• DocumentCode
    2983374
  • Title

    Analysis of the voltage event segmentation using Kaiman filter and Wavelet Transform

  • Author

    Ortiz, L.S. ; Torres S, H. ; Barrera, V. ; Duarte, C. ; Ordònez, G. ; Herraiz, S.

  • Author_Institution
    Electron. & Electr. Eng., Ind. Univ. of Santander (UIS), Colombia
  • fYear
    2010
  • fDate
    15-17 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper Kalman filter and Wavelet transform (DWT) are compared in voltage event segmentation. The waveform segmentation is required to detect stationary and non-stationary stages throughout the voltage event waveforms. This detection plays an important role in the features extraction process since some features must be computed during stationary stages and other in non-stationary ones. The comparison is carried out using field measurements, which have been previously segmented through a visual inspection. The third and fourth states of the Kalman filter as well as the voltage fundamental component have been used in the waveform segmentation process. Kalman- and DWT-based segmentation results are compared and their advantages and drawbacks are discussed.
  • Keywords
    adaptive Kalman filters; discrete wavelet transforms; feature extraction; inspection; Kalman filter; features extraction; nonstationary stages; visual inspection; voltage event segmentation; waveform segmentation; wavelet transform; Covariance matrix; Discrete wavelet transforms; Harmonic analysis; Kalman filters; Power harmonic filters; Time frequency analysis; Adaptive Kaiman filtering; covariance matrices; discrete wavelet transforms; power quality; waveform segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ANDESCON, 2010 IEEE
  • Conference_Location
    Bogota
  • Print_ISBN
    978-1-4244-6740-2
  • Type

    conf

  • DOI
    10.1109/ANDESCON.2010.5630052
  • Filename
    5630052