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Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid

Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct p...

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Detalles Bibliográficos
Autores principales: Byambasuren, Bat-erdene, Kim, Donghan, Oyun-Erdene, Mandakh, Bold, Chinguun, Yura, Jargalbaatar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801626/
https://www.ncbi.nlm.nih.gov/pubmed/26907274
http://dx.doi.org/10.3390/s16020250
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author Byambasuren, Bat-erdene
Kim, Donghan
Oyun-Erdene, Mandakh
Bold, Chinguun
Yura, Jargalbaatar
author_facet Byambasuren, Bat-erdene
Kim, Donghan
Oyun-Erdene, Mandakh
Bold, Chinguun
Yura, Jargalbaatar
author_sort Byambasuren, Bat-erdene
collection PubMed
description Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results.
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spelling pubmed-48016262016-03-25 Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid Byambasuren, Bat-erdene Kim, Donghan Oyun-Erdene, Mandakh Bold, Chinguun Yura, Jargalbaatar Sensors (Basel) Article Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results. MDPI 2016-02-19 /pmc/articles/PMC4801626/ /pubmed/26907274 http://dx.doi.org/10.3390/s16020250 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Byambasuren, Bat-erdene
Kim, Donghan
Oyun-Erdene, Mandakh
Bold, Chinguun
Yura, Jargalbaatar
Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title_full Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title_fullStr Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title_full_unstemmed Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title_short Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
title_sort inspection robot based mobile sensing and power line tracking for smart grid
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801626/
https://www.ncbi.nlm.nih.gov/pubmed/26907274
http://dx.doi.org/10.3390/s16020250
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