Paper Info
Title
Automatic Power Line Inspection Using UAV Images.
Abstract
Power line inspection ensures the safe operation of a power transmission grid. Using unmanned aerial vehicle (UAV) images of power line corridors is an effective way to carry out these vital inspections. In this paper, we propose an automatic inspection method for power lines using UAV images. This method, known as the power line automatic measurement method based on epipolar constraints (PLAMEC), acquires the spatial position of the power lines. Then, the semi patch matching based on epipolar constraints (SPMEC) dense matching method is applied to automatically extract dense point clouds within the power line corridor. Obstacles can then be automatically detected by calculating the spatial distance between a power line and the point cloud representing the ground. Experimental results show that the PLAMEC automatically measures power lines effectively with a measurement accuracy consistent with that of manual stereo measurements. The height root mean square (RMS) error of the point cloud was 0.233 m, and the RMS error of the power line was 0.205 m. In addition, we verified the detected obstacles in the field and measured the distance between the canopy and power line using a laser range finder. The results show that the difference of these two distances was within +/- 0.5 m.
Year
DOI
Venue
2017
10.3390/rs9080824
REMOTE SENSING
Keywords
Field
DocType
power line inspection,power line extraction,dense matching,obstacles within power line corridors,power line monitoring
Computer vision,Epipolar geometry,Remote sensing,Electric power transmission,Root mean square,Artificial intelligence,Root-mean-square deviation,Accuracy and precision,Point cloud,Power transmission,Geology,Grid
Journal
Volume
Issue
Citations 
9
8
7
PageRank 
References 
Authors
0.60
11
4
Name
Order
Citations
PageRank
Yong Zhang1224.53
xiuxiao yuan2374.09
Wenzhuo Li3315.70
Shiyu Chen43311.44