Application of fuzzy c-means clustering approach to partial discharge pattern recognition of cast-resin current transformers

Wen Yeau Chang, Hong Tzer Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper proposes a fuzzy c-means (FCM) clustering based recognition method to identify the defects of cast-resin current transformers (CRCT) arising from partial discharge (PD). To identify the defects, field data are collected in this paper using a PD detecting system for the CRCT. The proposed FCM clustering based classifier builds the cluster centers according to distributions of the extracted feature vectors. Effectiveness and feasibility of the proposed method have been verified through the encouraging results obtained using comprehensive experimental data.

Original languageEnglish
Title of host publicationProceedings of ICPADM 2006 - 8th International Conference on Properties and Applications of Dielectric Materials
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages372-375
Number of pages4
ISBN (Print)1424401895, 9781424401895
DOIs
Publication statusPublished - 2006 Jan 1
EventICPADM 2006 - 8th International Conference on Properties and Applications of Dielectric Materials - Bali, Indonesia
Duration: 2006 Jun 262006 Jun 30

Publication series

NameProceedings of the IEEE International Conference on Properties and Applications of Dielectric Materials

Other

OtherICPADM 2006 - 8th International Conference on Properties and Applications of Dielectric Materials
CountryIndonesia
CityBali
Period06-06-2606-06-30

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Materials Chemistry

Fingerprint Dive into the research topics of 'Application of fuzzy c-means clustering approach to partial discharge pattern recognition of cast-resin current transformers'. Together they form a unique fingerprint.

Cite this