Wavelet-Based Algorithm for Signal Analysis
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Research Article Wavelet-Based Algorithm for Signal Analysis Norman C. F. Tse1 and L. L. Lai2 1 Division 2 School
of Building Science and Technology, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong of Engineering and Mathematical Sciences, City University, Northampton Square, London EC1V0HB, UK
Received 6 August 2006; Revised 12 October 2006; Accepted 24 November 2006 Recommended by Irene Y. H. Gu This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using waveletbased 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. Copyright © 2007 N. C. F. Tse and L. L. 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.
1.
INTRODUCTION
Power quality has become a major concern for utility, facility, and consulting engineers in recent years. International as well as local standards have been formulated to address the power quality issues [1]. To the facility managers and end users, frequent complaints by tenants/customers on occasional power failures of computer and communication equipment and the energy inefficiency of the LV electrical distribution system are on the management’s agenda. Harmonic currents produced by nonlinear loads would cause extra copper loss in the distribution network, which on one hand will increase the energy cost and on the other hand would increase the electricity tariff charge. The benefits of using power electronic devices in the LV distribution system in buildings, such as switch mode power supplies, variable speed drive units, to save energy are sometimes offset by the increased energy loss in the distribution cables by current harmonics and the cost of remedial measures required. Voltage harmonics caused by harmonic voltage drops in the distribution cables are affecting the normal operation of voltage-sensitive equipment as well. In order to improve electric power quality and energy efficiency, the sources and causes of such disturbance must be known on demand sides before appropriate corrective or mitigating actions can be taken [2, 3].
A traditional approach is to use discrete Fourier transform (DFT) to analyze harmonics contents of a power signal. The DFT which is implemented by FFT has many attractive features. That theory of FFT
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