基于点云数据特征的电力线快速提取和重建

为了解决电力线点云可能存在交跨线点云较难处理、绝缘子点云较难分割、现有算法模型研究不完整问题,采用了基于点云数据特征的电力线快速提取和重建方法,首先通过输电线路体素栅格高程特征进行点云快速粗分类,然后运用随机一致性算法进行点云快速精化,采用顾及交跨线的滤波算法高效准确提取电力线点云,针对电力线局部线性模型分割出绝缘子,最后采用局部加权质心的方式提取电力线关键点,实现电力线的快速重建,并进行了理论分析和实验验证,取得了较好的实验结果。结果表明,电力线提取与重建综合准确率95.3%,总体耗时2.5s以内,验证了算法的快速性、准确性和鲁棒性。这一结果对电力线点云提取和重建有一定帮助。

Fast extraction and reconstruction of power line based on point cloud data features

In order to solve the problem that point clouds of intersecting and crossing lines may be difficult to deal with, insulator point clouds are difficult to be segmented, and the existing algorithm models are incomplete, fast extraction and reconstruction method of power line based on point cloud data features was adopted. Firstly, fast rough classification of point clouds was carried out based on voxel grid elevation characteristics of transmission lines. Then point cloud was refined rapidly by using random consistency algorithm. Point cloud of power line was extracted efficiently and accurately by filtering algorithm taking into account cross-line. In view of local linear model of power line, insulators were segmented. Finally, the local weighted centroid method was used to extract the key points of power line. Fast reconstruction of power line was realized. Theoretical analysis and experimental verification were carried out. Good experimental results were obtained. The results show that, overall accuracy of power line extraction and reconstruction is 95.3%. Total time consumed is less than 2.5s. The speed, accuracy and robustness of the algorithm are verified. This result is helpful to extract and reconstruct point cloud of power line.