Pattern recognition applications for power system disturbance classification |
| |
Authors: | Gaouda AM Kanoun SH Salama MMA Chikhani AY |
| |
Affiliation: | Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont.; |
| |
Abstract: | This paper presents an automated online disturbance classification technique. This technique is based on wavelet multiresolution analysis and pattern recognition techniques. The wavelet-multiresolution transform is introduced as a powerful tool for feature extraction in order to classify different disturbances. Minimum Euclidean distance, k-nearest neighbor, and neural network classifiers are used to evaluate the efficiency of the extracted features. |
| |
Keywords: | |
|
|