• DocumentCode
    2681108
  • Title

    Power quality disturbance recognition using S-transform

  • Author

    Zhao, Fengzhan ; Yang, Rengang

  • Author_Institution
    Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing
  • fYear
    0
  • fDate
    0-0 0
  • Abstract
    Taking advantage of S-transform(ST), the paper proposes a new method of detecting and classifying power quality disturbances. The S-transform is unique in that it provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. The features obtained from S-transform are distinct, understandable and immune to noise. According to a rule-based decision tree, eight types of single power disturbance and two types of complex power disturbance are well recognized, and there is no need to use other complicated classifiers. The comparison between the wavelet-transform-based method and the S-transform-based method for power quality disturbance recognition is also provided. The simulation results show that the proposed method is effective and immune against noise. The proposed method is feasible and promising for real applications
  • Keywords
    Fourier transforms; pattern recognition; power supply quality; wavelet transforms; Fourier spectrum; S-transform; complex power disturbance; power quality disturbance recognition; rule-based decision tree; single power disturbance; wavelet-transform-based method; Artificial neural networks; Continuous wavelet transforms; Decision trees; Feature extraction; Frequency; Fuzzy logic; Pattern recognition; Power quality; Voltage fluctuations; Voltage-controlled oscillators; Multiresolution analysis; S-transform; pattern recognition; power quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2006. IEEE
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    1-4244-0493-2
  • Type

    conf

  • DOI
    10.1109/PES.2006.1709411
  • Filename
    1709411