Research on transformer vibration monitoring and diagnosis based on Internet of things

A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power...

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Autores principales:	Wang Zhenzhuo, Sharma Amit
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	internet of things power transformer machine learning naive bayes support vector machine Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/9f302adaf9ec4af2bd9f2e307300f396
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spelling	oai:doaj.org-article:9f302adaf9ec4af2bd9f2e307300f3962021-12-05T14:10:51ZResearch on transformer vibration monitoring and diagnosis based on Internet of things2191-026X10.1515/jisys-2020-0111https://doaj.org/article/9f302adaf9ec4af2bd9f2e307300f3962021-05-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0111https://doaj.org/toc/2191-026XA recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.Wang ZhenzhuoSharma AmitDe Gruyterarticleinternet of thingspower transformermachine learningnaive bayessupport vector machineScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 677-688 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	internet of things power transformer machine learning naive bayes support vector machine Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	internet of things power transformer machine learning naive bayes support vector machine Science Q Electronic computers. Computer science QA75.5-76.95 Wang Zhenzhuo Sharma Amit Research on transformer vibration monitoring and diagnosis based on Internet of things
description	A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.
format	article
author	Wang Zhenzhuo Sharma Amit
author_facet	Wang Zhenzhuo Sharma Amit
author_sort	Wang Zhenzhuo
title	Research on transformer vibration monitoring and diagnosis based on Internet of things
title_short	Research on transformer vibration monitoring and diagnosis based on Internet of things
title_full	Research on transformer vibration monitoring and diagnosis based on Internet of things
title_fullStr	Research on transformer vibration monitoring and diagnosis based on Internet of things
title_full_unstemmed	Research on transformer vibration monitoring and diagnosis based on Internet of things
title_sort	research on transformer vibration monitoring and diagnosis based on internet of things
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/9f302adaf9ec4af2bd9f2e307300f396
work_keys_str_mv	AT wangzhenzhuo researchontransformervibrationmonitoringanddiagnosisbasedoninternetofthings AT sharmaamit researchontransformervibrationmonitoringanddiagnosisbasedoninternetofthings
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Research on transformer vibration monitoring and diagnosis based on Internet of things

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