Db复小波在超高频局部放电测量中的应用(英文)

On-line 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 tow important properties,which are nearly shift-invariant and availability of phase information.Those properties give CDW transform superiority over other real-valued wavelet transform,and then the construction algorithm of CDW is introduced in detail.Secondly,based on the real threshold algorithm of real-valued wavelet transform,complex threshold algorithm is devised.This algorithm take the different characteristics of real part and imaginary part of complex wavelet coefficients into account,it modifies the real and imaginary parts of complex wavelet coefficients respectively.Thirdly,to obtain a real de-noised signal,new combined information series is devised.By applying different combination of real part and imaginary part of de-noised complex signal,a real de-noised signal can be restored with higher peak signal-to-noise ratio(PSNR)and less distortion of original signals.Finally,On-site applications of extracting PD signals from noisy background by the optimal de-noising scheme based on CDW are illustrated.The on-site experimental results show that the optimal de-noising scheme is an effective way to suppress white noise in PD measurement.

Application of Complex Daubechies Wavelet in UHF Partial Discharge Measurements

On-line 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 tow important properties, which are nearly shift-invariant and availability of phase information. Those properties give CDW transform superiority over other real-valued wavelet transform, and then the construction algorithm of CDW is introduced in detail. Secondly, based on the real threshold algorithm of real-valued wavelet transform, complex threshold algorithm is devised. This algorithm take the different characteristics of real part and imaginary part of complex wavelet coefficients into account, it modifies the real and imaginary parts of complex wavelet coefficients respectively. Thirdly, to obtain a real de-noised signal, new combined information series is devised. By applying different combination of real part and imaginary part of de-noised complex signal, a real de-noised signal can be restored with higher peak signal-to-noise ratio (PSNR) and less distortion of original signals. Finally, On-site applications of extracting PD signals from noisy background by the optimal de-noising scheme based on CDW are illustrated. The on-site experimental results show that the optimal de-noising scheme is an effective way to suppress white noise in PD measurement.