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A Utilisation of Improved Gabor Transform for Harmonic Signals Detection and Classification Analysis

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 1 (2017)

DOI
10.11591/ijece.v7i1.pp21-28
ISSN
2088-8708, 2088-8708
Published
2017-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

This paper presents a utilization of improved Gabor transform for harmonic signals detection and classification analysis in power distribution system. The Gabor transform is one of time frequency distribution technique with a capability of representing signals in jointly time-frequency domain and known as time frequency representation (TFR). The estimation of spectral information can be obtained from TFR in order to identify the characteristics of the signals. The detection and classification of harmonic signals for 100 unique signals with numerous characteristic of harmonics with support of rule-based classifier and threshold setting that been referred to IEEE standard 1159 2009. The accuracy of proposed method is determined by using MAPE and the outcome demonstrate that the method gives high accuracy of harmonic signals classification. Additionally, Gabor transform also gives 100 percent correct classification of harmonic signals. It is verified that the proposed method is accurate and cost efficient in detecting and classifying harmonic signals in distribution system.

Collaboration network of the authors

40 authors · 95 co-authorship links · 43 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universiti Teknikal Malaysia Melaka
  • University of Technology Malaysia
  • Islamic Azad University, Tehran
  • Universitas Ahmad Dahlan
  • Sultan Agung Islamic University
  • Tun Hussein Onn University of Malaysia
  • University of Mazandaran
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nik Rumzi Nik IdrisUniversity of Technology Malaysia9
Mohammad JannatiUniversity of Technology Malaysia9
A.S. HussinUniversiti Teknikal Malaysia Melaka9
Mohd Ruddin Ab GhaniUniversiti Teknikal Malaysia Melaka9
Mohd Junaidi Abdul AzizUniversity of Technology Malaysia7
Awang JusohUniversity of Technology Malaysia7
Norhashimah Mohd SaadUniversiti Teknikal Malaysia Melaka6
M.F. HabbanUniversiti Teknikal Malaysia Melaka5
Muhammad AdoUniversity of Technology Malaysia4
Lina HandayaniUniversitas Ahmad Dahlan3
Imam Much Ibnu SubrotoSultan Agung Islamic University3
Nursabillilah Mohd AliUniversiti Teknikal Malaysia Melaka3
Shahreen binti KasimTun Hussein Onn University of Malaysia3
Mahmoud ZadehbagheriIslamic Azad University, Tehran3
Mohammad Javad KianiIslamic Azad University, Tehran3
Vahdat NazerianUniversity of Mazandaran3
Auzani JidinUniversiti Teknikal Malaysia Melaka2
M. GhanbariAffiliation unknown2
Munawar Agus RiyadiDiponegoro University2
Deris StiawanSriwijaya University2
M. Najafi KhoshrodiAffiliation unknown2
N. S. M. NoorUniversiti Teknikal Malaysia Melaka2
Mehdi DadkhahIslamic Azad University, Tehran2
Shahaboddin ShamshirbandUniversity of Malaya2
Ahmad Saudi SamosirLampung University2
Ahmad Sobri MudaUniversiti Putra Malaysia2
Ali AjamiAffiliation unknown2
Chibuike Peter OhanuUniversity of Nigeria2
Aiman Zakwan JidinUniversiti Teknikal Malaysia Melaka1
Rozana AlikUniversity of Technology Malaysia1
Muhammad Firdaus Abd RazakUniversity of Technology Malaysia1
Mohamad Hamka Bin SaifulUniversity of Technology Malaysia1
Jingwei TooUniversiti Teknikal Malaysia Melaka1
Haslinda MusaUniversiti Teknikal Malaysia Melaka1
Nor Nabilah Syazana Abdul RahmanUniversiti Teknikal Malaysia Melaka1

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>A Utilisation of Improved Gabor Transform for Harmonic Signals Detection and Classification Analysis</dc:title><dc:creator>Jopri, M.H.</dc:creator><dc:creator>Abdullah, A.R.</dc:creator><dc:creator>Sutikno, T.</dc:creator><dc:creator>Manap, M.</dc:creator><dc:creator>Yusoff, M.R.</dc:creator><dc:description>&lt;jats:p&gt;This paper presents a utilization of improved Gabor transform for harmonic signals detection and classification analysis in power distribution system.  The Gabor transform is one of time frequency distribution technique with a capability of representing signals in jointly time-frequency domain and known as time frequency representation (TFR). The estimation of spectral information can be obtained from TFR in order to identify the characteristics of the signals. The detection and classification of harmonic signals for 100 unique signals with numerous characteristic of harmonics with support of rule-based classifier and threshold setting that been referred to IEEE standard 1159 2009. The accuracy of proposed method is determined by using MAPE and the outcome demonstrate that the method gives high accuracy of harmonic signals classification. Additionally, Gabor transform also gives 100 percent correct classification of harmonic signals. It is verified that the proposed method is accurate and cost efficient in detecting and classifying harmonic signals in distribution system.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2017-02-01</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.v7i1.pp21-28</dc:identifier><dc:identifier>10.11591/ijece.v7i1.pp21-28</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 7 No 1 (2017); 21</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/6249/5964</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>