A method of power line fast extraction based on UAV LiDAR point cloud
In order to change the drawbacks of low efficiency in traditional manual inspection of long-distance power lines,improve production efficiency,and meet the needs of intelligent management of power grids,this paper is based on airborne LiDAR point cloud data,adopts the agglomerative clustering algorithm,uses C language programming to achieve rapid and accurate extraction of power line point clouds,and verifies through examples.The results show that the accuracy of the agglomerative clustering algorithm in extracting power line point clouds is 99.99％,the minimum fitting residual of the lightning line is 0.11 m,the minimum fitting residual of the power line is 0.19 m,the maximum fitting residual is 0.21 m,and the average fitting residual is 0.20 m.The automated implementation process of the algorithm can improve the inspection efficiency of power lines and obtain better test results.
LiDAR point cloudagglomerative clusteringpower line3D reconstructionaccuracy evaluation
NETL
NSTL
万方数据
维普
