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遥感技术与应用  2021, Vol. 36 Issue (6): 1306-1310    DOI: 10.11873/j.issn.1004-0323.2021.6.1306
LiDAR专栏     
机载LiDAR输电线路杆塔快速定位方法研究
王和平1(),陈世超2,胡伟1,马春田1,刘宁1,王成2()
1.国网通用航空有限公司,北京 102209
2.中国科学院空天信息创新研究院 中科院数字地球重点实验室,北京 100094
Study on Power Pylon Fast Positioning in Transmission Line from Airborne LiDAR Data
Heping Wang1(),Shichao Chen2,Wei Hu1,Chuntian Ma1,Ning Liu1,Cheng Wang2()
1.National Grid General Aviation Company Limited,Beijing 102209,China
2.Key Laboratory of Digital Earth,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China
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摘要:

杆塔位置是机载激光雷达电力巡检应用中进行输电线路点云分段、杆塔提取、变化检测的基础。为了提高其自动定位的精度和效率,提出了一种适用于复杂地形的高压输电线路杆塔自动定位方法。首先在分析了输电线路点云相对高度、垂直和水平分布特征基础上,采用格网预处理剔除低位点格网、聚类分析确定候选类簇,然后利用格网垂直连续分布系数、高程分布系数和凸包系数等识别杆塔点所在格网,并以邻近格网中心作为杆塔水平位置。实验结果表明:相比前人的方法,算法的杆塔定位精度提高了11.7%,查准率和召回率分别提高了50%和20%,尤其是在地形起伏大且不连续的情况下具有较好的普适性。

关键词: 机载激光雷达点云输电线路杆塔定位格网聚类    
Abstract:

Precise spatial position of power pylon is the basis for the transmission line point cloud segmentation, power pylon points extraction, and change monitoring in airborne Light Detection and Ranging (LiDAR) power inspection application. In order to improve the algorithm efficiency of its automatic positioning and the accuracy and robustness, an automatic positioning method for the high-voltage transmission line of complex terrain is proposed. Firstly, according to the analysis of the relative height, vertical and horizontal distribution characteristics of the airborne point cloud of the transmission line, a grid preprocessing is used to remove low-level point grid and a grid cluster analysis is applied to determine the candidate clusters, and then based on the grid vertical continuous distribution coefficient, elevation distribution coefficient, convex hull coefficient and so on, the grids where the power pylon points are located, are identified and the adjacent grid center serves as the horizontal position of the power pylon. The experimental results show that compared with the previous methods, the accuracy of the proposed algorithm has increased by 11.7%, the precision and recall rate has increased by 50% and 25% respectively, especially when the terrain is rough and discontinuous, it has better robustness.

Key words: Airborne LiDAR    Point cloud    Transmission power line    Power pylon positioning    Grid cluster
收稿日期: 2021-02-24 出版日期: 2022-01-26
ZTFLH:  P237  
基金资助: 国网通用航空有限公司科技项目(2400/2019-44003B)
通讯作者: 王成     E-mail: hopywang79@163.com;wangcheng@aircas.ac.cn
作者简介: 王和平(1979-),男,湖北公安人,高级工程师,主要从事直升机电力作业及信息化研究。E?mail:hopywang79@163.com
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引用本文:

王和平,陈世超,胡伟,马春田,刘宁,王成. 机载LiDAR输电线路杆塔快速定位方法研究[J]. 遥感技术与应用, 2021, 36(6): 1306-1310.

Heping Wang,Shichao Chen,Wei Hu,Chuntian Ma,Ning Liu,Cheng Wang. Study on Power Pylon Fast Positioning in Transmission Line from Airborne LiDAR Data. Remote Sensing Technology and Application, 2021, 36(6): 1306-1310.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.6.1306        http://www.rsta.ac.cn/CN/Y2021/V36/I6/1306

  
图1  垂直连续分布系数分布
图2  输电通道地物分布
图3  杆塔定位方法流程图
图4  移除低位点后点云相对高度
序号点数量线路长度/m线路宽度/m杆塔数量杆塔高度/m地形特征
最小最大
119 344 9314 748901252.6974.63平坦、连续
217 431 3033 02283928.4139.73平坦、不连续
335 020 7316 0063001520.4433.36起伏大、不连续
表1  实验数据信息
序号预设值格网聚类识别塔位置
TH1 (m)TH2 (m)TLCTL (m)TVTHTC
11580.91000.90.150.2
21080.9500.90.150.2
31080.91000.90.150.2
表2  所提算法的实验参数取值
序号本实验算法文献[12]
PRF1Efficiency(s/km)PRF1
1100%100%100%3.4100%100%100%
2100%100%100%3.0100%100%100%
3100%100%100%5.850.0%80.0%65.0%
平均值100%100%100%4.183.3%93.3%88.3%
表3  杆塔定位精度和效率
图5  杆塔定位结果
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