基于稀疏重建和激光实境复制的电力工程建模方法  

A modeling method for power engineering based on sparse reconstruction and laser reality replication

作　　者：周鑫 胡轶龙 张潇 李豪 李卓彬 ZHOU Xin;HU Yilong;ZHANG Xiao;LI Hao;LI Zhuobin(Electric Power Construction Engineering Consulting Branch,State Grid Beijing Electric Power Company,Beijing 100021,China)

机构地区：[1]国网北京市电力公司电力建设工程咨询分公司,北京100021

出　　处：《电子设计工程》2024年第4期191-195,共5页Electronic Design Engineering

基　　金：北京电力公司输变电工程应用项目(SGBJJS00XSJS2100639)。

摘　　要：由于机载激光雷达生成的原始点云数据存在质量较差且离散点多的问题,故难以直接应用于模型重建与电力工程的管理中。因此,文中基于稀疏-稠密算法和点云数据提出了一种电力工程模型重建算法。利用无人机机载激光雷达来获取多帧输电线路点云数据,并使用索引树近邻搜索法对原始点云数据进行坐标转换及离散数据过滤,进而得到重建的点云数据。通过稀疏重建算法对重建后数据中的框架特征加以提取,同时引入稠密算法进行框架填充,完成输电线路内容的重建。经实验测试表明,所提算法的点云提取误差仅为8.42 cm,在对比算法中性能最优。且重建后的模型可应用于电力工程验收、巡检等实际场景中,具有良好的工程意义。The raw point cloud data generated by airborne lidar has the problems of poor quality and many discrete points,which is difficult to be directly applied to model reconstruction and power engineering management.Therefore,this paper proposes a power engineering model reconstruction algorithm based on sparse dense algorithm and point cloud data.The algorithm uses the UAV airborne lidar to obtain multi frame transmission line point cloud data,and uses the index tree nearest neighbor search method to transform the coordinates of the original point cloud data and filter the discrete data to obtain the reconstructed point cloud data.The sparse reconstruction algorithm is used to extract the frame features in the reconstructed point cloud data,and the dense algorithm is introduced to fill the frame.The reconstruction of the transmission line content is completed.In the experimental test,the point cloud extraction error of the proposed algorithm is only 8.42 cm,and the performance of the comparison algorithm is the best.The reconstructed model can be applied to the actual engineering scenarios such as power engineering acceptance and patrol inspection,and has good engineering significance.

关 键 词：点云数据 索引树近邻搜索法 稀疏重建算法 稠密重建算法 电力工程管理 激光雷达 

分 类 号：TN-9[电子电信]