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

This paper Artificial Neural Networks (ANN) arc 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...

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Main Author: Mansor, Nur Diyana
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/12458/
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author Mansor, Nur Diyana
author_facet Mansor, Nur Diyana
author_sort Mansor, Nur Diyana
building UiTM Institutional Repository
collection Online Access
description This paper Artificial Neural Networks (ANN) arc 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 transformers. By interpretation of dissolved gasses in oil insulation of power transformers, this method was applied 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 in best cases.
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publishDate 2013
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spelling uitm-124582024-07-28T05:21:03Z https://ir.uitm.edu.my/id/eprint/12458/ Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor Mansor, Nur Diyana Neural networks (Computer science) Applications of electronics This paper Artificial Neural Networks (ANN) arc 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 transformers. By interpretation of dissolved gasses in oil insulation of power transformers, this method was applied 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 in best cases. 2013 Article NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/12458/1/12458.pdf Mansor, Nur Diyana (2013) Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor. (2013) pp. 1-7. (Unpublished)
spellingShingle Neural networks (Computer science)
Applications of electronics
Mansor, Nur Diyana
Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title_full Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title_fullStr Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title_full_unstemmed Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title_short Application of ANN to predict incipient faults in power transformer based on DGA method: article / Nur Diyana Mansor
title_sort application of ann to predict incipient faults in power transformer based on dga method: article / nur diyana mansor
topic Neural networks (Computer science)
Applications of electronics
url https://ir.uitm.edu.my/id/eprint/12458/