High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion

T. M. Lai, L. A. Snider, Wai Chau Edward Lo, D. Sutanto

Research output: Journal article publicationJournal articleAcademic researchpeer-review

180 Citations (Scopus)


High-impedance faults (HIFs) are faults which are difficult to detect by overcurrent protection relays. Various pattern recognition techniques have been suggested, including the use of Wavelet Transform 1. However this method cannot indicate the physical properties of output coefficients using the wavelet transform. In this paper we propose to use the Discrete Wavelet Transform (DWT) as well as frequency range and rms conversion to apply a pattern recognition based detection algorithm for electric distribution high impedance fault detection. The aim is to recognize the converted rms voltage and current values caused by arcs usually associated with HIF. The analysis using Discrete Wavelet Transform (DWT) with the conversion yields measurement voltages and currents which are fed to a classifier for pattern recognition. The classifier is based on the algorithm using nearest neighbor rule approach. It is proposed that this method can function as a decision support software package for HIF identification which could be installed in an alarm system.
Original languageEnglish
Pages (from-to)397-407
Number of pages11
JournalIEEE Transactions on Power Delivery
Issue number1
Publication statusPublished - 1 Jan 2005


  • High-impedance faults (HIFs)
  • Pattern recognition
  • Wavelet transform

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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