecting the best online position and generating an online instruction to control the flying robot to go online at the best online position, collecting images of the transmission line, processing the collected images of the transmission line, adjusting the flight state and the landing mode of the flying robot based on the processed images, so that the flying robot can find the best working environment in a complex environment, thereby reducing the influence of the external environment on the work and improving the stability of the flying robot's operation. The transmission line image is collected and optimized, thereby improving the accuracy of obtaining the transmission line position, thereby improving the accuracy of the flying robot's landing and improving the efficiency of transmission line maintenance.

[0006] In a first aspect, a technical solution provided in an embodiment of the present invention is: a control method for a flying robot for live working on a transmission line, comprising the following steps: S1. Determine the initial online position corresponding to the transmission line based on the initial position assessment principle; S2. Evaluation index calculation principle: In response to the geographical parameters of the initial online position and the configuration parameters of the flying robot, an online position evaluation index of each initial online position is obtained; S3, optimal line calculation principle: In response to the on-line position evaluation index of each initial on-line position, an optimal on-line position is obtained; synchronously, an on-line instruction is generated based on the optimal on-line position; the flying robot executes the on-line action in response to the on-line instruction and collects the transmission line image in real time; S4. Based on the image processing principle, the transmission line image is processed to obtain a target image, and a line-dropping instruction is generated based on the positional relationship between the transmission line and the flying robot in the target image; the flying robot executes the line-dropping action in response to the line-dropping instruction.

[0007] In this scheme, by comprehensively analyzing the geographical parameters of the area around the transmission line and the configuration parameters of the flying robot, the best online position is selected and the online command is generated to control the flying robot to go online at the best online position, so as to realize autonomous flight and accurate evaluation of the online position, so that the flying robot can quickly reach the optimal position to operate, which greatly reduces the time and human resources required for manual live operations; by collecting transmission line images, processing the collected transmission line images, and adjusting the flight state and landing mode of the flying robot based on the processed images, the flying robot can find the best working environment in a complex environment, thereby reducing the impact of the external environment on the work and improving the stability of the flying robot's operation; by collecting transmission line images and optimizing the images, the accuracy of obtaining the transmission line position is improved, and the posture of the flying robot is adjusted according to the transmission line image, so as to improve the accuracy of the flying robot's landing, ensure that the flying robot can accurately land on the transmission line, and further improve the efficiency of transmission line maintenance.

[0008] Preferably, in S1, determining the initial online position corresponding to the transmission line based on the initial position evaluation principle includes the following steps: Based on the geographic coordinate information of the transmission line, a three-dimensional space area including the transmission line and a set range around it is used as an initial screening area; The areas in the initial screening area that do not meet the configuration parameters of the flying robot and the areas that do not meet the operation requirements of the transmission line are eliminated to obtain the initial online position.

[0009] In this solution, since the flying robot needs to work around the transmission lines and these areas may have environments where the flying robot is difficult to operate normally, in these areas, areas that do not meet the configuration parameters of the flying robot (such as complex terrain, restricted altitude, excessive wind, and other areas that are not suitable for flying) will be eliminated, and areas that do not meet the operation requirements of the transmission lines (such as areas that may interfere with or damage the transmission lines) will also be eliminated. This helps to avoid any potential threats to the transmission lines when the flying robot performs tasks, thereby ensuring the normal operation and safety of the transmission lines, and also ensures that the flying robot can avoid these dangerous areas when performing tasks, thereby ensuring its flight safety and improving operational stability; since the screening process has excluded areas that are not suitable for flying, the flying robot can focus more on the target area when performing tasks, thereby improving task execution efficiency, helping to shorten task completion time, and improving overall work efficiency.

[0010] Preferably, the configuration parameters include at least performance parameters, operation parameters and hardware parameters of the flying robot; the geographic coordinate information of the transmission line includes at least the longitude, latitude and altitude of the transmission line.

[0011] In this scheme, the screening method based on geographic coordinate information is easy to implement and monitor. Through the geographic information system (GIS) or other related technologies, the position and status of the flying robot can be monitored in real time to ensure that it performs tasks according to the predetermined plan; the configuration parameters of the flying robot can be used to infer the working stability in different environments, which helps to screen out the best online position.

[0012] Preferably, in S2, the evaluation index calculation principle obtains the online position evaluation index of each initial online position in response to the geographical parameters of the initial online position and the configuration parameters of the flying robot, including the following steps: The initial on-line position of the response evaluation index calculation principle is used as the target on-line position, and the electromagnetic compatibility of the target on-line position is obtained based on the electromagnetic field strength of the target on-line position and the hardware parameters of the flying robot; The wind resistance stability of the target upper line position is obtained based on the effective predicted wind speed, air density and performance parameters of the flying robot; Obtaining the obstacle safety degree of the target upper line position based on the obstacle density, obstacle inclination and safety margin of the target upper line position; Electromagnetic compatibility, wind resistance stability and obstacle safety are used as evaluation indicators of the target upper line position.

[0013] In this scheme, due to the complex electromagnetic field around the transmission lines, this may interfere with the electronic equipment of the flying robot, causing its navigation, communication or control system to fail. At the same time, the wind speed around the transmission lines varies greatly, which will affect the flight stability of the flying robot and may even cause it to lose control. In addition, there may be obstacles such as trees and buildings around the transmission lines. These obstacles may hinder the flight path of the flying robot and increase the risk of collision. Therefore, in order to reduce the above risks, a comprehensive evaluation of electromagnetic compatibility, obstacle safety and wind resistance stability is carried out to screen out the area with the least impact on the work of the flying robot as the best online area, which helps the flying robot to focus more on the target area when performing tasks, thereby improving the efficiency of task execution, helping to shorten the task completion time and improve overall work efficiency.

[0014] Preferably, the performance parameters of the flying robot include at least the orthographic projection area and the drag coefficient; the operating parameters of the flying robot include at least the maximum flying altitude, the maximum flying speed and the minimum turning radius; and the hardware parameters of the flying robot include at least the sensitivity coefficient of the electronic equipment.

[0015] In this scheme, the orthographic projection area and drag coefficient of the flying robot help to calculate the wind resistance stability of the online position; the maximum flight altitude, maximum flight speed and minimum turning radius of the flying robot help to eliminate areas that are not suitable for the operation of the flying robot; the sensitivity coefficient of the electronic equipment of the flying robot helps to calculate the electromagnetic compatibility of the online position, and the optimal online position is obtained by analyzing various parameters of the flying robot, which helps to improve the accuracy and reliability of the optimal online position.

[0016] Preferably, in S3, the optimal route calculation principle obtains the optimal online position in response to the online position evaluation index of each initial online position; synchronously, generates an online instruction based on the optimal online position; and the flying robot performs the online action in response to the online instruction, including the following steps: The online position evaluation index of each initial online position is weightedly summed to obtain a comprehensive evaluation value, and the initial online position corresponding to the online position evaluation index with the highest comprehensive evaluation value is taken as the optimal online position; Based on the geographical parameters of the optimal online position, an online instruction is generated to control the flying robot to fly to the optimal online position.

[0017] In this scheme, by comprehensively considering various key factors that affect the selection of the flying robot's online position, including electromagnetic compatibility, wind resistance stability, obstacle safety, etc., a comprehensive evaluation method is adopted to more accurately reflect the complexity and variability of the actual flight environment, thereby improving the accuracy and reliability of the online position selection.

[0018] Preferably, in S4, the transmission line image is processed based on image processing principles to obtain a target image, including the following steps: Preprocessing the transmission line image and detecting the edge smoothness of the transmission line in the transmission line image; If the edge smoothness is less than the smoothness threshold, the power line image is used as a deformed power line image, and each pixel value of the deformed power line image is converted into a complex form and the deformed power line image is integrated into an intermediate image, in which each element corresponds to a pixel in the deformed power line image; The target image is obtained by performing deformation correction on the intermediate image based on the chaotic complex domain correction algorithm.

[0019] In this scheme, the edge smoothness of the transmission line in the transmission line image is detected to determine whether the transmission line is deformed. If there is deformation, it is regarded as a deformed transmission line image and each pixel value is converted into a complex form, which provides a data basis for the subsequent chaotic complex domain correction algorithm. The complex form can more comprehensively represent the information of the pixel, including amplitude and phase, which helps to simplify complex image problems, reduce the amount of calculation, and improve calculation efficiency. Deformation correction through the chaotic complex domain correction algorithm can significantly reduce or eliminate deformation problems such as distortion and stretching in the deformed transmission line image, restore its original shape and characteristics, and improve the accuracy of transmission line position recognition, thereby improving the accuracy of the landing position of the flying robot.

[0020] Preferably, the intermediate image is deformed and corrected in response to a chaotic complex domain correction algorithm to obtain a target image, comprising the following steps: A chaotic mapping function is defined based on the difference between the edge smoothness of the transmission line and a smoothness threshold; Mapping each element in the intermediate image based on the chaotic mapping function to obtain a first processed image; Adopting an iterative optimization algorithm, adjusting the parameters of the chaotic mapping function until the error between the first processed image and the intermediate image is less than a set threshold, the target complex domain coordinates are obtained; The real part of the target complex domain coordinates is extracted and used as the pixel value of the deformed power line image at the corresponding pixel coordinates to obtain the target image.

[0021] In this scheme, by analyzing the deformation characteristics in the transmission line image, such as the type (stretching, compression, distortion, etc.) and degree of deformation, according to the deformation characteristics, the appropriate chaotic mapping type is selected to define the chaotic mapping function, which can adaptively process the transmission line images with different deformation degrees, wherein the difference between the edge smoothness of the transmission line and the smoothness threshold can reflect the degree of deformation; by using the chaotic mapping function to map each element in the intermediate image, a first processed image can be obtained, which can retain the detailed features of the image while reducing or eliminating the distortion, stretching and other problems caused by deformation; adjusting the parameters of the chaotic mapping function through an iterative optimization algorithm helps to accelerate the convergence speed of the algorithm, improve the computational efficiency, and further improve the accuracy of the correction; after the target image is corrected, its deformation problem is significantly improved, which makes the image clearer and more intuitive. In applications such as power inspection, it not only helps the flying robot to accurately identify the location of the transmission line, but also helps the staff to more accurately judge the status and potential problems of the transmission line, thereby improving the inspection efficiency.

[0022] Preferably, the preprocessing at least includes using a filtering algorithm to remove noise in the transmission line image and using a contrast enhancement algorithm to increase the contrast between the transmission line and the background in the transmission line image.

[0023] In this scheme, if the environment in which the flying robot is working is relatively complex, the clarity of the transmission line image can be improved by using a filtering algorithm to remove noise and a contrast enhancement algorithm, which helps to reduce the interference of the external environment on it when calibrating the transmission line image and improve the image quality, thereby improving the accuracy of obtaining the transmission line position, thereby improving the accuracy of the flying robot's landing position.

[0024] Preferably, in S4, generating a line drop instruction based on the positional relationship between the power transmission line and the flying robot in the target image includes the following steps: Determine the laying direction of the transmission line based on the installation position of the transmission line in the target image, and generate a line-dropping instruction based on the laying direction of the transmission line and the deviation angle of the nose direction of the flying robot; The flying robot adjusts its flight attitude in response to the line-dropping instruction until the deviation angle between the nose direction of the flying robot and the laying direction of the transmission line is equal to a preset angle, and lands the flying robot on the transmission line.

[0025] In this solution, the laying direction of the transmission line can be accurately determined by the installation position of the transmission line in the target image. This helps the flying robot to accurately identify the position of the transmission line during flight and adjust the flight attitude accordingly to ensure that it can accurately align with the transmission line when landing; during the landing process, the flying robot can ensure a more stable and safe contact with the transmission line by accurately adjusting the flight attitude, avoiding the risk of damage to the flying robot or the transmission line due to improper landing, and improving the safety of the overall operation; by accurately controlling the landing process of the flying robot, the interference and damage to the surrounding environment can be reduced. For example, in complex terrain or sensitive areas, accurate landing can avoid damage to ground vegetation or buildings and reduce the impact on the environment; in power inspection, maintenance and other operations, the flying robot can quickly and accurately land on the transmission line, thereby shortening the operation time and improving work efficiency. At the same time, the accurate landing position also helps to improve the quality of the operation and ensure the smooth progress of maintenance or inspection work.

[0026] Beneficial effects of the present invention: (1) The present invention comprehensively analyzes the geographical parameters of the area around the power transmission line and the configuration parameters of the flying robot, selects the best online position and generates an online instruction to control the flying robot to go online at the best online position, thereby realizing autonomous flight and accurately evaluating the online position, so that the flying robot can quickly reach the optimal position for operation, greatly reducing the time and human resources required for manual live line operation; (2) The present invention collects transmission line images, processes the collected transmission line images, and adjusts the flight state and landing mode of the flying robot based on the processed images, so that the flying robot can find the best working environment in a complex environment, thereby reducing the impact of the external environment on the work and improving the stability of the flying robot's operation; (3) The present invention improves the accuracy of obtaining the location of the transmission line by collecting images of the transmission line and optimizing the images, and adjusts the posture of the flying robot according to the transmission line image, thereby improving the accuracy of the flying robot's landing, ensuring that the flying robot can accurately land on the transmission line, and further improving the efficiency of transmission line maintenance.

[0027] The above invention content is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0029] Figure 1 The present invention is a flow chart of a control method of a flying robot for live working on power transmission lines. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0031] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0032] Example: Figure 1 As shown, in order to solve the problem that the existing live working flight detection equipment is difficult to select a suitable working position in a complex environment and it is difficult to accurately select a landing position in a complex environment, resulting in low efficiency of live working, this embodiment provides a control method for a live working flight robot on a transmission line, including the following steps: S1: Determine the initial online position corresponding to the transmission line based on the initial position assessment principle.

[0033] In this embodiment, determining the initial on-line position corresponding to the transmission line based on the initial position evaluation principle includes the following steps: Based on the geographic coordinate information of the transmission line, a three-dimensional space area including the transmission line and a set range around it is used as an initial screening area; The areas in the initial screening area that do not meet the configuration parameters of the flying robot and the areas that do not meet the operation requirements of the transmission line are eliminated to obtain the initial online position.

[0034] In this embodiment, since the flying robot needs to work around the transmission lines, and these areas may have environments where the flying robot has difficulty in operating normally, in these areas, areas that do not meet the configuration parameters of the flying robot (such as areas with complex terrain, limited altitude, excessive wind, etc. that are not suitable for flying) will be eliminated, and areas that do not meet the operating requirements of the transmission lines (such as areas that may interfere with or damage the transmission lines) will also be eliminated. This helps to avoid any potential threats to the transmission lines when the flying robot performs tasks, thereby ensuring the normal operation and safety of the transmission lines, and also ensures that the flying robot can avoid these dangerous areas when performing tasks, thereby ensuring its flight safety and improving operational stability; since the screening process has excluded areas that are not suitable for flying, the flying robot can focus more on the target area when performing tasks, thereby improving task execution efficiency, helping to shorten task completion time, and improving overall work efficiency.

[0035] Specifically, before determining the online location, some feasible initial online locations are screened out by some conventional means. For example, according to the geographic coordinate information (longitude, latitude, altitude) of the transmission line, a three-dimensional space area containing the transmission line and a certain range around it is determined as the initial screening area. Set the performance parameters of the drone, including the maximum flight altitude, maximum flight speed, minimum turning radius, etc. Then continue to exclude those locations that the drone cannot reach or fly stably due to performance limitations. For example, locations where the altitude exceeds the limit, or locations where the drone cannot maintain due to complex terrain. Determine the prohibited flight areas of the transmission line, etc. Among the remaining flyable locations, further exclude those locations that do not meet the safety requirements of the transmission line.

[0036] In this embodiment, the configuration parameters include at least the performance parameters, operation parameters and hardware parameters of the flying robot; the geographic coordinate information of the power transmission line includes at least the longitude, latitude and altitude of the power transmission line.

[0037] The screening method based on geographic coordinate information in this embodiment is easy to implement and monitor. Through the geographic information system (GIS) or other related technologies, the position and status of the flying robot can be monitored in real time to ensure that it performs tasks according to the predetermined plan; the configuration parameters of the flying robot can be used to calculate the working stability in different environments, which helps to screen out the best online position.

[0038] S2: Evaluation Index Calculation Principles The online position evaluation index of each initial online position is obtained in response to the geographic parameters of the initial online position and the configuration parameters of the flying robot.

[0039] In this embodiment, the evaluation index calculation principle obtains the online position evaluation index of each initial online position in response to the geographical parameters of the initial online position and the configuration parameters of the flying robot, including the following steps: The initial on-line position in response to the on-line position evaluation principle is used as the target on-line position, and the electromagnetic compatibility of the target on-line position is obtained based on the electromagnetic field strength of the target on-line position and the hardware parameters of the flying robot; Specifically, the calculation formula for the electromagnetic compatibility is: Where E(P) represents the electromagnetic field strength at the upper line position P, and S(P) represents the sensitivity coefficient of the electronic equipment of the flying robot.

[0040] The existing method only considers the absolute value of the electromagnetic field strength, while ignoring the sensitivity of the electronic equipment of the flying robot. This embodiment introduces the sensitivity coefficient S(P) to more comprehensively evaluate the electromagnetic compatibility of the flying robot at a specific location, thereby improving the accuracy of the evaluation.

[0041] The wind resistance stability of the target upper line position is obtained based on the effective predicted wind speed, air density and performance parameters of the flying robot; Specifically, the calculation formula for wind resistance stability is: In the formula, v f (P) represents the effective predicted wind speed at the upper line position P, defined as v z (p) represents the longitudinal component of the predicted wind speed, v h (P) represents the lateral component of the predicted wind speed, k is the adjustment factor, S trepresents the drag coefficient of the flying robot, A represents the orthographic projection area of ​​the flying robot, and ρ represents the air density.

[0042] The traditional method only considers wind resistance, which easily ignores the impact of wind speed on the flying robot and cannot accurately reflect the actual impact of wind direction on the flight stability and wind resistance of the UAV. In order to more accurately calculate the wind resistance stability, this embodiment introduces the effective wind speed, considers the vector decomposition of the wind speed, and processes the longitudinal component and the transverse component of the wind speed separately. However, since the transverse wind mainly affects the lateral displacement and stability of the UAV rather than directly increasing the wind resistance, it is necessary to focus on the longitudinal wind speed and use it as an approximation of the effective wind speed. But in order to more comprehensively consider the impact of wind direction, we can introduce a stability adjustment factor related to the transverse wind speed. It is used to weigh the impact of the transverse wind speed on the stability of the UAV. This factor may need to be adjusted according to the specific design and flight conditions of the UAV.

[0043] Obtaining the obstacle safety degree of the target upper line position based on the obstacle density, obstacle inclination and safety margin of the target upper line position; Specifically, the calculation formula for obstacle safety is: In the formula, O(P) represents the density of obstacles, A(P) represents the inclination of obstacles, S represents the a Indicates safety margin.

[0044] It should be noted that the obstacle density is determined by the size and number of obstacles within the preset range of the upper line position, and the obstacle inclination is determined according to the angle between the target obstacle within the preset range of the upper line position and the upper obstacle closest to the target obstacle.

[0045] The obstacle safety calculation formula provided in this embodiment not only takes into account factors such as the size and number of obstacles, but also introduces the inclination angle of the obstacles, thereby more comprehensively evaluating the environmental safety risks faced by the drone during flight. This evaluation method helps to improve the flight safety of the drone and reduce the risk of collision with obstacles.

[0046] Electromagnetic compatibility, wind resistance stability and obstacle safety are used as evaluation indicators of the target upper line position.

[0047] In this embodiment, due to the complex electromagnetic field around the transmission lines, this may interfere with the electronic equipment of the flying robot, causing its navigation, communication or control system to fail. At the same time, the wind speed around the transmission lines varies greatly, which will affect the flight stability of the flying robot and may even cause it to lose control. In addition, there may be obstacles such as trees and buildings around the transmission lines. These obstacles may hinder the flight path of the flying robot and increase the risk of collision. Therefore, in order to reduce the above risks, a comprehensive evaluation is conducted on electromagnetic compatibility, obstacle safety and wind resistance stability, so as to screen out the area with the least impact on the work of the flying robot as the best online area, which helps the flying robot to focus more on the target area when performing tasks, thereby improving the efficiency of task execution, helping to shorten the task completion time and improving overall work efficiency.

[0048] In this embodiment, the performance parameters of the flying robot include at least the orthographic projection area and the drag coefficient; the operating parameters of the flying robot include at least the maximum flying altitude, the maximum flying speed and the minimum turning radius; the hardware parameters of the flying robot include at least the sensitivity coefficient of the electronic equipment.

[0049] This embodiment helps to calculate the wind resistance stability of the upper-line position through the orthographic projection area and the drag coefficient of the flying robot; helps to eliminate areas that are not suitable for the operation of the flying robot through the maximum flying altitude, maximum flying speed and minimum turning radius of the flying robot; helps to calculate the electromagnetic compatibility of the upper-line position through the sensitivity coefficient of the electronic equipment of the flying robot, and by analyzing various parameters of the flying robot, the optimal upper-line position is obtained, which helps to improve the accuracy and reliability of the optimal upper-line position.

[0050] S3: Optimal line calculation principle: In response to the online position evaluation index of each initial online position, the optimal online position is obtained; synchronously, an online instruction is generated based on the optimal online position; the flying robot executes the online action in response to the online instruction and collects the transmission line image in real time.

[0051] In this embodiment, the optimal route calculation principle obtains the optimal online position in response to the online position evaluation index of each initial online position; synchronously, generates an online instruction based on the optimal online position; and the flying robot performs the online action in response to the online instruction, including the following steps: The online position evaluation index of each initial online position is weightedly summed to obtain a comprehensive evaluation value, and the initial online position corresponding to the online position evaluation index with the highest comprehensive evaluation value is taken as the optimal online position; Based on the geographical parameters of the optimal online position, an online instruction is generated to control the flying robot to fly to the optimal online position.

[0052] This embodiment comprehensively considers multiple key factors that affect the selection of the flying robot's online position, including electromagnetic compatibility, wind resistance stability, obstacle safety, etc., and adopts a comprehensive evaluation method to more accurately reflect the complexity and variability of the actual flight environment, thereby improving the accuracy and reliability of the online position selection.

[0053] S4: Based on the image processing principle, the transmission line image is processed to obtain a target image, and a line-dropping instruction is generated based on the positional relationship between the transmission line and the flying robot in the target image; the flying robot executes the line-dropping action in response to the line-dropping instruction.

[0054] In this embodiment, the transmission line image is processed based on the image processing principle to obtain the target image, including the following steps: Preprocessing the transmission line image and detecting the edge smoothness of the transmission line in the transmission line image; If the edge smoothness is less than the smoothness threshold, the power line image is used as a deformed power line image, and each pixel value of the deformed power line image is converted into a complex form and the deformed power line image is integrated into an intermediate image, in which each element corresponds to a pixel in the deformed power line image; The intermediate image is deformed and corrected in response to the chaotic complex domain correction algorithm to obtain the target image.

[0055] This embodiment determines whether the transmission line is deformed by detecting the edge smoothness of the transmission line in the transmission line image. If deformation exists, it is regarded as a deformed transmission line image and each pixel value is converted into a complex form, which provides a data basis for the subsequent chaotic complex domain correction algorithm. The complex form can more comprehensively represent the information of the pixel, including amplitude and phase, which helps to simplify complex image problems, reduce the amount of calculation, and improve calculation efficiency. Deformation correction through the chaotic complex domain correction algorithm can significantly reduce or eliminate deformation problems such as distortion and stretching in the deformed transmission line image, restore its original shape and characteristics, and improve the accuracy of transmission line position recognition, thereby improving the accuracy of the landing position of the flying robot.

[0056] In this embodiment, the image of the transmission line taken by the drone under the influence of wind may be deformed or blurred, and the influence of wind on the image taken by the drone is complex and difficult to predict, similar to the phenomenon that small changes in a chaotic system lead to huge differences. At the same time, complex domain transformation performs well in signal processing and image processing, and can reveal complex structures hidden in the real domain. Therefore, this embodiment uses the intermediate image to respond to the chaotic complex domain correction algorithm to perform deformation correction to obtain the target image, including the following steps: A chaotic mapping function is defined based on the difference between the edge smoothness of the transmission line and the smoothness threshold. For example, the Logistic mapping is applicable to one-dimensional or simple two-dimensional deformation, while the Henon mapping or more complex chaotic mapping is applicable to more complex two-dimensional or three-dimensional deformation. According to the specific needs of image correction, the standard formula may need to be adjusted or expanded to adapt to specific deformation modes; Mapping each element in the intermediate image based on the chaotic mapping function to obtain a first processed image; Adopting an iterative optimization algorithm (such as genetic algorithm, particle swarm optimization, etc.) to adjust the parameters of the chaotic mapping function until the error between the first processed image and the intermediate image is less than a set threshold to obtain the target complex domain coordinates; Since the imaginary part usually does not carry valid information during the image correction process (or the information it carries has little effect on the correction result), it can be ignored. Therefore, it is only necessary to extract the real part of the target complex domain coordinates and obtain the target image as the pixel value of the deformed power line image at the corresponding pixel coordinates.

[0057] This embodiment analyzes the deformation characteristics in the transmission line image, such as the type (stretching, compression, distortion, etc.) and degree of deformation, and selects a suitable chaos mapping type according to the deformation characteristics to define a chaos mapping function, so as to adaptively process the transmission line images with different deformation degrees, wherein the difference between the edge smoothness of the transmission line and the smoothness threshold can reflect the deformation degree; by using the chaos mapping function to map each element in the intermediate image, a first processed image can be obtained, which can retain the detailed features of the image while reducing or eliminating the distortion, stretching and other problems caused by the deformation; adjusting the parameters of the chaos mapping function through an iterative optimization algorithm helps to accelerate the convergence speed of the algorithm, improve the calculation efficiency, and further improve the accuracy of the correction; after the target image is corrected, its deformation problem is significantly improved, which makes the image clearer and more intuitive. In applications such as power inspection, it not only helps the flying robot to accurately identify the location of the transmission line, but also helps the staff to more accurately judge the status and potential problems of the transmission line, thereby improving the inspection efficiency.

[0058] In this embodiment, the preprocessing at least includes using a filtering algorithm (such as Gaussian filtering, mean filtering, etc.) to remove noise in the transmission line image and using a contrast enhancement algorithm (such as histogram equalization, adaptive contrast enhancement, etc.) to improve the contrast between the transmission line and the background in the transmission line image.

[0059] In this embodiment, if the environment in which the flying robot is working is relatively complex, the clarity of the transmission line image is improved by using a filtering algorithm to remove noise and a contrast enhancement algorithm, which helps to reduce the interference of the external environment on it when calibrating the transmission line image and improve the image quality, thereby improving the accuracy of obtaining the transmission line position, thereby improving the accuracy of the flying robot's landing position.

[0060] In this embodiment, generating a line drop instruction based on the positional relationship between the power transmission line and the flying robot in the target image includes the following steps: Determine the laying direction of the transmission line based on the installation position of the transmission line in the target image, and generate a line-dropping instruction based on the laying direction of the transmission line and the deviation angle of the nose direction of the flying robot; The flying robot adjusts its flight attitude in response to the line-dropping instruction until the deviation angle between the nose direction of the flying robot and the laying direction of the transmission line is equal to a preset angle, and lands the flying robot on the transmission line.

[0061] This embodiment can accurately determine the laying direction of the transmission line through the installation position of the transmission line in the target image. This helps the flying robot to accurately identify the position of the transmission line during flight, and adjust the flight attitude accordingly to ensure that it can accurately align with the transmission line when landing; during the landing process, the flying robot can ensure that the contact with the transmission line is more stable and safe by accurately adjusting the flight attitude, avoiding the risk of damage to the flying robot or the transmission line caused by improper landing, and improving the safety of the overall operation; by accurately controlling the landing process of the flying robot, the interference and damage to the surrounding environment can be reduced. For example, in complex terrain or sensitive areas, accurate landing can avoid damage to ground vegetation or buildings and reduce the impact on the environment; in power inspection, maintenance and other operations, the flying robot can quickly and accurately land on the transmission line, thereby shortening the operation time and improving work efficiency. At the same time, the accurate landing position also helps to improve the quality of the operation and ensure the smooth progress of maintenance or inspection work.

[0062] This embodiment comprehensively analyzes the geographical parameters of the area around the transmission line and the configuration parameters of the flying robot, selects the best online position and generates an online instruction to control the flying robot to go online at the best online position, thereby realizing autonomous flight and accurately evaluating the online position, so that the flying robot can quickly reach the optimal position to perform operations, greatly reducing the time and human resources required for manual live operations; by collecting transmission line images, processing the collected transmission line images, and adjusting the flight state and landing mode of the flying robot based on the processed images, the flying robot can find the best working environment in a complex environment, thereby reducing the impact of the external environment on the work and improving the stability of the flying robot's operation; by collecting transmission line images and optimizing the images, the accuracy of obtaining the transmission line position is improved, and the posture of the flying robot is adjusted according to the transmission line image, thereby improving the accuracy of the flying robot's landing, ensuring that the flying robot can accurately land on the transmission line, and further improving the efficiency of transmission line maintenance.

[0063] It can be seen from the above embodiments that at least the following substantial effects are achieved: (1) The present invention comprehensively analyzes the geographical parameters of the area around the power transmission line and the configuration parameters of the flying robot, selects the best online position and generates an online instruction to control the flying robot to go online at the best online position, thereby realizing autonomous flight and accurately evaluating the online position, so that the flying robot can quickly reach the optimal position for operation, greatly reducing the time and human resources required for manual live line operation; (2) The present invention collects transmission line images, processes the collected transmission line images, and adjusts the flight state and landing mode of the flying robot based on the processed images, so that the flying robot can find the best working environment in a complex environment, thereby reducing the impact of the external environment on the work and improving the stability of the flying robot's operation; (3) The present invention improves the accuracy of obtaining the location of the transmission line by collecting images of the transmission line and optimizing the images, and adjusts the posture of the flying robot according to the transmission line image, thereby improving the accuracy of the flying robot's landing, ensuring that the flying robot can accurately land on the transmission line, and further improving the efficiency of transmission line maintenance.

[0064] The specific implementation described above is a preferred implementation of a method for controlling a flying robot for live working on transmission lines of the present invention, and is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation. All equivalent changes made to the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A control method for a flying robot for live working on a power transmission line, characterized in that: The following steps are involved: S1. Determine the initial online position corresponding to the transmission line based on the initial position assessment principle; S2. Evaluation index calculation principle: In response to the geographical parameters of the initial online position and the configuration parameters of the flying robot, an online position evaluation index of each initial online position is obtained; S3, optimal line calculation principle: obtaining an optimal online position in response to the online position evaluation index of each initial online position; synchronously, generating an online instruction based on the optimal online position; The flying robot responds to the online instruction to execute the online action and collect the transmission line image in real time; S4. Based on the image processing principle, the transmission line image is processed to obtain a target image, and a line-dropping instruction is generated based on the positional relationship between the transmission line and the flying robot in the target image; the flying robot executes the line-dropping action in response to the line-dropping instruction.

2. A method for controlling a flying robot for live working on a power transmission line according to claim 1, characterized in that: In S1, the initial online position corresponding to the transmission line is determined based on the initial position evaluation principle, including the following steps: Based on the geographic coordinate information of the transmission line, a three-dimensional space area including the transmission line and a set range around it is used as an initial screening area; The areas in the initial screening area that do not meet the configuration parameters of the flying robot and the areas that do not meet the operation requirements of the transmission line are eliminated to obtain the initial online position.

3. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 2, characterized in that: The configuration parameters include at least the performance parameters, operation parameters and hardware parameters of the flying robot; the geographic coordinate information of the transmission line includes at least the longitude, latitude and altitude of the transmission line.

4. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 3, characterized in that: In S2, the evaluation index calculation principle obtains the online position evaluation index of each initial online position in response to the geographical parameters of the initial online position and the configuration parameters of the flying robot, including the following steps: The initial on-line position of the response evaluation index calculation principle is used as the target on-line position, and the electromagnetic compatibility of the target on-line position is obtained based on the electromagnetic field strength of the target on-line position and the hardware parameters of the flying robot; The wind resistance stability of the target upper line position is obtained based on the effective predicted wind speed, air density and performance parameters of the flying robot; Obtaining the obstacle safety degree of the target upper line position based on the obstacle density, obstacle inclination and safety margin of the target upper line position; Electromagnetic compatibility, wind resistance stability and obstacle safety are used as evaluation indicators of the target upper line position.

5. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 4, characterized in that: The performance parameters of the flying robot include at least the orthographic projection area and the drag coefficient; the operating parameters of the flying robot include at least the maximum flying altitude, the maximum flying speed and the minimum turning radius; the hardware parameters of the flying robot include at least the sensitivity coefficient of the electronic equipment.

6. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 1, characterized in that: In S3, the optimal line calculation principle obtains the optimal online position in response to the online position evaluation index of each initial online position; synchronously, generates an online instruction based on the optimal online position; The flying robot performs an online action in response to the online instruction, including the following steps: The online position evaluation index of each initial online position is weightedly summed to obtain a comprehensive evaluation value, and the initial online position corresponding to the online position evaluation index with the highest comprehensive evaluation value is taken as the optimal online position; Based on the geographical parameters of the optimal online position, an online instruction is generated to control the flying robot to fly to the optimal online position.

7. The method for controlling a flying robot for live-line operation of a power transmission line according to claim 1, characterized in that: In S4, the transmission line image is processed based on the image processing principle to obtain the target image, including the following steps: Preprocessing the transmission line image and detecting the edge smoothness of the transmission line in the transmission line image; If the edge smoothness is less than the smoothness threshold, the power line image is used as a deformed power line image, and each pixel value of the deformed power line image is converted into a complex form and the deformed power line image is integrated into an intermediate image, in which each element corresponds to a pixel in the deformed power line image; The target image is obtained by performing deformation correction on the intermediate image based on the chaotic complex domain correction algorithm.

8. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 7, characterized in that: The target image is obtained by performing deformation correction on the intermediate image based on the chaotic complex domain correction algorithm, including the following steps: A chaotic mapping function is defined based on the difference between the edge smoothness of the transmission line and a smoothness threshold; Mapping each element in the intermediate image based on the chaotic mapping function to obtain a first processed image; Adopting an iterative optimization algorithm, adjusting the parameters of the chaotic mapping function until the error between the first processed image and the intermediate image is less than a set threshold, the target complex domain coordinates are obtained; The real part of the target complex domain coordinates is extracted and used as the pixel value of the deformed power line image at the corresponding pixel coordinates to obtain the target image.

9. A method for controlling a flying robot for live-line operation of a power transmission line according to claim 7, characterized in that: The preprocessing at least includes using a filtering algorithm to remove noise in the transmission line image and using a contrast enhancement algorithm to improve the contrast between the transmission line and the background in the transmission line image.

10. The method for controlling a flying robot for live-line operation of a power transmission line according to claim 1, characterized in that: In S4, a line drop instruction is generated based on the positional relationship between the power transmission line and the flying robot in the target image, including the following steps: Determine the laying direction of the transmission line based on the installation position of the transmission line in the target image, and generate a line-dropping instruction based on the laying direction of the transmission line and the deviation angle of the nose direction of the flying robot; The flying robot adjusts its flight attitude in response to the line-dropping instruction until the deviation angle between the nose direction of the flying robot and the laying direction of the transmission line is equal to a preset angle, and lands the flying robot on the transmission line.

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