为了解决目前复杂环境下电力线提取精度及鲁棒性低的问题，提出了一种基于激光点云的电力线自动提取方法。通过主成分分析确定输电线路的主方向，将长距离输电走廊划分为多个空间网格，以应对地形起伏变化时植被点云对提取算法的干扰；再通过一种自顶向下的全新滤波算法剔除每个空间网格的地物点，根据点云密度分布差异实现电力线和电塔的自动分离；另外,提出半径搜索算法对分离后的结果进行处理，得到单条电力线的激光点云数据。结果表明，所提出的方法对电力线的提取精度高达99.69%，针对不同连接塔型和不同地形都具有很好的鲁棒性。该研究在输电通道空间结构的自动分析领域以及智能巡检领域具有良好的工程应用价值。

In order to solve the problem of low accuracy and robustness of power line extraction in complex environment, an automatic power line extraction method based on laser point cloud was proposed. The main direction of transmission line was determined by principal component analysis, and the long distance transmission corridor was divided into several spatial grids to deal with the disturbance of vegetation point clouds on the extraction algorithm when the terrain changes. Then a new top-down filtering algorithm was used to eliminate the object points in each spatial grid, and the automatic separation of power lines and towers was realized according to the difference of point cloud density distribution. In addition, a radius search algorithm is proposed to process the separated results and obtain the laser point cloud data of a single power line. The results show that the proposed method has a high accuracy of 99.69%. It has good robustness for different connection tower types and different terrain. This research has good engineering application value in the field of automatic analysis of transmission channel spatial structure and intelligent patrol inspection.