Arc Fault and Flash Signal Analysis in DC Distribution Systems Using Wavelet Transformation

Zhan Wang, Robert Balog

Research output: Contribution to journalArticle

53 Citations (Scopus)


Arc faults have always been a concern for electrical systems, as they can cause fires, personnel shock hazard, and system failure. Existing commercialized techniques that rely on pattern recognition in the time domain or frequency domain analysis using a Fourier transform do not work well, because the signal-to-noise ratio is low and the arc signal is not periodic. Instead, wavelet transform (WT) provides a time and frequency approach to analyze target signals with multiple resolutions. In this paper, a new approach using WT for arc fault analysis in dc systems is proposed. The process of detecting an arc fault involves signal analysis and then feature identification. The focus of this paper is on the former. Simulation models are synthesized to study the theoretical results of the proposed methodology and traditional fast Fourier transform analysis on arcing faults. Experimental data from the dc system of a photovoltaic array is also shown to validate the approach.

Original languageEnglish
Article number7063248
Pages (from-to)1955-1963
Number of pages9
JournalIEEE Transactions on Smart Grid
Issue number4
Publication statusPublished - 1 Jul 2015



  • Arc fault analysis
  • Arc flash
  • dc distribution
  • dc microgrid safety
  • Signal processing
  • Wavelet transform (WT)

ASJC Scopus subject areas

  • Computer Science(all)

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