Cover Image

APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS

This report presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. While...

Full description

Saved in:
Bibliographic Details
Main Author: NASHRULADIN, KHAIRUN NISA'
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2007
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://utpedia.utp.edu.my/9476/1/2007%20-%20Application%20of%20ANN%20and%20GA%20for%20Transformer%20Winding%20Insulation%20Faults.pdf
http://utpedia.utp.edu.my/9476/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utp-utpedia.9476
record_format eprints
spelling my-utp-utpedia.94762013-10-22T14:38:38Z http://utpedia.utp.edu.my/9476/ APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS NASHRULADIN, KHAIRUN NISA' TK Electrical engineering. Electronics Nuclear engineering This report presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. While, heuristic method of Genetic Algorithm is used to locate the optimal values to enhance the accuracy of fault detection. The dissolved gas in oil analysis is chosen to diagnosis the transformer faults in this project as the method is known to be an early fault detection method and enables to carry out during online operation of the transformer. Besides, the condition of the transformer could be monitored continuously by time to time. The project outcome is analyzed using Neural Network and Genetic Algorithm MATLAB Toolbox. Comparison between the real fault and predicted fault is made as to observe the accuracy rate of the system. As transformer faults detection concentrated more in conventional method such the stability of the voltage and current of the transformer. Therefore, hopefully the transformer winding and insulation faults could be studied from new point ofview and method. Universiti Teknologi PETRONAS 2007-06 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/9476/1/2007%20-%20Application%20of%20ANN%20and%20GA%20for%20Transformer%20Winding%20Insulation%20Faults.pdf NASHRULADIN, KHAIRUN NISA' (2007) APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS. Universiti Teknologi PETRONAS. (Unpublished)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
NASHRULADIN, KHAIRUN NISA'
APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
description This report presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. While, heuristic method of Genetic Algorithm is used to locate the optimal values to enhance the accuracy of fault detection. The dissolved gas in oil analysis is chosen to diagnosis the transformer faults in this project as the method is known to be an early fault detection method and enables to carry out during online operation of the transformer. Besides, the condition of the transformer could be monitored continuously by time to time. The project outcome is analyzed using Neural Network and Genetic Algorithm MATLAB Toolbox. Comparison between the real fault and predicted fault is made as to observe the accuracy rate of the system. As transformer faults detection concentrated more in conventional method such the stability of the voltage and current of the transformer. Therefore, hopefully the transformer winding and insulation faults could be studied from new point ofview and method.
format Final Year Project
author NASHRULADIN, KHAIRUN NISA'
author_facet NASHRULADIN, KHAIRUN NISA'
author_sort NASHRULADIN, KHAIRUN NISA'
title APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
title_short APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
title_full APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
title_fullStr APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
title_full_unstemmed APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS
title_sort application of ann and ga for transformer winding/ insulation faults
publisher Universiti Teknologi PETRONAS
publishDate 2007
url http://utpedia.utp.edu.my/9476/1/2007%20-%20Application%20of%20ANN%20and%20GA%20for%20Transformer%20Winding%20Insulation%20Faults.pdf
http://utpedia.utp.edu.my/9476/
_version_ 1739831676752625664
score 13.211869

Similar Items