Artificial intelligent based technique for partial discharge detection / Rosainy Baharom

This project presents an artificial intelligent based technique for partial discharge (PD) detection. The study involves an artificial neural network (ANN) development which will be used to train and test a series of data set in order to predict the presence of PD. The PD data are generated using a...

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Main Author: Baharom, Rosainy
Format: Thesis
Language:English
Published: 2011
Online Access:https://ir.uitm.edu.my/id/eprint/84539/1/84539.pdf
https://ir.uitm.edu.my/id/eprint/84539/
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spelling my.uitm.ir.845392024-02-19T07:24:51Z https://ir.uitm.edu.my/id/eprint/84539/ Artificial intelligent based technique for partial discharge detection / Rosainy Baharom Baharom, Rosainy This project presents an artificial intelligent based technique for partial discharge (PD) detection. The study involves an artificial neural network (ANN) development which will be used to train and test a series of data set in order to predict the presence of PD. The PD data are generated using a PD circuit, controlled by the various parameters in the circuit. The generated data will be grouped into training and testing data. Two programmed are developed namely the training programme and testing programme. The developed ANN model is able to predict the occurrence of partial discharge under various scenarios. 2011 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/84539/1/84539.pdf Artificial intelligent based technique for partial discharge detection / Rosainy Baharom. (2011) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description This project presents an artificial intelligent based technique for partial discharge (PD) detection. The study involves an artificial neural network (ANN) development which will be used to train and test a series of data set in order to predict the presence of PD. The PD data are generated using a PD circuit, controlled by the various parameters in the circuit. The generated data will be grouped into training and testing data. Two programmed are developed namely the training programme and testing programme. The developed ANN model is able to predict the occurrence of partial discharge under various scenarios.
format Thesis
author Baharom, Rosainy
spellingShingle Baharom, Rosainy
Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
author_facet Baharom, Rosainy
author_sort Baharom, Rosainy
title Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
title_short Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
title_full Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
title_fullStr Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
title_full_unstemmed Artificial intelligent based technique for partial discharge detection / Rosainy Baharom
title_sort artificial intelligent based technique for partial discharge detection / rosainy baharom
publishDate 2011
url https://ir.uitm.edu.my/id/eprint/84539/1/84539.pdf
https://ir.uitm.edu.my/id/eprint/84539/
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score 13.214268