基于激光雷达数据的高压输电线路塔架提取与植被侵占分析改进方法

Nosheen Munir, M. Awrangjeb, Bela Stantic
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引用次数: 6

摘要

由于植被的侵入,维护高压电线的通行权对于配电公司安全可靠地输送电力非常重要。然而,当电力线走廊(PLC)存在于山地或森林等复杂环境中时,其监测就变得更加困难。为了克服这些挑战,本文旨在提供一种自动化的方法来提取单个塔和监测丘陵地形PLC附近的植被。该方法首先将大数据集划分为可管理的小数据集。在每个数据集上形成一个体素网格,将电力线与塔和植被分开。将电力线点转换成二值图像,得到各个点的跨度。这些跨度点用于寻找附近的植被和塔点,并使用统计分析进一步分离单个塔和植被。最后,根据电力线估算提取植被的高度和位置,并将其划分为危险区和清除区。在澳大利亚两个大型数据集上的实验表明,该方法对塔架的完整性和正确性分别达到了96.5%和99%。此外,还确定了PLC下面和周围生长的植被,这些植被可能会损害电力线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved method for pylon extraction and vegetation encroachment analysis in high voltage transmission lines using LiDAR data
The maintenance of high-voltage power lines rights-of-way due to vegetation intrusions is important for electric power distribution companies for safe and secure delivery of electricity. However, the monitoring becomes more challenging if power line corridor (PLC) exists in complex environment such as mountainous terrains or forests. To overcome these challenges, this paper aims to provide an automated method for extraction of individual pylons and monitoring of vegetation near the PLC in hilly terrain. The proposed method starts off by dividing the large dataset into small manageable datasets. A voxel grid is formed on each dataset to separate power lines from pylons and vegetation. The power line points are converted into a binary image to get the individual spans. These span points are used to find nearby vegetation and pylon points and individual pylons and vegetation are further separated using a statistical analysis. Finally, the height and location of extracted vegetation with reference to power lines are estimated and separated into danger and clearance zones. The experiment on two large Australian datasets shows that the proposed method provides high completeness and correctness of 96.5% and 99% for pylons, respectively. Moreover, the growing vegetation beneath and around the PLC that can harm the power lines is identified.
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