机载激光雷达数据中电力线的快速提取

Study on power line fast extraction based on airborne LiDAR data

针对当前机载LiDAR技术在电力巡线应用中对电力线数字模型高精度和快速重建的需求,该文提出一种高效的电力线点云分类方法。首先基于局部范围点的高程统计直方图,实现电力线点的快速粗提取;然后运用随机抽样一致性算法剔除残留的电塔点,结合点云高程统计进一步剔除绝缘子点,实现电力线点的精提取;最后利用同一垂直面内电力线点的高程分布特性,实现单根电力线点的快速提取。基于实际输电线路机载LiDAR数据的实验结果表明,该方法可实现电力线点的快速、高精度提取:粗分类后的电力线点中仅含约10%的非电力线点;精分类后约有2%的电力线点被误分为绝缘子点,最终各条电力线点的提取比率平均为98%以上。

Nowadays, airborne LiDAR technology has been widely used in power patrol operation, and it usually requires an accurate power line digital model from raw point cloud data immediately when the flight mission is over. This paper proposed an efficient and accurate method for power line extraction from airborne LiDAR data. Firstly, the point clouds of power lines were filtered from raw data roughly and fast by using a height histogram statistical analysis. Secondly, the RANSAC algorithm was used to separate the power line point clouds accurately, while the insulator points were removed by using the elevation statistical method. Finally, the separated power lines were achieved according to the elevation difference of the power lines. Experimental results showed that this method has high accuracy and efficiency; there are 10% noisy points in power lines after the coarse filter, and about 2% powerline points are lost when removing insulator＇s points; the average rate of power line points extraction is over 98%.