Study The Method For Suppress Denoise In Partial Discharge Signal Of Transformer Using Wavelet Technique

Because power transformer in electric power system is one of the best key equipments, on-line partial discharge (PD) monitoring of power transformer to prevent insulation paroxysmal accident of power transformer has very important value and has become a hotspot in research. Field acquisition PD signal has the strong interferences Because of a great amount of electromagnetic interferences in operational circumstance of power transformer. So it is a key and difficult issue to obtain the PD signal for a PD monitoring system and it is prerequisite and foundation to pattern recognition. Aiming at this technical problem, the main contents of this thesis is presented as follows:This paper introduces the characteristics of PD signal and periodical narrow bandwidth noise in time domain and frequency domain. At the same time, this paper studies the theory of the self-adapting filter suppressing periodical narrow bandwidth noise in PD signal and analysis that different parameters of self-adapting filter how to affect the filtering results. The shortage of self-adapting filter is discussed. Then the essence thoughts and advantages of wavelet packet transform (WPT) are introduced. WPT is applied in self-adapting filter and the new algorithm to suppress periodical narrow bandwidth noise is introduced, which combine the advantages of WPT and self-adapting filter.This paper study the theory and method about spatially selective noise filtration technique and analysis the shortages of this technique. Basing on the discrimination coefficient and the iterative stop coefficient, which are put forwarded in this paper, improved spatially selective noise filtration technique to suppress white noise is put forwarded. A Trous algorithm in wavelet theory is discussed and applied in improved spatially selective noise filtration technique.This paper introduces the wavelet transform characteristics of PD and white noise in power transformer and study the theory about algorithm of wavelet threshold to suppress white noise in PD. The error energy about PD signal and wavelet signal is discussed, and then deduce the related coefficientsρfψbased on the error energy. Optimal wavelet of different PD signal is obtained by comparing the value ofρfψ.The 3σrule to threshold value choice is put forward by using probability method. Based on the 3σrule and WPT, the author presents WPT composite threshold values technique to suppress white-noise in PD signal. At last the contrast between WPT composite threshold values technique and spatially selective noise filtration technique, indicate that two methods have advantages and shortages.The theoretical analysis, experimental research, and the on-site measured PD signal de-noising examples, are used to qualify our proposed methods. Research proved that proposed methods are good technology for on-line partial discharge (PD) monitoring of power transformer.