Recognizing Noise-Influenced Power Quality Events With Integrated Feature Extraction and Neuro-Fuzzy Network

The wavelet transform coefficients (WTCs) contain plenty of information needed for transient signal identification of power quality (PQ) events. However, once the power signals under investigation are corrupted by noises, the performance of the wavelet transform (WT) on detecting and recognizing PQ...

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Veröffentlicht in:	IEEE transactions on power delivery 2009-10, Vol.24 (4), p.2132-2141
Hauptverfasser:	LIAO, Chiung-Chou, YANG, Hong-Tzer
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Degradation Disturbances. Regulation. Protection Electrical engineering. Electrical power engineering Electrical power engineering Event detection Exact sciences and technology Feature extraction Fuzzy Fuzzy logic Fuzzy neural networks Fuzzy systems Miscellaneous Neural networks neuro-Fuzzy network Noise Noise reduction noise-suppression Operation. Load control. Reliability Power electronics, power supplies Power networks and lines Power quality Power system transients Recognition Riding Signal processing wavelet transform Wavelet transforms
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