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New Robot for Power Line Inspection

Authors: Jaka Katrasnik; Franjo Pernus; Bostjan Likar;

New Robot for Power Line Inspection

Abstract

Power line inspection is of the utmost importance for the reliability and stability of electric power distribution. However, manual inspection is a hazardous, slow, expensive and unreliable task. Therefore, new highly specialized robots are required to improve the overall quality and safety of the power line inspection. The research conducted so far has been mainly focused on the development of climbing and flying robots. This paper first addresses the main achievements in the field of robotic power line inspection. The proposed solutions are critically assessed and the associated problems are outlined. Based on these findings, a new concept for robot-assisted power line inspection, combining both climbing and flying principles, is proposed in the second part of the paper. The proposed concept is critically assessed and related to the other established concepts so as to demonstrate its advantages and feasibility for a routine power line inspection.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Average
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