电力线激光点云的分割及安全检测研究

Segmentation of laser point cloud and safety detection of power lines

为了进行高压输电线路安全检测分析,基于机载激光雷达(LiDAR)电力走廊数据,提出了一种基于密度的空间聚类方法(DBSCAN)的电力线激光点云单条分割提取算法。通过该方法可以实现输电走廊中单条电力线的快速分割提取。首先对电力线点云在x-O-y平面上投影,对投影后的激光点采用最小二乘法进行直线拟合;其次通过计算输电走廊长度,采用经验参量进行电力线点云分段;再次对分段点云在投影平面内进行DBSCAN聚类;最后将分段聚类结果类别归一化,得到单条电力线激光点云数据。结果表明,采用该方法能够在只需经验参量分段宽度的情况下,快速准确地对电力线激光点云进行分割提取,并根据分割结果进行电力线与电力走廊地物距离计算,判断危险点类型及距离。所提出的方法具有较高的提取与测量精度,能够有效地应用于电力线安全检测分析。

In order to detect and analyze the safety of high voltage transmission lines, based on airborne light detection and rangring(LiDAR) power corridor data, a segmentation and extraction algorithm of power line laser point cloud was proposed based on density-based spatial clustering of applications with noise (DBSCAN). This method can realize fast segmentation and extraction of single power line in transmission corridor. Firstly, the point cloud of power line was projected on the x-O-y plane. The projected laser points were fitted linearly by the least square method. Secondly, after calculating the length of transmission corridor, empirical parameters were used to segment power line point clouds. Then, DBSCAN was applied to segment point clouds in the projection plane. Finally, the classification of segmentation clustering results was normalized and the laser point cloud data of a single power line was obtained. The results show that, with this method, fast and accurate segmentation and extraction of power line laser point cloud can be obtained when the piecewise width of the empirical parameter is only needed. According to the segmentation results, the distance between the power line and the objects in the power corridor is calculated and the type and distance of dangerous points can be judged. By comparing and verifying the experiment with the field measurement results, the proposed method has high extraction and measurement accuracy. It can be effectively applied to power line safety detection and analysis.