根据空中立体雷达 (LiDAR) 进行电线提取和树木风险检测.
Siyuan Xi1, Zhaojiang Zhang1, Yufen Niu1
1School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China.
Sensors (Basel, Switzerland)
|October 14, 2023
概括
本研究引入了一种用于电力线路检查的自动化方法,准确检测输电线路附近的树木风险. 该方法通过精确识别潜在危险并计算安全距离,确保了更安全的操作.
科学领域:
- 电气工程 电气工程
- 计算机视觉 计算机视觉
- 林业科学 林业科学
背景情况:
- 输电线路的安全运行对于人类活动至关重要.
- 及时识别树木风险对于防止停电和确保电网稳定至关重要.
研究的目的:
- 提出一种自动化的方法来提取电力线和树木风险检测.
- 通过准确的风险评估,提高输电线路运营的安全性和可靠性.
主要方法:
- 使用的高度差和局部维度特征为电力线点提取的概率模型.
- 采用布模拟过算法和社区共享用于导体和接地电线分类.
- 应用线性链式模型用于导体重建和安全距离计算,用于树木风险分类.
主要成果:
- 实现了导体和接地线的高分类精度,精度,回忆和F-score超过98%.
- 证明了精确的导体重建,根-平均-平方误差低 (<3.67厘米) 和最大误差 (<7.13厘米).
- 在安全距离计算中,验证了树风险检测方法的有效性,平均绝对误差为<6.47厘米.
结论:
- 拟议的方法有效地提取电力线,并以高准确度和可靠性检测树木风险.
- 这种方法有助于提高输电线路的安全性和运营效率.
- 这些发现支持将先进的计算方法集成到电力基础设施管理中.
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