Abrupt change detection in power system fault analysis using adaptive whitening filter and wavelet transform

Abhisek Ukil, Rastko Živanović

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)

Abstract

This paper describes the application of the adaptive whitening filter and the wavelet transform used to detect the abrupt changes in the signals recorded during disturbances in the electrical power network in South Africa. Main focus has been to estimate exactly the time-instants of the changes in the signal model parameters during the pre-fault condition and following events like initiation of fault, circuit-breaker opening, auto-reclosure of the circuit-breakers. The key idea is to decompose the fault signals, de-noised using the adaptive whitening filter, into effective detailed and smoothed version using the multiresolution signal decomposition technique based on discrete wavelet transform. Then we apply the threshold method on the decomposed signals to estimate the change time-instants, segmenting the fault signals into the event-specific sections for further signal processing and analysis. This paper presents application on the recorded signals in the power transmission network of South Africa.

Original languageEnglish
Pages (from-to)815-823
Number of pages9
JournalElectric Power Systems Research
Volume76
Issue number9-10
DOIs
Publication statusPublished - Jun 2006
Externally publishedYes

Keywords

  • Abrupt change detection
  • Adaptive whitening filter
  • Power system fault analysis
  • Wavelet transform

Fingerprint

Dive into the research topics of 'Abrupt change detection in power system fault analysis using adaptive whitening filter and wavelet transform'. Together they form a unique fingerprint.

Cite this