Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor

This report is about the Artificial Neural Networks (ANN) are used to predict incipient faults in power transformers oil. The prediction is performed through the Dissolved Gas Analysis (DGA) method. The function of this method is for detect and diagnose the different types of incipient faults that o...

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Main Author:	Mansor, Nur Diyana
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Neural networks (Computer science) Electronics
Online Access:	https://ir.uitm.edu.my/id/eprint/84633/1/84633.pdf
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id	my-uitm-ir.84633
record_format	uketd_dc
spelling	my-uitm-ir.846332024-04-23T09:29:49Z Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor 2013 Mansor, Nur Diyana Neural networks (Computer science) Electronics This report is about the Artificial Neural Networks (ANN) are used to predict incipient faults in power transformers oil. The prediction is performed through the Dissolved Gas Analysis (DGA) method. The function of this method is for detect and diagnose the different types of incipient faults that occur in power trasformers. By interpretation of dissolved gasses in oil insulation of power transformers, this method was applied in the Artificial Neural Networks (ANN) to classify the different faults by using the DGA method. In DGA method, the Roger's Ratio and International Electrotechnical Commission (IEC) Ratio were applied into ANN to see the performance of ANN's network. For assessment, two set databases are employed: Roger's ratio and IEC ratio. The data bases are collected from Tenaga Nasional Berhad (TNB) data. The results show these methods were used to predicting the fault more than 90% of accuracy m best case. 2013 Thesis https://ir.uitm.edu.my/id/eprint/84633/ https://ir.uitm.edu.my/id/eprint/84633/1/84633.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Johari, Dalina
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Johari, Dalina
topic	Neural networks (Computer science) Electronics
spellingShingle	Neural networks (Computer science) Electronics Mansor, Nur Diyana Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
description	This report is about the Artificial Neural Networks (ANN) are used to predict incipient faults in power transformers oil. The prediction is performed through the Dissolved Gas Analysis (DGA) method. The function of this method is for detect and diagnose the different types of incipient faults that occur in power trasformers. By interpretation of dissolved gasses in oil insulation of power transformers, this method was applied in the Artificial Neural Networks (ANN) to classify the different faults by using the DGA method. In DGA method, the Roger's Ratio and International Electrotechnical Commission (IEC) Ratio were applied into ANN to see the performance of ANN's network. For assessment, two set databases are employed: Roger's ratio and IEC ratio. The data bases are collected from Tenaga Nasional Berhad (TNB) data. The results show these methods were used to predicting the fault more than 90% of accuracy m best case.
format	Thesis
qualification_level	Bachelor degree
author	Mansor, Nur Diyana
author_facet	Mansor, Nur Diyana
author_sort	Mansor, Nur Diyana
title	Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
title_short	Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
title_full	Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
title_fullStr	Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
title_full_unstemmed	Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor
title_sort	application of ann to predict incipient faults in power transformer based on dga method / nur diyana mansor
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/84633/1/84633.pdf
_version_	1804889730605645824

Application of ANN to predict incipient faults in power transformer based on DGA method / Nur Diyana Mansor

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