• DocumentCode
    336225
  • Title

    Adaptive power-line disturbance detection scheme using a prediction error filter and a stop-and-go CA CFAR detector

  • Author

    Chung, Jaehak ; Powers, Edward J. ; Grady, W. Mack ; Bhatt, Sid C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
  • Volume
    3
  • fYear
    1999
  • fDate
    15-19 Mar 1999
  • Firstpage
    1533
  • Abstract
    This paper presents a new power-line disturbance detection algorithm. The utilized recursive least square (RLS) prediction error filter extracts the power-line disturbance signal from recorded data, and the modified stop-and-go cell average constant false alarm rate (CA CFAR) detector makes a decision based on the squared output of the previous stage. The detection performance of the proposed algorithm is determined by simulations, and actual high voltage transmission line data is utilized to demonstrate the performance of the proposed algorithm
  • Keywords
    adaptive filters; adaptive signal detection; filtering theory; least squares approximations; power transmission faults; power transmission lines; prediction theory; recursive filters; RLS prediction error filter; adaptive power-line disturbance detection; algorithm; cell average constant false alarm rate; detection performance; harmonics; high voltage transmission line data; prediction error filter; recorded data; recursive least square prediction error filter; sag disturbance data; simulations; squared output; stop-and-go CA CFAR detector; voltage sag detection; Adaptive filters; Adaptive signal detection; Computer errors; Detection algorithms; Detectors; Electrical fault detection; Power harmonic filters; Power system harmonics; Predictive models; Voltage fluctuations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
  • Conference_Location
    Phoenix, AZ
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-5041-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1999.756277
  • Filename
    756277