空载LiDAR电源线点云的增强自动跨度细分:缓解相邻电源线干扰
Yi Ma1, Guofang Wang1, Tianle Liu2
1Electric Power Research Institute, Yunnan Power Grid Company Ltd., Kunming 650217, China.
Sensors (Basel, Switzerland)
|October 29, 2025
概括
本研究介绍了一种自动化方法,用于从LiDAR数据中对电力线点云进行细分,这对于传输走廊检查至关重要. 这种新的方法有效地处理相邻电力线的干扰,使得3D重建的数据更清洁.
科学领域:
- 地质学工程 工程地质学
- 计算机视觉 计算机视觉
- 遥感 遥感 遥感 遥感
背景情况:
- 自动传输走廊检查依赖于从空中的LiDAR中对电力线点云的3D重建.
- 提取准确的电力线数据是具有挑战性的,因为相邻或交叉电力线的干扰.
研究的目的:
- 从LiDAR点云开发一个高效的,自动化的方法来对电源线跨度进行细分.
- 为电力线连锁曲线模型的自动重建提供清洁的数据.
- 在数据处理过程中解决和抑制相邻电力线的干扰.
主要方法:
- 开发了一种新的基于点计数网格 (PCGrid) 的快密度集群算法 (DBSCAN).
- 该方法利用LiDAR数据中的 pylons和电力线之间的空间关系.
- 它涉及2D/3D密度集群用于柱子提取和点云过,柱子连接验证和跨度分配.
主要成果:
- PCGrid 结构显著加快了集群效率.
- 该方法实现了完全自动化的跨度细分.
- 邻近的电源线干扰被有效地抑制,为3D电源线重建提供可靠的结果.
结论:
- 拟议的方法为电力线跨度细分提供了一种高效和自动化的解决方案.
- 集成PCGrid集群和空间关系驱动的柱子验证可以提高3D电力线重建的准确性.
- 这一框架对于改善自动传输走廊检查流程至关重要.
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