Fault classification in transformer using low frequency component

Chaiyan Jettanasen, Atthapol Ngaopitakkul*, Dimas Anton Asfani, I. Made Yulistya Negara

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Transform is a vital equipment in power system that need protection system in order to provide fast and correct response when disturbance occur in system. So, this paper proposed internal and external fault classification in Transformer using algorithm based on discrete wavelet transform (DWT). Low frequency component from DWT has been used to create condition for algorithm. The proposed algorithm has been test using transmission line connected to transformer experimental setup on laboratory level. The result from proposed algorithm shown satisfactory result with 100% accuracy in both internal and external fault in transmission line connected transformer system.

Original languageEnglish
Title of host publication2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages199-202
Number of pages4
ISBN (Electronic)9781538604694
DOIs
Publication statusPublished - 13 Dec 2017
Event10th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Hiroshima, Japan
Duration: 11 Nov 201712 Nov 2017

Publication series

Name2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings
Volume2017-December

Conference

Conference10th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2017
Country/TerritoryJapan
CityHiroshima
Period11/11/1712/11/17

Keywords

  • Discrete Wavelet Transform
  • Fault
  • Transformer
  • Transmission Line

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