Suppressing white‐noise in partial discharge measurements—part 1: construction of complex Daubechies wavelet and complex threshold

Online partial discharge (PD) detection still remains a very challenging task because of the strong electromagnetic interferences. In this paper, a new method of de-noising, using complex Daubechies wavelet (CDW) transform, has been proposed. It is a relatively recent enhancement to the real-valued wavelet transform because of two important properties, which are nearly shift invariant and availability of phase information. Those properties give CDW transform superiority over other real-valued wavelet transform. On the basis of CDW transform, complex threshold algorithm and combined information are devised. In order to take into account the difference of the real part and imaginary part of complex wavelet coefficients, complex threshold is devised to modify the real part and imaginary part respectively. Because the restored signal by inverse CDW transform is complex one, combined information is devised to combine the real part and imaginary part of complex signal to construct a real one, furthermore making full use of the simple information from complex signal. Copyright © 2009 John Wiley & Sons, Ltd.

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