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This article is part of the series Emerging Signal Processing Techniques for Power Quality Applications.

Open Access Open Badges Research Article

Wavelet-Based Algorithm for Signal Analysis

Norman CF Tse1* and LL Lai2

Author Affiliations

1 Division of Building Science and Technology, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

2 School of Engineering and Mathematical Sciences, City University, Northampton Square, London EC1V0HB, UK

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EURASIP Journal on Advances in Signal Processing 2007, 2007:038916  doi:10.1155/2007/38916

The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2007/1/038916

Received:6 August 2006
Revisions received:12 October 2006
Accepted:24 November 2006
Published:10 January 2007

© 2007 Tse and Lai

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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