• DocumentCode
    3560764
  • Title

    DSP Wavelet-Based Tool for Monitoring Transformer Inrush Currents and Internal Faults

  • Author

    Gaouda, A.M. ; Salama, M.M.A.

  • Author_Institution
    Dept. of Electr. Eng., United Arab Emirates Univ., Al-Ain, United Arab Emirates
  • Volume
    25
  • Issue
    3
  • fYear
    2010
  • fDate
    7/1/2010 12:00:00 AM
  • Firstpage
    1258
  • Lastpage
    1267
  • Abstract
    This paper proposes a wavelet-based technique for monitoring nonstationary variations in order to distinguish between transformer inrush currents and transformer internal faults. The proposed technique utilizes a small set of coefficients of the local maxima that represent most of the signal´s energy: only one coefficient at each resolution level is utilized to measure the magnitude of the variation in the signal. The data is processed while sliding through a Kaiser window and the technique has been applied in the laboratory as well as with simulated data, producing excellent results.
  • Keywords
    condition monitoring; electrical faults; power transformers; signal processing; wavelet transforms; DSP wavelet-based tool; Kaiser window; internal faults; nonstationary variations monitoring; power transformer; transformer inrush current monitoring; transformer internal faults; wavelet transform; wavelet-based technique; Inrush current; Kaiser window; internal faults; multiresolution analysis; transformer; wavelet transform;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • Conference_Location
    6/1/2010 12:00:00 AM
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2010.2046653
  • Filename
    5475361