Algorithm of pylon automatically localization and point cloud extraction in power line inspection based on LiDAR

doi:10.13474/j.cnki.11-2246.2020.0111

Abstract

Abstract: An automatic pylon localization and point cloud extraction algorithm is presented in this paper in order to solve the problem of pylon automatically extraction from point cloud of power line inspection. Firstly, 2D mesh is applied to get bias and variance of height of point cloud in each grid, and in which pylon is located cursorily. Secondly, points from tower are extracted roughly according to continuity of height in grids. Afterwards, points from tower are accurately extracted based on the structural features of pylon and power line, in which the density in different hierarchy of height and open operation of image are applied. Finally, point cloud collected from light small UAV-LiDAR is applied in experiments for experimental verification. Experiments show that the presented algorithm works well in the problem of tower extraction, and also has a high performance under condition of poor quality of point cloud. Algorithm presented in this paper has some value in application of power line inspection with LiDAR.

Key words: powerline inspection, LiDAR, point cloud classification, pylon localization, pylon extraction

CLC Number:

P234

HUANG Lujun, CHEN Guangping, YUAN Shuai, TU Pu, QIAO Jie. Algorithm of pylon automatically localization and point cloud extraction in power line inspection based on LiDAR[J]. Bulletin of Surveying and Mapping, 2020, 0(4): 53-57,75.

References

[1] 杨俊涛,康志忠.多尺度特征和马尔可夫随机场模型的电力线场景点云分类法[J].测绘学报,2018,47(2):188-197.
[2] 施孟佶,秦开宇,李凯,等.高压输电线路多无人机自主协同巡线设计与测试[J].电力系统自动化,2017,41(10):117-122.
[3] 段敏燕.机载激光雷达点云电力线三维重建方法研究[J].测绘学报,2016,45(12):1495.
[4] 陈勇,韩晓言,侯国彦,等.激光雷达小型化及其在输电系统中的应用研究[J].电力勘测设计,2013(1):70-73,77.
[5] 吕明,盛戈皞,张卫东,等.无人飞行器巡检输电线路的杆塔和导线跟踪算法[J].电力系统自动化,2012,36(9):92-97.
[6] 林祥国,张继贤.架空输电线路机载激光雷达点云电力线三维重建[J].测绘学报,2016,45(3):347-353.
[7] 彭劲松,许俊,李娟.无人机载激光测量系统在电力上的应用[J].测绘通报,2018(4):152-154.
[8] 刘洋,杨必胜,梁福逊.机载激光点云中高压电塔自动识别方法[J].测绘通报,2019(1):34-38.
[9] 周汝琴,许志海,彭炽刚,等.一种高压输电走廊机载激光点云分类方法[J].测绘科学,2019,44(3):21-27,33.
[10] 赖广陵,秦志远,丁璐.车载LiDAR数据电力线与塔杆提取方法[J].测绘科学技术学报,2016,33(6):617-622.
[11] GRILLI E, MENNA F, REMONDINO F. A review of point clouds segmentation and classification algorithm[J]. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, XLII-2/W3:339-344.
[12] LIU Y,LI Z,HAYWARD R, et al. Classification of airborne LiDAR intensity data using statistical analysis and hough transform with application to power line corridors[C]//Proceedings of 2009 Digital Image Computing:Techniques & Applications.[S.l.]:IEEE, 2010.
[13] 赖旭东,戴大昌,郑敏,等.LiDAR点云数据的电力线3维重建[J].遥感学报,2014,18(6):1223-1229.
[14] 王丽英,徐艳,李玉.机载LiDAR点云体元化及其在3D滤波中的应用[J].仪器仪表学报,2018,39(7):173-182.
[15] IPPOLITO C, KRISHNAKUMAR K, HENING S. Preliminary results of powerline reconstruction from airborne LiDAR for safe autonomous low-altitude urban operations of small UAS[C]//Proceedings of 2016 IEEE Sensors.[S.l.]:IEEE, 2016.
[16] QIN X Y,WU G P,YE X H, et al. A novel method to reconstruct overhead high-voltage power lines using cable inspection robot LiDAR data[J]. Remote Sensing, 2017, 9(7):753.
[17] LIU X, ZHENG S, LEI X U. Power line automatic extraction algorithm based on LiDAR data[J]. Journal of Geomatics, 2017, 42(4):13-16.
[18] SIRMACEK B, LINDENBERGH R. Automatic classification of trees from laser scanning point clouds[J]. Isprs Annals of Photogrammetry Remote Sensing & Spatial Informa, 2015, II-3/W5(4):137-144.
[19] ZHANG Z, ZHANG L, TONG X, et al. A multilevel point-cluster-based discriminative feature for ALS point cloud classification[J]. IEEE Transactions on Geoscience & Remote Sensing, 2016, 54(6):3309-3321.
[20] NI H, ZHANG J. Classification of ALS point cloud with improved point cloud segmentation and random forests[J]. Remote Sensing Technology & Application, 2017, 9(3):288.
[21] MARMANIS D, SCHINDLER K, WEGNER J D, et al. Classification with an edge: improving semantic image segmentation with boundary detection[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2018,35(1):158-172.
[22] ZHANG Liangpei. Splitting and merging based multi-model fitting for point cloud segmentation[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(2): 78-89.