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Wavelet-Based Algorithm for Signal Analysis

Abstract

This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform (CWT) using the complex Morlet wavelet (CMW) is adopted to detect the harmonics presented in a power signal. A frequency detection algorithm is developed from the wavelet scalogram and ridges. A necessary condition is established to discriminate adjacent frequencies. The instantaneous frequency identification approach is applied to determine the frequencies components. An algorithm based on the discrete stationary wavelet transform (DSWT) is adopted to denoise the wavelet ridges. Experimental work has been used to demonstrate the superiority of this approach as compared to the more conventional one such as the fast Fourier transform.

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Correspondence to Norman C.F. Tse.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Tse, N.C., Lai, L. Wavelet-Based Algorithm for Signal Analysis. EURASIP J. Adv. Signal Process. 2007, 038916 (2007). https://doi.org/10.1155/2007/38916

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Keywords

  • Fast Fourier Transform
  • Detection Algorithm
  • Frequency Component
  • Identification Approach
  • Power Signal