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Fuzzy logic based on-line fault detection and classification in transmission line

This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisitio...

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Detalles Bibliográficos
Autores principales: Adhikari, Shuma, Sinha, Nidul, Dorendrajit, Thingam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936998/
https://www.ncbi.nlm.nih.gov/pubmed/27398278
http://dx.doi.org/10.1186/s40064-016-2669-4
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author Adhikari, Shuma
Sinha, Nidul
Dorendrajit, Thingam
author_facet Adhikari, Shuma
Sinha, Nidul
Dorendrajit, Thingam
author_sort Adhikari, Shuma
collection PubMed
description This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application.
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spelling pubmed-49369982016-07-08 Fuzzy logic based on-line fault detection and classification in transmission line Adhikari, Shuma Sinha, Nidul Dorendrajit, Thingam Springerplus Research This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application. Springer International Publishing 2016-07-07 /pmc/articles/PMC4936998/ /pubmed/27398278 http://dx.doi.org/10.1186/s40064-016-2669-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Adhikari, Shuma
Sinha, Nidul
Dorendrajit, Thingam
Fuzzy logic based on-line fault detection and classification in transmission line
title Fuzzy logic based on-line fault detection and classification in transmission line
title_full Fuzzy logic based on-line fault detection and classification in transmission line
title_fullStr Fuzzy logic based on-line fault detection and classification in transmission line
title_full_unstemmed Fuzzy logic based on-line fault detection and classification in transmission line
title_short Fuzzy logic based on-line fault detection and classification in transmission line
title_sort fuzzy logic based on-line fault detection and classification in transmission line
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936998/
https://www.ncbi.nlm.nih.gov/pubmed/27398278
http://dx.doi.org/10.1186/s40064-016-2669-4
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