Disturbance Classification Utilizing Dynamic Time Warping Classifier

A. M. Youssef, T. K. Abdel-Galil, E. F. El-Saadany, M. M.A. Salama

Research output: Contribution to journalArticlepeer-review

105 Scopus citations


The application of deregulation policies in electric power systems results in the absolute necessity to quantify power quality. This fact highlights the need for a new classification strategy which is capable of tracking, detecting, and classifying power-quality events. In this paper, a new classification approach that is based on the dynamic time warping (DTW) algorithm is proposed. The new algorithm is supported by the vector quantization (VQ) and the fast match (FM) techniques to speed up the classification process. The Walsh transform (WT) and the fast Fourier transform (FFT) are adopted as feature extraction tools. The application of the combined fast match-dynamic time warping (FM-DTW) algorithms provides superior results in speed and accuracy compared to the traditional artificial neural networks and fuzzy logic classifiers. Moreover, the proposed classifier proves to have a very low sensitivity to noise levels.

Original languageBritish English
Pages (from-to)272-278
Number of pages7
JournalIEEE Transactions on Power Delivery
Issue number1
StatePublished - Jan 2004


  • Dynamic time warping
  • Pattern classification
  • Power quality
  • Vector quantization
  • Walsh transform


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