• DocumentCode
    2103083
  • Title

    An enhanced data compression method for applications in power quality analysis

  • Author

    Ribeiro, Moisés V. ; Romano, João Marcos T ; Duque, Carlos A.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Univ. Estadual de Campinas, Sao Paulo, Brazil
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    676
  • Abstract
    This paper presents an enhanced method for data compression using a wavelet transform, to be applied in power systems signals for quality evaluation. The proposed approach is based on a previous estimation of the sinusoidal components of the signal under analysis, so that it could be subtracted from the original data in order to generate a transient type signal, which is subsequently applied to the compression techniques. The approach employs the Kalman filter and the adaptive notch filter techniques to provide the estimation of the sinusoidal components. Taking into account the wavelet property of sparse representation makes an improvement in the compression rate and in the signal degradation is attained. Finally, a proposed frame format to store the coded signal is presented
  • Keywords
    Kalman filters; adaptive filters; data compression; notch filters; power supply quality; wavelet transforms; Kalman filter; adaptive notch filter techniques; amplitude estimation; coded signal; enhanced data compression method; frequency estimation; phase estimation; power quality analysis; power systems signals; sinusoidal components; sinusoidal components estimation; sparse representation; transient type signal generation; wavelet transform; Adaptive filters; Data compression; Power engineering and energy; Power quality; Power system analysis computing; Power system transients; Signal analysis; Signal generators; Transient analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
  • Conference_Location
    Denver, CO
  • Print_ISBN
    0-7803-7108-9
  • Type

    conf

  • DOI
    10.1109/IECON.2001.976594
  • Filename
    976594