Back to Search Start Over

Small UAV Urban Overhead Transmission Line Autonomous Correction Inspection System Based on Radar and RGB Camera

Authors :
Li, Ziran
Wu, Hao
Wang, Qi
Wang, Wei
Suzuki, Satoshi
Namiki, Akio
Source :
IEEE Sensors Journal; 2024, Vol. 24 Issue: 5 p5593-5608, 16p
Publication Year :
2024

Abstract

As the scale of the power grid continues to expand, drone inspection operations are becoming increasingly popular. However, most of the existing inspection drones are for transmission line inspection in the open field environment, with the characteristics of large size and high quality, which is difficult to be directly applied to transmission line inspection around the city area. To address the above issues, in this article, a small unmanned aerial vehicle (UAV) inspection system is designed with the aim of achieving autonomous inspection of overhead ground wires in urban peripheral areas, combined with image processing technology, with a total weight of less than 400 g. Specifically, during the inspection of small UAV, Raspberry Pi uses traditional image processing methods, such as Hough transform, to obtain the position information and pixel error of ground wire from real-time video stream; the flight control system uses the results of image processing combined with data from millimeter-wave radar to achieve conversion from pixel error to actual distance error; finally, the ground wire is made to be in the center of the video as much as possible through the correction strategy, thus realizing the autonomous inspection task of the small UAV along the line. The experimental results show that the small UAV can stably identify the target transmission lines and achieve autonomous flight along the lines with horizontal deviation within plus or minus 0.3 m and height deviation within plus or minus 0.1 m, which is of great reference value for the application of small UAV in urban transmission line inspection.

Details

Language :
English
ISSN :
1530437X and 15581748
Volume :
24
Issue :
5
Database :
Supplemental Index
Journal :
IEEE Sensors Journal
Publication Type :
Periodical
Accession number :
ejs65663274
Full Text :
https://doi.org/10.1109/JSEN.2023.3317076