Automatic Extraction of High-Voltage Power Transmission Objects from UAV Lidar Point Clouds-时空数据智能获取技术与应用教育部工程中心

Automatic Extraction of High-Voltage Power Transmission Objects from UAV Lidar Point Clouds

石莹 2021-08-08 浏览

引言

输电系统的检查和维护是电力资源管理的重要内容。远距离输电系统主要由高压输电塔、输电线路及附件组成。高压塔不仅起着机械支撑的作用，而且起着连接节点或转折点的作用。输电线路是电源的载体。它们通过绝缘体等附件连接在一起。为了保证输电系统的安全性和可靠性，电力公司必须确保这些部件与周围环境保持足够的安全裕度。电力廊道检查是风险管理的一项日常工作。输电廊道位于偏远的恶劣地形环境中，一般包括与输电系统混合的植被、建筑物等地面环境对象。因此，维护工作需要付出很大的努力。新型无人机载激光雷达技术为电力巡线带来了极大的改进。

摘要

电力传输和维护是电力行业的基础，激光雷达线路巡检技术为此带来了很大的便利。因此基于激光点云技术的输电通道三维对象提取技术是引起关注的研究点。本文提出了一种基于网格特征的高压输电目标自动提取方法，实现了从无人机采集的通道点云数据中快速分割提取主要高压输电对象。首先，在预处理时，构造一个空间哈希矩阵来逐层分割点云，并计算每个稀疏网格内点的局部分布特征。其次，利用邻近网格的高度相似度估计和线性特征提取电力线；再通过分析栅格在水平和垂直方向上的特征，识别候选输电塔区块。最后，结合线段与电塔之间的拓扑关系，优化提取结果，剔除信号塔等一类伪电塔。优化后的算法能够消除孤立的高大树木和通信信号柱的干扰，并剔除不完整的低压电力线。结果表明，该方法能够有效地在海量点云数据中获取三维目标的精确坐标，目标提取整体精度约97%。获取的高压电力线、电塔的三维地理信息，结合进一步重建的三维模型，是走廊安全维护和无人机遥感监测的重要基础。

成果介绍

图1 方法流程图

7CE3

图2 输电线提取过程

404F

图3 高电压塔提取过程

A16E

图4 主要输电要素三维重建

Abstract

Electric power transmission and maintenance is essential for the power industry. This paper proposes a method for the efficient extraction and classification of three-dimensional (3D) targets of electric power transmission facilities based on regularized grid characteristics computed from point cloud data acquired by unmanned aerial vehicles (UAVs). First, a special hashing matrix was constructed to store the point cloud after noise removal by a statistical method, which calculated the local distribution characteristics of the points within each sparse grid. Secondly, power lines were extracted by neighboring grids’ height similarity estimation and linear feature clustering. Thirdly, by analyzing features of the grid in the horizontal and vertical directions, the transmission towers in candidate tower areas were identified. The pylon center was then determined by a vertical slicing analysis. Finally, optimization was carried out, considering the topological relationship between the line segments and pylons to refine the extraction. Experimental results showed that the proposed method was able to efficiently obtain accurate coordinates of pylon and attachments in the massive point data and to produce a reliable segmentation with an overall precision of 97%. The optimized algorithm was capable of eliminating interference from isolated tall trees and communication signal poles. The 3D geo-information of high-voltage (HV) power lines, pylons, conductors thus extracted, and of further reconstructed 3D models can provide valuable foundations for UAV remote-sensing inspection and corridor safety maintenance.

Automatic Extraction of High-Voltage Power Transmission Objects from UAV Lidar Point Clouds

石莹 2021-08-08 _showDynClicks("wbnews", 1448217335, 1975)浏览

石莹 2021-08-08 浏览