Power-Quality Disturbance Recognition Using S-Transform

Taking advantage of S-transforms (STs), this paper proposes a new method of detecting and classifying power-quality disturbances. The ST is unique in that it provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. The features obtained from ST 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 ST-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

[1]  P. K. Dash,et al.  Power Quality Disturbance Data Compression, Detection, and Classification Using Integrated Spline Wavelet and S-Transform , 2002, IEEE Power Engineering Review.

[2]  P.K. Dash,et al.  Multiresolution S-transform-based fuzzy recognition system for power quality events , 2004, IEEE Transactions on Power Delivery.

[3]  Zhao Rong,et al.  FFT Algorithm with High Accuracy for Harmonic Analysis in Power System , 2006 .

[4]  Pradipta Kishore Dash,et al.  S-transform-based intelligent system for classification of power quality disturbance signals , 2003, IEEE Trans. Ind. Electron..

[5]  Zwe-Lee Gaing,et al.  Wavelet-based neural network for power disturbance recognition and classification , 2004, IEEE Transactions on Power Delivery.

[6]  Lalu Mansinha,et al.  Localization of the complex spectrum: the S transform , 1996, IEEE Trans. Signal Process..

[7]  Ding Yi-feng,et al.  S-TRANSFORM-BASED CLASSIFICATION OF POWER QUALITY DISTURBANCE SIGNALS BY SUPPORT VECTOR MACHINES , 2005 .

[8]  E.F. El-Saadany,et al.  Disturbance classification utilizing dynamic time warping classifier , 2004, IEEE Transactions on Power Delivery.

[9]  G. Panda,et al.  Power Quality Analysis Using S-Transform , 2002, IEEE Power Engineering Review.

[10]  M. Kezunovic,et al.  A Novel Software Implementation Concept for Power Quality Study , 2001, IEEE Power Engineering Review.

[11]  Chen Xue-yun,et al.  Fractal exponent wavelet analysis of dynamic power quality , 2004 .