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Voltage variations identification using gabor transform and rule-based classification method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 1 (2020)

DOI
10.11591/ijece.v10i1.pp681-689
ISSN
2088-8708, 2088-8708
Published
2020-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

This paper presents a comparatively contemporary easy to use technique for the identification and classification of voltage variations. The technique was established based on the Gabor Transform and the rule-based classification method. The technique was tested by using mathematical model of Power Quality (PQ) disturbances based on the IEEE Std 519-2009. The PQ disturbances focused were the voltage variations, which included voltage sag, swell and interruption. A total of 80 signals were simulated from the mathematical model in MATLAB and used in this study. The signals were analyzed by using Gabor Transform and the signal pattern, time-frequency representation (TFR) and root-mean-square voltage graph were presented in this paper. The features of the analysis were extracted, and rules were implemented in rule-based classification to identify and classify the voltage variation accordingly. The results showed that this method is easy to be used and has good accuracy in classifying the voltage variation.

Collaboration network of the authors

29 authors · 91 co-authorship links · 22 across different organisations

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  • Universiti Teknikal Malaysia Melaka
  • Universitas Ahmad Dahlan
  • Universiti Putra Malaysia
  • Universiti Malaysia Perlis
  • University of Osijek
  • Multimedia University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Tole SutiknoUniversitas Ahmad Dahlan10
Mohd Hatta JopriUniversiti Teknikal Malaysia Melaka10
Mustafa ManapUniversiti Teknikal Malaysia Melaka10
Norhashimah Mohd SaadUniversiti Teknikal Malaysia Melaka6
Nursabillilah Mohd AliUniversiti Teknikal Malaysia Melaka3
A.S. HussinUniversiti Teknikal Malaysia Melaka3
Mohd Ruddin Ab GhaniUniversiti Teknikal Malaysia Melaka3
N. S. M. NoorUniversiti Teknikal Malaysia Melaka2
Ahmad Sobri MudaUniversiti Putra Malaysia2
M.F. HabbanUniversiti Teknikal Malaysia Melaka2
Jingwei TooUniversiti Teknikal Malaysia Melaka1
Haslinda MusaUniversiti Teknikal Malaysia Melaka1
Nor Nabilah Syazana Abdul RahmanUniversiti Teknikal Malaysia Melaka1
Khalil Azha Mohd AnnuarUniversiti Teknikal Malaysia Melaka1
Mohd Firdaus Mohd Ab HalimUniversiti Teknikal Malaysia Melaka1
Mohamad Haniff HarunUniversiti Teknikal Malaysia Melaka1
Farriz Hj Md BasarAffiliation unknown1
Mohd OmarUniversiti Malaysia Perlis1
Norihan Binti Abdul HamidUniversiti Teknikal Malaysia Melaka1
M. A. Muhammad SyahmiUniversiti Teknikal Malaysia Melaka1
Srete NikolovskiUniversity of Osijek1
Nur Hasanah AliMultimedia University1
Shaarmila KandayaUniversiti Teknikal Malaysia Melaka1
Ezreen Farina ShairUniversiti Teknikal Malaysia Melaka1
Muhammad Izzat Ahmad SabriAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Voltage variations identification using gabor transform and rule-based classification method</dc:title><dc:creator>Tee, Weihown</dc:creator><dc:creator>Yusoff, M. R.</dc:creator><dc:creator>Yaakub, M. Faizal</dc:creator><dc:creator>Abdullah, A. R.</dc:creator><dc:description>&lt;jats:p&gt;This paper presents a comparatively contemporary easy to use technique for the identification and classification of voltage variations. The technique was established based on the Gabor Transform and the rule-based classification method. The technique was tested by using mathematical model of Power Quality (PQ) disturbances based on the IEEE Std 519-2009. The PQ disturbances focused were the voltage variations, which included voltage sag, swell and interruption. A total of 80 signals were simulated from the mathematical model in MATLAB and used in this study. The signals were analyzed by using Gabor Transform and the signal pattern, time-frequency representation (TFR) and root-mean-square voltage graph were presented in this paper. The features of the analysis were extracted, and rules were implemented in rule-based classification to identify and classify the voltage variation accordingly. The results showed that this method is easy to be used and has good accuracy in classifying the voltage variation.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v10i1.pp681-689</dc:identifier><dc:identifier>10.11591/ijece.v10i1.pp681-689</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 1 (2020); 681</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/17922/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>