UAV-lidar aids automatic intelligent powerline inspection

doi:10.1016/j.ijepes.2021.106987

	UAV-lidar aids automatic intelligent powerline inspection
	Guan, Hongcan 1; Sun, Xiliang 1; Su, Yanjun 1; Hu, Tianyu 1; Wang, Haitao 2; Wang, Heping 3; Peng, Chigang 4; Guo, Qinghua5
	2021
发表期刊	INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
ISSN	0142-0615
卷号	130
摘要	In recent decades, a substantial increase in electricity demand has put pressure on powerline systems to ensure an uninterrupted power supply. In order to prevent power failures, timely and thorough powerline inspections are needed to detect possible anomalies in advance. In the past few years, the emerging unmanned aerial vehicle (UAV)-mounted sensors (e.g. light detection and ranging/lidar, optical cameras, infrared cameras, and ultraviolet cameras) have provided rich data sources for comprehensive and accurate powerline inspections. A challenge that still hinders the use of UAVs in powerline inspection is that their operation is highly dependent on the pilot?s experience, which may pose risks to the safety of the powerline system and reduce inspection efficiency. An intelligent automatic inspection solution could overcome the limitations of current UAV-based inspection solutions. The main objective of this paper is to provide a contemporary look at the current state-of-the-art UAVbased inspections as well as to discuss a potential lidar-supported intelligent powerline inspection concept. Overall, standardized protocols for lidar-supported intelligent powerline inspections include four data analysis steps, i.e., point cloud classification, key point extraction, route generation, and fault detection. To demonstrate the feasibility of the proposed concept, we implemented a workflow using a dataset of 3536 powerline spans, showing that the inspection of a single powerline span could be completed in 10 min with only one or two technicians. This demonstrates that lidar-supported intelligent inspection can be used to inspect a powerline system with extremely high efficiency and low costs.
关键词	Powerline inspection Intelligent Unmanned aerial vehicle Deep learning Lidar
学科领域	Engineering, Electrical & Electronic
DOI	10.1016/j.ijepes.2021.106987
收录类别	SCI
语种	英语
WOS关键词	LINE INSPECTION ; EXTRACTION ; VEGETATION ; AIRBORNE ; CLASSIFICATION ; PHOTOGRAMMETRY ; URBANIZATION ; MANAGEMENT ; PLATFORM ; VEHICLE
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000647654800016
出版者	ELSEVIER SCI LTD
文献子类	Article
出版地	OXFORD
EISSN	1879-3517
资助机构	National Natural Science Foundation of China [31971575] ; Beijing Municipal Science and Technology Project [Z191100007419004]
作者邮箱	guo.qinghua@pku.edu.cn
引用统计	被引频次：55[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/26633
专题	植被与环境变化国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Virginia Tech, Ctr Geospatial Informat Technol, Blacksburg, VA 24061 USA 4.State Grid Gen Aviat Co Ltd, Beijing 100031, Peoples R China 5.UAV Cruise Ctr Guangdong Power Grid, Guangzhou 510160, Peoples R China 6.Peking Univ, Coll Urban & Environm Sci, Inst Ecol, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Guan, Hongcan,Sun, Xiliang,Su, Yanjun,et al. UAV-lidar aids automatic intelligent powerline inspection[J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS,2021,130.
APA	Guan, Hongcan.,Sun, Xiliang.,Su, Yanjun.,Hu, Tianyu.,Wang, Haitao.,...&Guo, Qinghua.(2021).UAV-lidar aids automatic intelligent powerline inspection.INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS,130.
MLA	Guan, Hongcan,et al."UAV-lidar aids automatic intelligent powerline inspection".INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 130(2021).

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