基于激光点云的电力线悬挂点定位方法

史洪云; 虢韬; 王迪; 王时春; 赵健; 刘欣; 龙新

doi:doi:10.7510/jgjs.issn.1001-3806.2020.03.017

激光技术, 2020, 44 (3): 364, 网络出版: 2020-06-08

基于激光点云的电力线悬挂点定位方法

Power line suspension point location method based on laser point cloud

论文大纲

史洪云 ^1,*虢韬 ¹王迪 ²王时春 ¹赵健 ²刘欣 ¹龙新 ²

作者单位

¹ 贵州电网有限责任公司输电运行检修分公司, 贵阳 550000

² 中国电建集团贵州电力设计研究院有限公司, 贵阳 550000

摘要

为了解决目前电力线悬挂点定位方法鲁棒性低、定位不精确的问题, 采用基于激光点云的结合局部3维重建与迭代搜索的方法对电力线悬挂点定位进行了研究。首先, 对电力线点云空间特征进行分析进而推导电力线空间约束条件, 以此作为生长准则进行基于空间约束的区域生长, 实现跨越多档的单根电力线分割; 然后, 对杆塔点云聚类提取杆塔中心点, 以杆塔中心点连线的角平分线为基准划定每档电力线的空间分割平面; 之后, 对各分割平面附近电力线点云进行空间多项式局部3维重建; 最后, 结合分割平面迭代搜索计算重建电力线的交点, 实现电力线悬挂点空间位置定位。结果表明, 对于3种电压等级线路点云及2种数据质量点云, 电力线悬挂点定位平均偏差均在0.09m以内, 最小偏差为0.03m。该方法鲁棒性高, 可以精确地实现各电压等级及各质量点云数据中的电力线悬挂点定位, 为后续基于悬挂点的电力线模拟工况安全分析提供了基础。

Abstract

In order to solve the problems of low robustness and inaccurate location of power line suspension point location methods, a power line suspension point location method based on laser point cloud combined with local 3-D reconstruction and iterative search was used to study the location of power line suspension point. The spatial characteristics of power line point clouds were analyzed and the spatial constraints of power lines were deduced, which is used as a growth criterion for region growth based on spatial constraints to realize single power line segmentation across multiple stages. Then, the center point of the tower was extracted by clustering the point cloud of the tower, and the spatial segmentation plane of each power line was delineated on the basis of the angular bisector of the connection line of the center point of the tower. After that, the spatial polynomial local 3-D reconstruction of the power line point cloud near each segmentation plane was carried out; Finally, combined with the iterative search of the segmentation plane, the intersection point of the power line was reconstructed, and the spatial location of the power line suspension point was realized. The results show that for three kinds of voltage grade line point clouds and two kinds of data quality point clouds, the average location deviation is less than 0.09m, and the minimum deviation is 0.03m. This method has high robustness and can accurately locate the power line suspension point in each voltage level and mass point cloud data with high robustness and accuracy, which provides a basis for the subsequent safety analysis of power line simulation based on the suspension point.

参考文献

[1] SHI L, GUO T, PENG Ch, et al. Segmentation of laser point cloud and safety detection of power lines[J]. Laser Technology, 2019, 43(3): 341-346(in Chinese).

[2] WU J J, LI L, FANG P k, et al. Effective organization and visualization of helicopter-based laser scanning data in power line inspection[J]. Laser Technology, 2019, 43(3): 318-323(in Chinese).

[3] WU J J, CHEN L, LI L, et al. Power line extraction and reconstruction from airborne LiDAR point cloud[J]. Laser Technology, 2019, 43(4): 500-500(in Chinese).

[4] YANG J, ZENG X J, WANG J Y, et al. Research on power equipment damage based on laser detection and big data analysis[J]. Laser Journal, 2018, 39 (12): 78-82(in Chinese).

[5] POULIOT N, RICHARD P, MONTAMBAULT S. LineScout power line robot: Characterization of a UTM-30LX LIDAR system for obstacle detection[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). New York, USA: IEEE, 2012:25-46.

[6] WANG S B, LI M X, LI H R, et al. Research on obstacle detection of transmission line corridor based on 3-D laser radar technology[J]. Electronic Technology, 2019, 32 (4): 81-84(in Chinese).

[7] DING W, HUANG X Y, TAN X Y, et al. Detecting danger vegetation in powerline corridors using airborne laser points[J]. Surveying and Mapping and Spatial Geographic Information, 2018, 41 (11): 125-128(in Chinese).

[8] CHEN L M, ZHANG W, YU H, et al. Application of UAV-based LiDAR system for power line surveys[J]. Surveying and Mapping Bulletin, 2017(s1): 176-178(in Chinese).

[9] PU Sh, WU X Q, YAN Zh L, et al. Automatic recognition of defects on transmission lines from UAV-borne laser scanning data[J]. Remote Sensing Information, 2017, 32 (4): 52-57(in Chinese).

[10] RICHARD P L, POULIOT N, MONTAMBAULT S. Introduction of a LIDAR-based obstacle detection system on the Line Scout power line robot[C]//IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).New York, USA:IEEE,2014:3533-3538.

[11] CHEN Ch, PENG X Y, SONG Sh, et al. Safety distance diagnosis of large scale transmission line corridor inspection based on LiDAR point cloud collected with UAV[J]. Power Grid Technology, 2017, 41(8): 2723-2730(in Chinese).

[12] GUO B, LI Q, HUANG X, et al. An improved method for power line reconstruction from point cloud data[J]. Remote Sensing, 2016, 8(1): 36.

[13] YANG Y, CHEN F X, GUO T, et al. Power line extraction using airborne LiDAR point clouds characteristics and model fitting method[J]. Journal of Chinese Academy of Sciences, 2018, 35(5): 612-616(in Chinese).

[14] SHEN X J, QIN Ch, DU Y, et al. An automatic power line extraction method from airborne light detection and ranging point cloud in complex terrain[J]. Journal of Tongji University (Natural Science Edition), 2018, 46 (7): 982-987(in Chinese).

[15] LIN X G, NING X G, XIA Sh B. A method for power line LiDAR point cloud segmentation using K-means clustering of a feature space[J]. Surveying and Mapping Science, 2016, 41(5): 60-63(in Chinese).

[16] WANG Y, CHEN Q, LIU L, et al. Supervised classification of power lines from airborne LiDAR data in urban areas[J]. Remote Sensing, 2017, 9(8):771.

[17] XU B, LIU Zh J, WANG J. Extraction and security detection of power line based on laser point cloud data[J]. Laser Journal, 2017, 38 (7): 48-51(in Chinese).

[18] DUAN M Y. 3-D power line reconstruction from airborne LiDAR point cloud[J]. Journal of Surveying and Mapping, 2016, 45 (12): 1495(in Chinese).

[19] YU J, MU Ch, FENG Y M, et al.Powerlines extraction techniques from airborne LiDAR data[J]. Journal of Wuhan University (Information Science Edition), 2011, 36(11): 1275-1279(in Chinese).

[20] YIN H Z, SUN X, NIE Zh G. An automated extraction algorithm of power lines based on airborne laser scanning data[J]. Geography and Geographic Information Science, 2012, 28 (2): 31-34(in Chinese).

[21] LIN X G, DUAN M Y, ZHANG J X, et al. A method of reconstructing 3-D powerlines from airborne LiDAR point clouds[J]. Surveying and Mapping Science, 2016, 41(1): 109-114(in Chinese).

史洪云, 虢韬, 王迪, 王时春, 赵健, 刘欣, 龙新. 基于激光点云的电力线悬挂点定位方法[J]. 激光技术, 2020, 44(3): 364. SHI Hongyun, GUO Tao, WANG Di, WANG Shichun, ZHAO Jian, LIU Xin, LONG Xin. Power line suspension point location method based on laser point cloud[J]. Laser Technology, 2020, 44(3): 364.

基于激光点云的电力线悬挂点定位方法

关于本站 Cookie 的使用提示

全站搜索

基于激光点云的电力线悬挂点定位方法

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索