A method based on independent component analysis for single and multiple power quality disturbance classification

Abstract This paper proposes a method based on single channel independent component analysis for single and multiple power quality disturbance classification. The proposed method decouples the power system signal into its independent components, which are classified by specialized classifiers. The classifier outputs are combined by using a logic that gives the final classification. Five classes of single disturbances and twelve of multiple disturbances are considered and a classification efficiency above 97% is achieved for each event class. Both qualitative and quantitative analysis elucidate the efficiency of the proposed method. Results are obtained from both simulated and experimental signals.

[1]  Carlos A. Duque,et al.  Exploiting principal curves for power quality monitoring , 2013 .

[2]  Abdelazeem A. Abdelsalam,et al.  Classification of power system disturbances using linear Kalman filter and fuzzy-expert system , 2012 .

[3]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[4]  Pradipta Kishore Dash,et al.  A hybrid ant colony optimization technique for power signal pattern classification , 2011, Expert Syst. Appl..

[5]  Pradipta Kishore Dash,et al.  Measurement and Classification of Simultaneous Power Signal Patterns With an S-Transform Variant and Fuzzy Decision Tree , 2013, IEEE Transactions on Industrial Informatics.

[6]  Mohammad A. S. Masoum,et al.  Detection and classification of power quality disturbances using discrete wavelet transform and wavelet networks , 2010 .

[7]  Rajiv Kapoor,et al.  Classification of power quality events – A review , 2012 .

[8]  Ali Enshaee,et al.  Detection and classification of single and combined power quality disturbances using fuzzy systems oriented by particle swarm optimization algorithm , 2010 .

[9]  Augusto S. Cerqueira,et al.  ICA-Based Method for Power Quality Disturbance Analysis , 2009, 2009 15th International Conference on Intelligent System Applications to Power Systems.

[10]  M.E. Davies,et al.  Source separation using single channel ICA , 2007, Signal Process..

[11]  Moisés Vidal Ribeiro,et al.  Classification of Single and Multiple Disturbances in Electric Signals , 2007, EURASIP J. Adv. Signal Process..

[12]  E. Oja,et al.  Independent Component Analysis , 2013 .

[13]  José G. M. S. Decanini,et al.  Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network , 2011 .

[14]  Ming Zhang,et al.  A real-time classification method of power quality disturbances , 2011 .

[15]  Hyoung Joong Kim,et al.  Knowledge-Assisted Media Analysis for Interactive Multimedia Applications , 2007, EURASIP J. Adv. Signal Process..

[16]  M. Karimi-Ghartemani,et al.  Robust and frequency-adaptive measurement of peak value , 2004, IEEE Transactions on Power Delivery.

[17]  Carlos A. Duque,et al.  HOS-based method for classification of power quality disturbances , 2009 .