On-line disturbance classification using nearest neighbor rule

This paper presents an automated on-line disturbance classification techniq ue for different power quality problems. This technique is based on wavelet multi-resolution analysis and nearest neighbors pattern recognition method . The wavelet-multi-resolution transform is introduced as a powerful tool f or feature extraction. It has the ability to extract discriminative, transl ation invariant features with small dimensionality in order to classify dif ferent disturbances. The nearest neighbor pattern recognition technique is then implemented to classify different disturbances and evaluate the effici ency of the extracted features. (C) 2001 Elsevier Science S.A. All rights r eserved.