Title :
Power Quality Disturbance Recognition Using Wavelet-Based Neural Networks
Author :
Kaewarsa, S. ; Attakitmongcol, K.
Author_Institution :
Sch. of Electr. Eng., Rajamangala Univ. of Technol. Isan, Sakon Nakhon
Abstract :
This paper proposes a wavelet-based neural network classifier for recognizing power quality disturbances is implemented and tested under various transient events. The discrete wavelet transform technique is integrated with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, the results show that the classier can detect and classify different power quality disturbance types efficiency.
Keywords :
discrete wavelet transforms; neural nets; power supply quality; power system faults; vector quantisation; discrete wavelet transform; learning vector quantization network; power quality disturbance recognition; wavelet-based neural network classifier; Continuous wavelet transforms; Discrete wavelet transforms; Event detection; Neural networks; Power quality; Power system transients; Signal resolution; Voltage fluctuations; Wavelet domain; Wavelet transforms;
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
DOI :
10.1109/TENCON.2005.301264