Bilinear time-frequency analysis techniques for power quality signals

Bilinear time-frequency distributions (TFDs) are powerful techniques that offer good time and frequency resolution of time-frequency representation (TFR). It is very appropriate to analyze power quality signals which consist of non-stationary and multi-frequency components. However, the TFDs suffer from interference because of cross-terms. This paper presents the analysis of power quality signals using bilinear TFDs. The chosen TFDs are smooth-windowed Wigner-Ville distribution (SWWVD), Choi-Williams distribution (CWD), B-distribution (BD) and modified B- distribution (MBD). The power quality signals focused are swell, sag, interruption, harmonic, interharmonic and transient based on IEEE Std. 1159-2009. To identify and verify the TFDs that operated at optimal kernel parameters, a set of performance measures are defined and used to compare the TFRs. The performance measures are main-lobe width (MLW), peak-to-side lobe ratio (PSLR), signal-to-cross-terms ratio (SCR) and absolute percentage error (APE). The result shows that SWWVD is the best bilinear TFD and appropriate for power quality signal analysis.

[1]  Braham Barkat,et al.  A high-resolution quadratic time-frequency distribution for multicomponent signals analysis , 2001, IEEE Trans. Signal Process..

[2]  Jo Lynn Tan,et al.  Adaptive Optimal Kernel Smooth-Windowed Wigner-Ville Distribution for Digital Communication Signal , 2008, EURASIP J. Adv. Signal Process..

[3]  Abdul Rahim Abdullah,et al.  Power quality analysis using smooth-windowed wigner-ville distribution , 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).

[4]  Peter J. Schreier A New Interpretation of Bilinear Time-Frequency Distributions , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[5]  Abdul Rahim Bin Abdullah,et al.  Classification of power quality signals using smooth-windowed Wigner-Ville distribution , 2010, 2010 International Conference on Electrical Machines and Systems.

[6]  D.D. Sabin,et al.  Roadmap for Power-Quality Standards Development , 2007, IEEE Transactions on Industry Applications.

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

[8]  A.R. Abdullah,et al.  Power quality analysis using linear time-frequency distribution , 2008, 2008 IEEE 2nd International Power and Energy Conference.

[9]  Rengang Yang,et al.  Power-Quality Disturbance Recognition Using S-Transform , 2007, IEEE Transactions on Power Delivery.

[10]  Zhang Shi,et al.  The research of power quality analysis based on improved S-Transform , 2009, 2009 9th International Conference on Electronic Measurement & Instruments.

[11]  Suttichai Premrudeepreechacharn,et al.  A power quality monitoring system for real-time fault detection , 2009, 2009 IEEE International Symposium on Industrial Electronics.