Title :
Wavelet-based intelligent system for monitoring non-stationary disturbances
Author :
Gaouda, A.M. ; Kanoun, S.H. ; Salama, M.M.A. ; Chikhani, A.Y.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Abstract :
This paper presents a wavelet-based procedure that will assist in automated detecting, classifying, and measuring of different power system disturbances. Two pattern recognition techniques are used to evaluate the efficiency of the features of the nonstationary signal in the wavelet domain. The paper also presents a new technique that can monitor the variations of the RMS value and any further changes in the nonstationary signal
Keywords :
computerised monitoring; feature extraction; pattern recognition; power system faults; power system measurement; wavelet transforms; RMS value; nonstationary disturbances monitoring; nonstationary signal features; pattern recognition techniques; power system disturbances; wavelet domain; wavelet-based intelligent system; Computerized monitoring; Distortion measurement; Feature extraction; Intelligent systems; Power engineering computing; Power measurement; Power system measurements; Signal resolution; Wavelet analysis; Wavelet domain;
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2000. Proceedings. DRPT 2000. International Conference on
Conference_Location :
London
Print_ISBN :
0-7803-5902-X
DOI :
10.1109/DRPT.2000.855643
