提出了一种基于机载LiDAR点云数据的电力线自动提取方法。先对LiDAR数据进行空间网格划分;再依据电力线在三维空间中的水平分布特性,利用改进的欧氏聚类实现电力线粗提取;采用电力线与电力塔的相连性,估算出电力塔顶端的空间坐标位置;使用改进的欧氏聚类实现单根电力线提取,利用直线和抛物线相结合的模型求解单根电力线的中心线方程及其半径;最后根据电力线方程和半径自适应生长电力线于绝缘子处,并得到单根电力线的完整点云。实验结果表明,对比于支持向量机(SVM)结合几何特征方法的分类效果,所提方法可自动、快速和精确地从电力巡线数据中提取完整的电力线,对电力巡线具有一定的应用价值。

In this work, an automatic power line extraction method based on airborne LiDAR point cloud data is proposed. First, spatial partitioning of LiDAR data was performed. Second, according to the horizontal distribution characteristics of power lines in three-dimensional space, an improved Euclidean clustering algorithm was used to realize rough extraction of the power lines. Third, using the connection between a power line and a power tower, the spatial coordinate position at the top of the power tower was estimated. Then, the improved Euclidean clustering algorithm was used to realize single power line extraction, and the model was used to combine a straight line and parabola to obtain the centerline equation of a single power line and its radius. Finally, a power line adapter was developed at the insulator according to the power line equation and radius, and the complete point cloud of a single power line was obtained. Experiment results show that compared with the classification effect of support vector machines combined with the geometric feature method, the proposed method can extract complete power lines automatically, quickly, and accurately from power line inspection data, which has application value in power patrol.