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

Open Access 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.


  1. IEEE recommended practice for monitoring electric power quality IEEE Standards Board, June 1995

  2. LL Lai, WL Chan, CT Tse, ATP So, Real-time frequency and harmonic evaluation using artificial neural networks. IEEE Transactions on Power Delivery 14(1), 52–59 (1999). Publisher Full Text OpenURL

  3. WL Chan, ATP So, LL Lai, Harmonics load signature recognition by wavelets transforms. Proceedings of International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT '00), April 2000, London, UK, 666–671 (IEEE Catalog no), . 00EX382 OpenURL

  4. NCF Tse, Practical application of wavelet to power quality analysis. Proceedings of IEEE Power Engineering Society General Meeting, June 2006, Montreal, Quebec, Canada, 5 (IEEE Catalogue no), . 06CH37818C, CD ROM OpenURL

  5. PS Addison, The Illustrated Wavelet Transform Handbook (Institute of Physics, Bristol, UK, 2002)

  6. VL Pham, KP Wong, Wavelet-transform-based algorithm for harmonic analysis of power system waveforms. IEE Proceedings: Generation, Transmission and Distribution 146(3), 249–254 (1999). Publisher Full Text OpenURL

  7. G Strang, T Nguyen, Wavelets and Filter Banks (Wellesley-Cambridge, Wellesley, Mass, USA, 1996)

  8. S-J Huang, C-T Hsieh, C-L Huang, Application of Morlet wavelets to supervise power system disturbances. IEEE Transactions on Power Delivery 14(1), 235–241 (1999). Publisher Full Text OpenURL

  9. A Teolis, Computational Signal Processing with Wavelets (Birkhäuser, Boston, Mass, USA, 1998)

  10. M Misiti, Y Misiti, G Oppenheim, Wavelet Toolbox for Use with Matlab (The Mathworks, Natick, Mass, USA, 1996)

  11. S Mallet, A Wavelet Tour of Signal Processing (Academic Press, San Diego, Calif, USA, 1998)

  12. RA Carmona, WL Hwang, B Torrésani, Multiridge detection and time-frequency reconstruction. IEEE Transactions on Signal Processing 47(2), 480–492 (1999). Publisher Full Text OpenURL

  13. RA Carmona, WL Hwang, B Torresani, Characterization of signals by the ridges of their wavelet transforms. IEEE Transactions on Signal Processing 45(10), 2586–2590 (1997). Publisher Full Text OpenURL

  14. Antoniadis A, Oppenheim G (eds.), Wavelets and Statistics, Lecture Notes in Statistics (Springer, New York, NY, USA, 1995)