Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation

The subject matter of this paper is to introduce the time-frequency representation in analyzing the acoustic emission signals emitted by partial discharge sources. Three different types of partial discharge sources used to generate the acoustic emission signals during the partial discharge (PD) occu...

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Main Authors: Chai M.L., Md Thayoob Y.H., Ghosh P.S., Sha'ameri A.Z., Talib M.A.
Other Authors: 24448195600
Format: Conference paper
Published: IEEE Computer Society 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-297462023-12-28T16:08:41Z Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation Chai M.L. Md Thayoob Y.H. Ghosh P.S. Sha'ameri A.Z. Talib M.A. 24448195600 6505876050 55427760300 6602299273 36609320500 Acoustic emission signals Feature extraction Partial discharge sources Time-frequency representation Acoustic emissions Feature extraction Oil filled transformers Spectrographs Acoustic emission signal Descriptors Partial discharge sources Short time Fourier transforms Spectrograms Subject matters Time-frequency representations Partial discharges The subject matter of this paper is to introduce the time-frequency representation in analyzing the acoustic emission signals emitted by partial discharge sources. Three different types of partial discharge sources used to generate the acoustic emission signals during the partial discharge (PD) occurrences are created in an experimental tank filled with transformer oil. These partial discharge sources are the plain pressboard, the floating metal in the pressboard and the bubble in the pressboard. The acoustic emission (AE) signals are detected and stored as time-frequency representation, in the form of spectrogram, by utilizing the Short-Time Fourier Transform (STFT). Finally, seven descriptors are introduced in order to extract the features from each of the spectrogram. The obtained results also confirmed the ability of the proposed technique to discriminate between different types of PD sources. � 2006 IEEE. Final 2023-12-28T08:08:41Z 2023-12-28T08:08:41Z 2006 Conference paper 10.1109/PECON.2006.346718 2-s2.0-46249095130 https://www.scopus.com/inward/record.uri?eid=2-s2.0-46249095130&doi=10.1109%2fPECON.2006.346718&partnerID=40&md5=af3b8998a0b55a61e697714c1f2d39e1 https://irepository.uniten.edu.my/handle/123456789/29746 4154562 581 586 IEEE Computer Society Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Acoustic emission signals
Feature extraction
Partial discharge sources
Time-frequency representation
Acoustic emissions
Feature extraction
Oil filled transformers
Spectrographs
Acoustic emission signal
Descriptors
Partial discharge sources
Short time Fourier transforms
Spectrograms
Subject matters
Time-frequency representations
Partial discharges
spellingShingle Acoustic emission signals
Feature extraction
Partial discharge sources
Time-frequency representation
Acoustic emissions
Feature extraction
Oil filled transformers
Spectrographs
Acoustic emission signal
Descriptors
Partial discharge sources
Short time Fourier transforms
Spectrograms
Subject matters
Time-frequency representations
Partial discharges
Chai M.L.
Md Thayoob Y.H.
Ghosh P.S.
Sha'ameri A.Z.
Talib M.A.
Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
description The subject matter of this paper is to introduce the time-frequency representation in analyzing the acoustic emission signals emitted by partial discharge sources. Three different types of partial discharge sources used to generate the acoustic emission signals during the partial discharge (PD) occurrences are created in an experimental tank filled with transformer oil. These partial discharge sources are the plain pressboard, the floating metal in the pressboard and the bubble in the pressboard. The acoustic emission (AE) signals are detected and stored as time-frequency representation, in the form of spectrogram, by utilizing the Short-Time Fourier Transform (STFT). Finally, seven descriptors are introduced in order to extract the features from each of the spectrogram. The obtained results also confirmed the ability of the proposed technique to discriminate between different types of PD sources. � 2006 IEEE.
author2 24448195600
author_facet 24448195600
Chai M.L.
Md Thayoob Y.H.
Ghosh P.S.
Sha'ameri A.Z.
Talib M.A.
format Conference paper
author Chai M.L.
Md Thayoob Y.H.
Ghosh P.S.
Sha'ameri A.Z.
Talib M.A.
author_sort Chai M.L.
title Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
title_short Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
title_full Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
title_fullStr Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
title_full_unstemmed Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
title_sort identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation
publisher IEEE Computer Society
publishDate 2023
_version_ 1806423540074807296