Remote installation and removal method of wire anti-dancing spacer cooperated with unmanned aerial vehicle

Abstract

The application discloses an unmanned aerial vehicle cooperative wire anti-dancing spacer remote mounting and dismounting method, relates to the related technical field of wire spacers, and comprises the following steps: collecting time-series wind speed data and wire erection data of a target area, performing wind deflection dancing fitting, and combining with the unmanned aerial vehicle cooperation performance to set a wind speed stability index; performing wind speed stability index breakthrough analysis, and establishing an unmanned aerial vehicle track route if the analysis fails; positioning the first dismounting end of the anti-dancing spacer after a first unmanned aerial vehicle arrives at the target area, reconstructing a path, combining with a real-time wind speed optimization approach control strategy, connecting the first dismounting end and dismounting, and connecting the second dismounting end after a threshold is met; and the two unmanned aerial vehicles form a cooperative transportation group to transport the spacers. The technical problems that a single unmanned aerial vehicle is not accurately positioned, has poor operation stability and has a low dismounting success rate due to wire dancing in a complex wind field environment are solved, and the technical effect that the wire anti-dancing spacer is high-precision, safe and reliable in a dynamic wind field is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric wire spacer, and particularly to a method for remotely installing and uninstalling an electric wire anti-dancing spacer in cooperation with a UAV. BACKGROUND

[0002] The stability and safety of high-voltage and ultra-high-voltage transmission lines are extremely important. In various meteorological disasters, conductor dancing caused by external excitations such as strong wind and icing is an important factor threatening the safe operation of power grids. Conductor dancing can lead to line tripping, hardware wear and tear, tower component damage, and even tower collapse and other serious accidents. Anti-dancing spacers are widely used in transmission lines to constrain the relative movement of conductors by mechanical means, thereby dispersing dynamic loads and improving the anti-dancing ability of the line. However, the installation and uninstallation of traditional anti-dancing spacers usually rely on manual high-altitude operations, which increases the difficulty of operation in complex terrain or adverse weather conditions, resulting in low efficiency, high cost, and high safety risks. With the widespread application of UAV technology in the field of power inspection, UAVs are used to assist in installing spacers, but most of them are in single-machine operation mode. In the face of large-span, high-suspension, and strong disturbance environments, there are still problems such as insufficient positioning accuracy, poor wind resistance stability, and limited coordination capability.

[0003] In the related art at the present stage, there are technical problems of single UAV in complex wind field environment due to conductor dancing leading to inaccurate positioning, poor operation stability, and low installation and uninstallation success rate. SUMMARY

[0004] The present application provides a method for remotely installing and uninstalling an electric wire anti-dancing spacer in cooperation with a UAV, which solves the technical problems of single UAV in complex wind field environment due to conductor dancing leading to inaccurate positioning, poor operation stability, and low installation and uninstallation success rate in the prior art, and achieves the technical effect of high-precision, safe and reliable installation and uninstallation of electric wire anti-dancing spacers in dynamic wind fields.

[0005] The application provides a method for remotely loading and unloading a wire anti-dancing spacer in cooperation with a UAV, which comprises the following steps: collecting wind speed data of a target area, establishing a time-series wind speed dataset, synchronously acquiring wire erection data of a target wire, fitting wind deviation dancing according to the wire erection data, setting a wind speed stability index by using the wind deviation dancing fitting result and the UAV cooperation performance; performing wind speed stability index breaking analysis on the time-series wind speed dataset based on wind speed extreme value and wind speed stability, and establishing a UAV trajectory route according to the wire erection data if the result is a failure result; starting a visual detection unit to perform positioning of a first unloading end of the anti-dancing spacer when a first UAV reaches the target area along the UAV trajectory route, reconstructing a positioning trajectory path; reading real-time wind speed data, performing proximity control optimization according to the real-time wind speed data and the positioning trajectory path, and establishing a proximity control optimization strategy; controlling the first UAV to perform a first unloading end connection after the proximity control optimization strategy is used, performing an unloading operation, and controlling a second UAV to connect a second unloading end when an unloading state meets a preset unloading threshold; sequentially performing unloading of the first unloading end and the second unloading end, and then forming a cooperative transportation group composed of the first UAV and the second UAV to perform remote transportation of the anti-dancing spacer.

[0006] In a possible implementation, the method for remotely loading and unloading the wire anti-dancing spacer in cooperation with the UAV further performs the following processing: establishing a real-time state space, wherein the real-time state space comprises a real-time wind speed sequence, a positioning trajectory path, and position and attitude data of the first UAV; performing short-term trend prediction of wind speed according to the real-time state space, and establishing a short-term trend prediction result; performing side wind bias compensation of the positioning trajectory path by using the short-term trend prediction result, and establishing a pre-compensation parameter; after a cost function is set, performing hierarchical proximity control optimization based on the real-time state space and the pre-compensation parameter, and establishing a proximity control optimization strategy.

[0007] In a possible implementation, the method for remotely loading and unloading the wire anti-dancing spacer in cooperation with the UAV further performs the following processing: adaptively configuring path hierarchy according to the real-time wind speed data and the positioning trajectory path, wherein the path hierarchy comprises a remote segment layer, an intermediate segment layer, and a short-range segment layer; configuring an evaluation item weight of a cost function by using the path hierarchy, wherein the evaluation items of the cost function comprise a wind speed disturbance suppression cost item, a trajectory deviation cost item, an attitude stability cost item, an energy consumption cost item, a task safety margin cost item, and a time response cost item; taking the real-time state space and the pre-compensation parameter as initial constraint conditions, and performing hierarchical proximity control optimization according to the path hierarchy and the mapped cost function.

[0008] In a possible implementation, the unmanned aerial vehicle cooperative power line anti-dancing spacer remote loading and unloading method further performs the following processing: when the unloading state of the first unloading end meets a preset unloading threshold, a connection instruction is synchronously activated; the connection instruction is used to control the unloading and transportation assembly of the first unmanned aerial vehicle to perform active connection of the anti-dancing spacer; after the second unmanned aerial vehicle completes the active connection and performs unloading of the second unloading end, a cooperative transportation group composed of the first unmanned aerial vehicle and the second unmanned aerial vehicle is formed to perform cooperative transportation control of the anti-dancing spacer.

[0009] In a possible implementation, the unmanned aerial vehicle cooperative power line anti-dancing spacer remote loading and unloading method further performs the following processing: a control target object is reconstructed by the first unmanned aerial vehicle, the second unmanned aerial vehicle, the anti-dancing spacer, and the active connection component; a taboo space is reconstructed according to the power line erection data and current wind speed data; a return path planning result is established by using the control target object and the taboo space to perform return path planning; and the control roles of the master control machine and the follower of the first unmanned aerial vehicle and the second unmanned aerial vehicle are dynamically switched according to real-time tension difference and attitude offset along the return path planning result, so as to complete the cooperative transportation control.

[0010] In a possible implementation, the unmanned aerial vehicle cooperative power line anti-dancing spacer remote loading and unloading method further performs the following processing: wind speed trend analysis is performed according to the time-series wind speed data set, wind speed trend fitting is performed in a preset execution task time period, and a wind speed extreme value is established by using the wind speed trend fitting result; a fluctuation amplitude and a fluctuation frequency of the wind speed are obtained by using the wind speed trend fitting result; a wind speed stability index is calculated according to the wind speed extreme value, the fluctuation amplitude, and the fluctuation frequency; and wind speed stability index breaking analysis is performed by using the wind speed stability index calculation result.

[0011] In a possible implementation, the unmanned aerial vehicle cooperative power line anti-dancing spacer remote loading and unloading method further performs the following processing: if the wind speed stability index breaking analysis result is a pass result, a wind speed influence early warning instruction is generated; and environmental abnormality reporting is performed according to the wind speed influence early warning instruction.

[0012] The unmanned aerial vehicle cooperative power line anti-dancing spacer remote mounting and dismounting method provided in the application collects time sequence wind speed data and power line erection data and performs wind deflection dancing fitting, sets a wind speed stability index in combination with the unmanned aerial vehicle cooperative performance, performs wind speed stability index breakthrough analysis, establishes an unmanned aerial vehicle track route if it fails to pass, positions the first dismounting end of the anti-dancing spacer after the first unmanned aerial vehicle arrives at the target area, reconfigures a path in combination with real-time wind speed optimization approach control strategy, connects the first dismounting end and dismounts, and connects the second dismounting end after a threshold is met; and two unmanned aerial vehicles form a cooperative carrying group to transport the spacer. The technical problems of inaccurate positioning, poor operation stability and low dismounting success rate of a single unmanned aerial vehicle in a complex wind field environment due to power line dancing are solved, and the technical effect of realizing high-precision, safe and reliable mounting and dismounting of the power line anti-dancing spacer in a dynamic wind field is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings of the embodiments of the application will be briefly introduced below. The flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the foregoing or the following operations are not necessarily performed in sequence. On the contrary, various steps can be processed in reverse order or simultaneously according to needs. Meanwhile, other operations can be added to these processes, or a step or several steps can be removed from these processes.

[0014] Figure 1 The flowchart of the unmanned aerial vehicle cooperative power line anti-dancing spacer remote mounting and dismounting method provided for the embodiments of the present application.

[0015] Figure 2 The flowchart of the proximity control optimization strategy establishment in the unmanned aerial vehicle cooperative power line anti-dancing spacer remote mounting and dismounting method provided for the embodiments of the present application. DETAILED DESCRIPTION

[0016] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the embodiments of the present application can be implemented according to the content of the description, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described.

[0017] In order to make the purposes, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those skilled in the art without making creative efforts fall within the scope of protection of the present application.

[0018] In the following description, "some embodiments" are referred, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subset of all possible embodiments, and can be combined with each other without conflict, the term "first\second" referred to only distinguishes similar objects, and does not represent a specific order for the objects. The terms "include" and "have" and any variations, are intended to cover non-exclusive inclusion, for example, a process, method, product or server including a series of steps does not have to be limited to those clearly listed, but can include other steps not clearly listed or inherent to these processes, methods, products or devices, unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art belonging to the technical field of the present application. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0019] The embodiments of the present application provide a method for remotely installing and uninstalling a wire anti-dancing spacer cooperated by a UAV, as shown in the method, the method comprises: Figure 1

[0020] In step S100, wind speed data of a target area is collected, a time series wind speed data set is established, data of a wire erection of a target wire is synchronously acquired, wind deviation dancing fitting is performed according to the data of the wire erection, and a wind speed stability index is set by using a wind deviation dancing fitting result and a UAV cooperation performance.

[0021] ​Preferably, in the target power transmission line area where the anti-galloping spacer bar handling operation is planned to be carried out, sensors such as ultrasonic anemometers are deployed to collect wind speed data in real time, which may include measuring and recording wind speed and wind direction data to form a time-sequenced data set, i.e. a time-series wind speed data set, containing wind speed values corresponding to each time point; then the conductor erection data of the target power transmission line area is extracted from the power grid design and operation database, which usually includes conductor parameters such as type, diameter, unit length mass, tension, the distance between two adjacent towers, the suspension point height of the conductor on the tower, and the terrain features along the target conductor. Then, according to the conductor erection data, wind deviation galloping fitting is performed, i.e. computer simulation is performed using finite element models or multi-body dynamics models to simulate the static deviation and low-frequency, large-amplitude periodic oscillation of the conductor under specific wind speed and wind direction conditions, and then to predict the motion trajectory, amplitude and frequency of the conductor and the spacer bar installed thereon in the wind field, as the wind deviation galloping fitting result; finally, the wind speed stability index is set in combination with the wind deviation galloping fitting result and the UAV cooperative performance, wherein the UAV cooperative performance provides its own capability boundary information, including the wind resistance level, positioning accuracy, maneuverability, response speed of the UAV, and the accuracy and delay of multi-UAV cooperative control, etc., and the wind speed stability index may include one or more threshold indicators for determining whether the current or predicted wind condition is suitable for the UAV to safely and reliably perform cooperative operation, for example, the wind speed extreme value threshold is the maximum allowed average wind speed and gust wind speed set based on the wind resistance capability of the UAV, the wind fluctuation threshold is the maximum allowed wind speed change rate and fluctuation frequency set based on the response capability of the UAV control system, and the galloping amplitude and frequency threshold is the maximum allowed conductor galloping amplitude and frequency set based on the visual recognition and trajectory tracking accuracy of the UAV.

[0022] In step S200, the time-series wind speed data set is subjected to wind speed stability index breakthrough analysis based on wind speed extreme value and wind speed stability, and if the result is a fail result, a UAV trajectory route is established according to the conductor erection data.

[0023] Preferably, the wind speed stability index breakthrough analysis is used to determine whether the actual wind speed data exceeds the wind speed stability index set based on simulation and unmanned aerial vehicle performance, including wind speed extreme value analysis and wind speed stability analysis. Specifically, it is checked whether the maximum wind speed in the time series wind speed data set exceeds the maximum allowable wind speed threshold in the wind speed stability index, while it is checked whether the fluctuation of the wind speed, the change frequency, the standard deviation, etc. exceeds the wind speed stability tolerance in the wind speed stability index, thereby obtaining a binary decision analysis result, including pass and fail; if the result is fail, it means that the current wind condition is too severe, the risk of flying directly to the conductor operation point for loading and unloading operation is extremely high, and it is likely to fail or even cause the unmanned aerial vehicle to crash, so the obtained conductor erection data is called, based on the tower position, the conductor suspension point height, the span, etc. Data, plan a safe flight route from the starting point to the vicinity of the target operation area, usually away from the dancing conductor, possibly above the side of the conductor or other safe positions, so that the unmanned aerial vehicle can safely arrive and hover above the target area, until the wind speed stability index breakthrough analysis result becomes pass, then start working to improve the overall operation efficiency.

[0024] Further, step S200 further comprises step S210 of performing wind speed trend analysis according to the time series wind speed data set, performing wind speed trend fitting within a preset execution task time period, and establishing a wind speed extreme value using the wind speed trend fitting result; step S220 of obtaining a fluctuation amplitude and a fluctuation frequency of the wind speed using the wind speed trend fitting result; step S230 of performing wind speed stability index calculation according to the wind speed extreme value, the fluctuation amplitude, and the fluctuation frequency; and step S240 of performing wind speed stability index breakthrough analysis using the wind speed stability index calculation result.

[0025] Preferably, the wind speed trend analysis is performed on the time-series wind speed dataset, using moving average method, linear regression, etc. to fit the wind speed trend within a preset execution task time period, to filter out short-term random fluctuations and capture the overall change direction of the wind speed, obtain the wind speed trend fitting result, and predict the wind speed extreme value in this time period, representing the possible maximum wind speed in the future. Then, the original wind speed data of the time-series wind speed dataset is compared with the wind speed trend fitting result, a plurality of residuals are calculated as the fluctuation part of the wind speed deviating from its overall trend, and the root mean square of the residuals is calculated to quantify the intensity of wind speed fluctuations, determine the fluctuation amplitude, the larger the amplitude, the stronger the change in wind speed; the frequency domain analysis is performed on the plurality of residuals to quantify the frequency of wind speed fluctuations, the higher the frequency, the faster the wind speed switches; then, the wind speed stability index is calculated according to the wind speed extreme value, the fluctuation amplitude and the fluctuation frequency, which is used to comprehensively evaluate the severity and instability of the wind condition, i.e. the wind speed extreme value, the fluctuation amplitude and the fluctuation frequency are weighted and summed, wherein the weight is determined according to the historical data, the higher the wind speed extreme value, the larger the fluctuation amplitude, the higher the fluctuation frequency, the worse the wind speed stability index; finally, the wind speed stability index calculation result is used for wind speed stability index breakthrough analysis, i.e. the wind speed stability index is compared with the set wind speed stability index, if the wind speed stability index is better than the wind speed stability index, the result is passed, indicating that the wind condition is stable and the work is allowed; if the wind speed stability index is worse than the wind speed stability index, the result is failed, indicating that the wind condition is unstable or too severe to prohibit work, thereby greatly improving the safety and reliability of the wire anti-dancing spacer rod mounting and dismounting work.

[0026] Further, step S200 further includes step S250, if the wind speed stability index breakthrough analysis result is a pass result, generating a wind speed influence warning instruction; step S260, performing environmental abnormality reporting according to the wind speed influence warning instruction.

[0027] Preferably, if the wind speed stability index breakthrough analysis result is a pass result, it indicates that the current or predicted wind condition meets the minimum requirement of safe work, allowing mounting and dismounting work, but there may be potential risks that need to be highly vigilant, i.e. generating a wind speed influence warning instruction, entering an enhanced alert mode, identifying whether the wind speed is continuously jumping around the threshold value, whether the volatility is increasing, etc., and then performing environmental abnormality reporting according to the wind speed influence warning instruction, including sending prompt information to the operator or the upper monitoring, realizing risk grading management, and improving the efficiency of wire anti-dancing spacer rod mounting and dismounting under the premise of ensuring safety.

[0028] Step S300, when the first unmanned aerial vehicle reaches the target area along the unmanned aerial vehicle trajectory route, starting the visual detection unit to perform positioning of the first dismounting end of the anti-dancing spacer rod, and reconstructing the positioning trajectory path.

[0029] Preferably, after the first unmanned aerial vehicle reaches the target area according to the unmanned aerial vehicle track route generated according to the wire erection data, the visual detection unit is started to perform positioning of the first unloading end of the anti-dancing spacer, that is, the high-definition camera and the laser radar / deep sensor and other visual perception devices carried by the unmanned aerial vehicle are activated, the first unloading end of the anti-dancing spacer that needs to be connected or detached is quickly identified and accurately positioned through a pre-trained visual model and feature matching, the accurate three-dimensional coordinates and attitude angle of the target relative to the unmanned aerial vehicle are calculated through stereoscopic vision or laser ranging, and finally the path planning is performed with the current preparation position of the first unmanned aerial vehicle as the starting point and the first unloading end position of the anti-dancing spacer positioned by the visual detection unit as the end point, that is, the positioning trajectory path is reconstructed, and then the accurate tracking target is provided for proximity control optimization.

[0030] In step S400, real-time wind speed data is read, proximity control optimization is performed according to the real-time wind speed data and the positioning trajectory path, and proximity control optimization strategy is established.

[0031] Further, as shown in Figure 2 step S400, step S400 further includes step S410 of establishing a real-time state space, step S420 of performing short-term trend prediction of wind speed according to the real-time state space to establish a short-term trend prediction result, step S430 of performing crosswind bias compensation of the positioning trajectory path by using the short-term trend prediction result to establish a pre-compensation parameter, and step S440 of performing hierarchical proximity control optimization based on the real-time state space and the pre-compensation parameter after setting a cost function to establish a proximity control optimization strategy.

[0032] Preferably, the real-time wind speed sequence is the wind speed / wind direction data in the recent period of time, which is used to analyze the current mode and short-term trend of the wind, the positioning trajectory path is a dynamic three-dimensional path that needs to be accurately tracked by the unmanned aerial vehicle, and the position and attitude data of the first unmanned aerial vehicle refer to its own real-time state, including three-dimensional coordinates, pitch / roll / yaw angle attitude and corresponding angular velocity and linear velocity. The real-time wind speed sequence, the positioning trajectory path and the position and attitude data of the first unmanned aerial vehicle are integrated into a real-time state space. Then, the short-term trend prediction of wind speed is performed according to the real-time state space, including using Kalman filtering, ARIMA model and other time series prediction algorithms to predict the wind speed and wind direction based on the real-time wind speed sequence in the real-time state space, and outputting the short-term trend prediction result to predict the change of the wind in a short time window in the future.

[0033] Preferably, the wind will generate a lateral thrust on the UAV, causing it to deviate from the predetermined path, and the short-term trend prediction result is used to compensate for the lateral wind bias of the positioning trajectory path, that is, according to the predicted wind speed trend, the expected interference force that the wind will generate on the UAV is calculated, and then according to the UAV dynamics model, the control instruction correction amount that the UAV needs to make in advance to offset the expected interference force is calculated, for example, how much roll angle needs to be increased in advance to generate a lateral force to counteract the wind force, and then the pre-compensation parameter is determined; then a cost function is defined by comprehensively considering the trajectory deviation, attitude stability, energy consumption, safety margin, and operation completion time, which is used to evaluate the pros and cons of potential flight paths, and based on the real-time state space and the pre-compensation parameter, a hierarchical approach control optimization is performed, specifically, the entire approach process is divided into different stages such as long, medium, and short ranges according to the distance, and in different stages, the weights of various indicators in the cost function are different, for example, in the long-range stage, energy consumption and time are more important, and in the short-range stage, trajectory deviation and safety margin are extremely important, then the real-time state space is taken as the current condition, and the pre-compensation parameter is taken as the feedforward input, among the multiple possible future flight paths, a path that makes the cost function take the minimum value is searched and selected as the optimal path through model predictive control, and then the approach control optimization strategy is output, that is, the optimal control instruction set at the current time is output and sent to the flight control system of the UAV for execution, so that the UAV can complete the flight operation task with extremely high precision in an extremely complex and dynamic environment.

[0034] Further, step S440 further includes step S441 of configuring a path hierarchy according to the real-time wind speed data and the positioning trajectory path, the path hierarchy including a long-range segment layer, a medium-range segment layer, and a short-range segment layer; step S442 of configuring weight of evaluation items of the cost function by using the path hierarchy, the evaluation items of the cost function including a wind speed disturbance suppression cost item, a trajectory deviation cost item, an attitude stability cost item, an energy consumption cost item, a task safety margin cost item, and a time response cost item; and step S443 of taking the real-time state space and the pre-compensation parameter as initial constraint conditions, and performing hierarchical approach control optimization according to the path hierarchy and the mapped cost function.

[0035] Preferably, the path hierarchy is configured adaptively according to the real-time wind speed data and the positioning trajectory path, and the final approach path is automatically divided into a long-range segment layer, a medium-range segment layer, and a short-range segment layer, wherein the UAV is relatively far from the target in the long-range segment layer, and the core target is to approach the target area quickly and energy-efficiently; the UAV enters the target vicinity in the medium-range segment layer, and the core target is to adjust the attitude and accurately align; the UAV is about to contact the target in the short-range segment layer, and the core target is to achieve extreme precision and absolute safety to ensure smooth and reliable docking; and the distance threshold of the hierarchy can be adjusted according to the dynamic characteristics of the real-time wind speed data and the positioning trajectory path, for example, the distance threshold is increased when the wind is strong, and the short-range segment is lengthened when the target shakes violently.

[0036] Preferably, the evaluation term weight of the cost function is configured by path layering, and the evaluation term of the cost function includes a wind speed disturbance suppression cost term, a trajectory deviation cost term, a posture stability cost term, an energy consumption cost term, a task safety margin cost term, and a time response cost term, wherein the wind speed disturbance suppression cost term punishes deviation caused by wind, the trajectory deviation cost term punishes deviation from the preset path, the posture stability cost term punishes shaking of the UAV body, the energy consumption cost term punishes high energy consumption operation, the task safety margin cost term punishes too close to obstacles, and the time response cost term punishes slow action. The evaluation term weight configuration of the cost function is shown in Table 1:

[0037] Table 1: Evaluation term weight distribution data table of cost function

[0038]

[0039] Preferably, the real-time state space and the pre-compensation parameter are used as initial constraint conditions, and the hierarchical approaching control optimization is performed according to the path layering and the cost function mapping. Specifically, the real-time state space and the pre-compensation parameter are used as the calculation starting point and the physical limit that must be followed, and then the real-time distance is used to determine whether the UAV is currently in the long-range segment layer, the medium-range segment layer, or the short-range segment layer and to call the corresponding evaluation term weight. The model predictive control is used to simulate a large number of possible flight paths in a short future time window, and the cost function with the configured evaluation term weight is used to score each flight path. The flight path with the minimum cost function value is the highest score, and then the control instruction sequence corresponding to the path is output to the UAV for execution.

[0040] In step S500, after the first UAV is controlled to execute the first unloading end connection by using the approaching control optimization strategy, the unloading operation is performed, and when the unloading state meets the preset unloading threshold, the second UAV is controlled to connect the second unloading end.

[0041] Preferably, the first unmanned aerial vehicle operates as the leading unmanned aerial vehicle, uses the proximity control optimization strategy containing wind disturbance resistance and high-precision flight control instructions to control the first unmanned aerial vehicle to fly accurately and make the end execution mechanism of the first unmanned aerial vehicle physically connected with the first unloading end, wherein the first unloading end is a connection point of the anti-dancing spacer, after confirming the reliable connection of the first unloading end, the first unmanned aerial vehicle starts to perform the unloading or installation operation, which may be loosening a locking bolt, releasing a locking pin, releasing a connection mechanism or preliminarily fixing and bearing the weight of the spacer to change the connection state of the spacer and the power line; the unloading state refers to the state after the connection and operation of the first unloading end are completed, which is quantified through vision, force sensor, position sensor, current sensor, etc., the preset unloading threshold is a quantification standard for successful completion defined in advance, for example, mechanical threshold, displacement threshold, visual threshold, etc., when the unloading state meets the preset unloading threshold, a start instruction is sent to the second unmanned aerial vehicle to control the second unmanned aerial vehicle to connect the second unloading end, that is, the second unmanned aerial vehicle starts to fly to the other connection point of the spacer and performs the same accurate connection operation as the first unmanned aerial vehicle, so as to avoid the collision risk and unstable state of two unmanned aerial vehicles operating at the same time, thereby greatly improving the reliability, safety and success rate of the complex cooperative operation of the unmanned aerial vehicle.

[0042] Step S600: After the first unloading end and the second unloading end are unloaded in turn, a cooperative transportation group composed of the first unmanned aerial vehicle and the second unmanned aerial vehicle is formed to perform remote transportation of the anti-dancing spacer.

[0043] Step S600 further includes the following steps: S610, when the unloading state of the first unloading end meets the preset unloading threshold, a connection instruction is activated synchronously; S620, based on the connection instruction, the first unmanned aerial vehicle controls the unloading transportation assembly to perform the active connection of the anti-dancing spacer; S630, after the second unmanned aerial vehicle completes the active connection and performs the unloading of the second unloading end, a cooperative transportation group composed of the first unmanned aerial vehicle and the second unmanned aerial vehicle is formed to perform cooperative transportation control of the anti-dancing spacer.

[0044] Preferably, when the unloading state of the first unloading end meets the preset unloading threshold, it indicates that the first unmanned aerial vehicle has successfully completed the disassembly operation on the first unloading end of the anti-dancing spacer, and a connection instruction is generated to control the unloading and transportation assembly of the first unmanned aerial vehicle to perform active connection of the anti-dancing spacer, wherein the unloading and transportation assembly is a multifunctional end effector carried by the first unmanned aerial vehicle, which can not only perform disassembly / installation operation, but also has the connection function required for transportation, such as complex mechanical devices integrating wrench, clamping jaw, lock catch, etc.; the active connection of the anti-dancing spacer refers to a connection mode allowing relative motion freedom within a certain range, such as spherical hinge connection, universal joint or jointed connecting arm, wherein it is impossible for two unmanned aerial vehicles to be completely synchronized and absolutely stationary in flight, and if rigid connection is adopted, the small attitude difference and relative motion between the unmanned aerial vehicles will generate huge internal force at the connection point, which is easy to damage the equipment or cause loss of control, and the active connection acts as a buffer joint to ensure the stability and safety of the cooperative transportation process. Similarly, after the second unmanned aerial vehicle completes the active connection and performs the unloading of the second unloading end, the first unmanned aerial vehicle and the second unmanned aerial vehicle form a cooperative transportation group to perform cooperative transportation control of the anti-dancing spacer, including generating a common flight path, i.e. planning a flight route for transporting the anti-dancing spacer to the target location, and ensuring that the lift provided by the two unmanned aerial vehicles can stably bear the weight of the spacer together, while coordinating the flight attitude and speed of the two unmanned aerial vehicles as much as possible to reduce swinging and achieve stable transportation.

[0045] Further, step S630 further includes step S631 of reconstructing a control target body by the first unmanned aerial vehicle, the second unmanned aerial vehicle, the anti-dancing spacer and the active connection component; step S632 of reconstructing a taboo space according to the conductor erection data and current wind speed data; step S633 of performing homeward path planning by using the control target body and the taboo space to establish a homeward path planning result; and step S634 of dynamically switching the master control machine and the follower control machine of the first unmanned aerial vehicle and the second unmanned aerial vehicle according to real-time tension difference and attitude offset along the homeward path planning result to complete cooperative transportation control.

[0046] Preferably, the first unmanned aerial vehicle, the second unmanned aerial vehicle and the anti-dancing spacer are regarded as a whole constituted by the active connection component to reconstruct a virtual control object as the control target body, which has a dynamic model and a motion state, and calculates the motion speed and orientation of the control target body, and then decomposes the control instruction to the two unmanned aerial vehicles; and then the taboo space is reconstructed according to the conductor erection data and current wind speed data, wherein the conductor erection data provides static taboo space to clearly indicate the position and height of the power transmission line and the tower, and the transportation path must be away from the inherent obstacles to maintain a safe distance; and the current wind speed data provides dynamic taboo space, and strong wind will blow the spacer and the unmanned aerial vehicle to increase the swinging range, and the dynamic swinging envelope range is predicted according to the current wind condition and added to the taboo space.

[0047] Preferably, the homing path planning is performed by using the control target ontology and the taboo space, that is, an optimal safe path from the current high-altitude conductor position to the final ground maintenance destination is planned, it is ensured that the entire control target ontology and its dynamic swing range do not touch the taboo space throughout the path, and then the homing path planning result is determined; then, according to the real-time tension difference and the attitude offset, the control roles of the master control machine and the follower of the first unmanned aerial vehicle and the second unmanned aerial vehicle are dynamically switched along the homing path planning result, wherein, during the transportation process, the influence of wind or the slight change of the center of gravity will cause the two unmanned aerial vehicles to be unevenly stressed, resulting in a tension difference, and the attitudes are out of synchronization, resulting in an attitude offset, wherein the tension difference reflects whether the load distribution is balanced, and the attitude offset reflects whether the flight is synchronized, and then a dynamic role switching strategy is adopted, the master control machine is responsible for tracking the global path and deciding where and how fast to fly, and the follower is responsible for maintaining the formation mode and adjusting itself according to the relative position relationship with the master control machine to maintain a stable transportation attitude; the tension difference and the attitude offset of the suspension points of the two unmanned aerial vehicles are monitored in real time, for example, if it is found that the tension of the first unmanned aerial vehicle is too large and the attitude is unstable, it means that the first unmanned aerial vehicle is bearing more wind resistance or more weight, and the control performance is decreased, so the roles are immediately switched, that is, the second unmanned aerial vehicle with better control performance is made to serve as the master control machine, and the first unmanned aerial vehicle is switched to the follower, through the dynamic switching of the collaborative transportation control, it is ensured that the unmanned aerial vehicle with better state and larger control margin always assumes the leading responsibility, thereby greatly enhancing the robustness and self-adaptability of the entire transportation under disturbance.

[0048] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application. In some cases, the actions or steps described in the present application can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

Claims

1. A method for remote installation and removal of wire anti-hunting spacer by drone cooperation, characterized in that, The method comprises: Performing wind speed data collection of the target area, establishing a time-series wind speed dataset, synchronously acquiring conductor erection data of the target conductor, performing windage oscillation fitting according to the conductor erection data, and setting a wind speed stability index by using the windage oscillation fitting result and the UAV cooperative performance; Performing wind speed stability index breakthrough analysis on the time-series wind speed dataset based on wind speed extreme value and wind speed stability, and establishing a UAV trajectory route according to the conductor erection data if the result is a failure result; After the first UAV reaches the target area along the UAV trajectory route, starting a visual detection unit to perform positioning of the first unloading end of the anti-oscillation spacer, and reconstructing a positioning trajectory path; Reading real-time wind speed data, performing proximity control optimization according to the real-time wind speed data and the positioning trajectory path, and establishing a proximity control optimization strategy; After the first UAV is controlled to perform connection of the first unloading end by using the proximity control optimization strategy, performing unloading operation, and controlling the second UAV to connect the second unloading end when the unloading state of the first unloading end meets a preset unloading threshold; After sequentially performing unloading of the first unloading end and the second unloading end, forming a cooperative transportation group by the first UAV and the second UAV, and performing remote transportation of the anti-oscillation spacer.

2. The method of claim 1, wherein the method further comprises: The proximity control optimization according to the real-time wind speed data and the positioning trajectory path comprises: Establishing a real-time state space, wherein the real-time state space comprises a real-time wind speed sequence, a positioning trajectory path, and position and attitude data of the first UAV; Performing short-term trend prediction of wind speed according to the real-time state space, and establishing a short-term trend prediction result; Performing side wind bias compensation of the positioning trajectory path by using the short-term trend prediction result, and establishing a pre-compensation parameter; After setting a cost function, performing hierarchical proximity control optimization based on the real-time state space and the pre-compensation parameter, and establishing a proximity control optimization strategy.

3. The method of claim 2, wherein the method further comprises: The hierarchical proximity control optimization after setting the cost function comprises: Adaptively configuring path hierarchy according to the real-time wind speed data and the positioning trajectory path, wherein the path hierarchy comprises a remote segment layer, a middle-distance segment layer, and a short-distance segment layer; Configuring weight of an evaluation item of the cost function by using the path hierarchy, wherein the evaluation item of the cost function comprises a wind speed disturbance suppression cost item, a trajectory deviation cost item, an attitude stability cost item, an energy consumption cost item, a task safety margin cost item, and a time response cost item; Taking the real-time state space and the pre-compensation parameter as initial constraint conditions, and performing hierarchical proximity control optimization according to the path hierarchy and the mapped cost function.

4. The drone coordinated wire anti-hunting spacer remote installation and removal method of claim 1, wherein, The remote transportation of the anti-oscillation spacer after sequentially performing unloading of the first unloading end and the second unloading end comprises: Synchronously activating a connection instruction when the unloading state of the first unloading end meets a preset unloading threshold; Controlling an unloading transportation assembly of the first UAV to perform active connection of the anti-oscillation spacer based on the connection instruction; When the second unmanned aerial vehicle completes the active connection and performs the second unloading end unloading, a cooperative transportation group composed of the first unmanned aerial vehicle and the second unmanned aerial vehicle is formed to perform cooperative transportation control of the anti-dancing spacer.

5. The method of claim 4, wherein the method further comprises: The cooperative transportation control of the anti-dancing spacer performed by the cooperative transportation group composed of the first unmanned aerial vehicle and the second unmanned aerial vehicle includes: The control target body is reconfigured by the first unmanned aerial vehicle, the second unmanned aerial vehicle, the anti-dancing spacer, and the active connection component; The taboo space is reconfigured according to the conductor erection data and the current wind speed data; The homeward path planning result is established by performing homeward path planning using the control target body and the taboo space; The control roles of the master control machine and the follower of the first unmanned aerial vehicle and the second unmanned aerial vehicle are dynamically switched according to the real-time tension difference and the attitude offset along the homeward path planning result to complete the cooperative transportation control.

6. The drone coordinated wire anti-hunting spacer remote installation and removal method of claim 1, wherein, The wind speed stability index breakthrough analysis based on the wind speed extreme value and the wind speed stability includes: The wind speed trend analysis is performed according to the time series wind speed data set, the wind speed trend fitting is performed within a preset execution task time period, and the wind speed extreme value is established using the wind speed trend fitting result; The fluctuation amplitude and the fluctuation frequency of the wind speed are obtained using the wind speed trend fitting result; The wind speed stability index is calculated according to the wind speed extreme value, the fluctuation amplitude, and the fluctuation frequency; The wind speed stability index breakthrough analysis is performed using the wind speed stability index calculation result.

7. The drone coordinated wire anti-hunting spacer remote installation and removal method of claim 1, wherein, The wind speed stability index breakthrough analysis based on the wind speed extreme value and the wind speed stability further includes: If the wind speed stability index breakthrough analysis result is a pass result, a wind speed influence early warning instruction is generated; The environmental abnormality is reported according to the wind speed influence early warning instruction.

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