CN-121979247-A - Group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method and system

CN121979247ACN 121979247 ACN121979247 ACN 121979247ACN-121979247-A

Abstract

The invention relates to the technical field of particle swarm optimization, and provides a group-intelligence-based power transmission line unmanned aerial vehicle routing inspection path planning method and system, wherein the method comprises the steps of collecting three-dimensional point cloud data along a power transmission line, and identifying line tower point clouds and line point clouds; and establishing a patrol objective function by combining the position relation between adjacent track points and the distances between the track points and the points of the line tower point cloud and the line point cloud, and acquiring a path planning result of the unmanned aerial vehicle patrol of the power transmission line according to the patrol objective function. The invention can improve the safety of the path planning result.

Inventors

KONG XIANGCHEN
LI XINYANG
Qin sanying
ZHENG DONGFANG
XUE SHUNCHENG
XU ZHIWEN
LIU SHUWEI
Kuang cong
CHEN BIN
Jia Aohui

Assignees

国网河南省电力公司商丘供电公司

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (10)

1. The power transmission line unmanned aerial vehicle routing inspection path planning method based on group intelligence is characterized by comprising the following steps of: three-dimensional point cloud data along the transmission line are collected, and line tower point clouds and line point clouds are identified from the three-dimensional point cloud data; Calculating a first electric field influence factor of the patrol road section according to the distances between adjacent track points forming the patrol road section and the line tower point cloud and the line point cloud, carrying out voxelization processing on three-dimensional point cloud data, calculating density characteristic values of voxel grids, determining a reference path of the patrol road section according to the included angle between the direction of vectors determined by the adjacent track points forming the patrol road section and preset different selected paths, calculating a second electric field influence factor of the patrol road section according to the position relation between the reference path of the patrol road section and the adjacent track points corresponding to the patrol road section, and obtaining the electric field influence degree of the patrol road section according to the first electric field influence factor, the second electric field influence factor and the density characteristic values of all voxel grids passed by the patrol road section; And establishing a patrol objective function according to the position relation between the adjacent track points, the distances between the track points and the point clouds of the line tower and the line point clouds and the electric field influence degree of all the patrol road sections, and acquiring a path planning result of the unmanned aerial vehicle patrol of the power transmission line according to the patrol objective function.
2. The group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method according to claim 1, wherein the specific acquisition method of the first electric field influence factor of the routing inspection road section is as follows: The minimum value of Euclidean distance between the track point and the midpoint of the point cloud of all the line towers is recorded as the line tower collision distance of the track point, and the minimum value of Euclidean distance between the track point and the midpoint of the point cloud of all the line towers is recorded as the line collision distance of the track point; Taking the difference value of the line collision distance between the end point and the starting point of the inspection road section as a numerator, taking the difference value of the line tower collision distance between the end point and the starting point of the inspection road section as a denominator, and taking the value of the denominator as a first electric field influence factor of the inspection road section.
3. The group intelligent-based power transmission line unmanned aerial vehicle routing path planning method according to claim 1, wherein the method for determining the density characteristic value of the voxel grid is as follows: and recording the number of the line tower point clouds and the line point clouds contained in the voxel grid and the ratio of the number of the points in the line point clouds to the number of the points in the three-dimensional point cloud data contained in the voxel grid as a density characteristic value of the voxel grid.
4. The group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method according to claim 1, wherein the specific acquisition method of the reference path of the routing inspection road section is as follows: According to the routing inspection direction of the adjacent track points, directional vectors of the adjacent track points are established, directional unit vectors of each preset selection path are established, and the selection path corresponding to the directional unit vector with the smallest included angle between the directional vectors of the adjacent track points is used as a reference path of the routing inspection road section determined by the adjacent track points.
5. The group intelligent-based power transmission line unmanned aerial vehicle routing path planning method according to claim 4, wherein the preset selection path comprises: a selection path from one crossarm to another, a selection path from a distance to a crossarm and from again to the crossarm, a selection path for vertical downward tour, a selection path for vertical upward tour, a selection path for diagonal downward tour, and a selection path for diagonal upward tour.
6. The group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method according to claim 1, wherein the specific calculation method of the second electric field influence factor of the routing inspection road section is as follows: Establishing a first fitting curve of the electric field strength with respect to the distance between each position on the reference path and the starting point in the adjacent track point of the determined patrol road section, dividing the patrol road section into patrol sub road sections according to the inflection point of the fitting curve, and calculating the comprehensive relative influence degree of the patrol road section according to the increase or decrease of the curve sections corresponding to all the patrol sub road sections divided by the patrol road section on the fitting curve; Recording the slope of the point with the minimum Euclidean distance between the reference path and the track point on the first fitting curve as the reference slope of the track point; And recording the total relative influence degree of the patrol road section and the positive correlation processing result of the first mean value as a second electric field influence factor of the patrol road section.
7. The group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method according to claim 6, wherein the specific acquisition method of the comprehensive relative influence degree of the routing inspection road section is as follows: When the curve section corresponding to the patrol sub-section on the fitting curve is monotonically increased, marking the normalized value of the length of the patrol sub-section as the relative influence degree of the patrol sub-section; when the curve section corresponding to the patrol sub-section on the fitting curve is monotonically decreasing, marking the normalized value of the opposite number of the length of the patrol sub-section as the relative influence degree of the patrol sub-section; and (3) marking the accumulated sum of the relative influence of all the patrol sub-sections divided by the patrol section as the comprehensive relative influence of the patrol section.
8. The group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method according to claim 1, wherein the specific acquisition method of the electric field influence degree of the routing inspection road section is as follows: The method comprises the steps of marking the sum of the normalized value of a first electric field influence factor of a patrol road section and the density characteristic value of all voxel grids passed by the patrol road section as a first sum of the patrol road section, and marking the product of the first sum of the patrol road section and a second electric field influence factor as the electric field influence degree of the patrol road section.
9. The group intelligent-based power transmission line unmanned aerial vehicle routing path planning method according to claim 1, wherein the routing objective function is: the weighted sum of the distance cost, the collision cost, the electric field influence cost and the penalty function; the distance cost is the accumulated sum of the lengths of the inspection road sections formed by all the adjacent track points; the electric field influence cost is the sum of the electric field influence values of all the inspection road sections; The collision cost is determined according to minimum Euclidean distances between the track points and the line tower point cloud and between the track points and all points in the line point cloud; the penalty function is determined based on the steering angle of the track point location.
10. A group intelligence based power line unmanned aerial vehicle routing planning system comprising a memory, a processor and a computer program stored in the memory and running on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1-9 when executing the computer program.

Description

Group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method and system Technical Field The invention relates to the technical field of particle swarm optimization, in particular to a power transmission line unmanned aerial vehicle routing inspection path planning method and system based on swarm intelligence. Background The fixed line unmanned aerial vehicle is used for carrying out transmission line inspection, the equipment health condition cannot be responded dynamically, and the missed inspection of key components can occur. The unmanned aerial vehicle inspection path of the power transmission line is subjected to scientific path planning, so that safety can be guaranteed, inspection efficiency is improved, and cost is reduced. In the process of realizing the unmanned aerial vehicle routing inspection path planning of the power transmission line, different constraints are set, so that the existence of enough safe distance between the routing inspection line and the obstacle in the routing inspection environment can be ensured, the routing inspection targets are contained in the planned path, and the total routing inspection distance is short. However, the power transmission line can generate high-voltage electric fields with different influence degrees at different positions in the surrounding space, and the influence is not considered in the process of realizing the unmanned aerial vehicle routing inspection path planning of the power transmission line, so that the problem of insufficient safety of a path planning result is easily caused. Disclosure of Invention The invention provides a group intelligent-based power transmission line unmanned aerial vehicle routing inspection path planning method and system, which are used for solving the problem that the influence of a high-voltage electric field generated by a power transmission line is not considered in the unmanned aerial vehicle routing inspection path planning process, and the safety of a path planning result is influenced, and the adopted technical scheme is as follows: in a first aspect, an embodiment of the present invention provides a group intelligence-based power transmission line unmanned aerial vehicle routing inspection path planning method, including the steps of: three-dimensional point cloud data along the transmission line are collected, and line tower point clouds and line point clouds are identified from the three-dimensional point cloud data; Calculating a first electric field influence factor of the patrol road section according to the distances between adjacent track points forming the patrol road section and the line tower point cloud and the line point cloud, carrying out voxelization processing on three-dimensional point cloud data, calculating density characteristic values of voxel grids, determining a reference path of the patrol road section according to the included angle between the direction of vectors determined by the adjacent track points forming the patrol road section and preset different selected paths, calculating a second electric field influence factor of the patrol road section according to the position relation between the reference path of the patrol road section and the adjacent track points corresponding to the patrol road section, and obtaining the electric field influence degree of the patrol road section according to the first electric field influence factor, the second electric field influence factor and the density characteristic values of all voxel grids passed by the patrol road section; And establishing a patrol objective function according to the position relation between the adjacent track points, the distances between the track points and the point clouds of the line tower and the line point clouds and the electric field influence degree of all the patrol road sections, and acquiring a path planning result of the unmanned aerial vehicle patrol of the power transmission line according to the patrol objective function. Further, the specific method for acquiring the first electric field influence factor of the inspection road section comprises the following steps: The minimum value of Euclidean distance between the track point and the midpoint of the point cloud of all the line towers is recorded as the line tower collision distance of the track point, and the minimum value of Euclidean distance between the track point and the midpoint of the point cloud of all the line towers is recorded as the line collision distance of the track point; Taking the difference value of the line collision distance between the end point and the starting point of the inspection road section as a numerator, taking the difference value of the line tower collision distance between the end point and the starting point of the inspection road section as a denominator, and taking the value of the denominator as a first electric field influence factor of the inspection road