A Novel Method of Selecting Complex Wavelet for Feature Extraction in Partial Discharge Signal Processing

Author

Cui, Xuemei ; Huang, Tingwen

Author_Institution

Chengdu Univ. of Inf. Technol., Chengdu

Volume

1

fYear

2008

fDate

27-30 May 2008

Firstpage

128

Lastpage

131

Abstract

This paper presents an efficient method for selecting optimal complex wavelet from a family of wavelets for feature extraction in partial discharge signal (PDS) processing. The optimal wavelet can be used to extract features of PDS from signals with strong disturbance and noise. Specifically, the optimal complex wavelet is selected based on the phase-spectrum similarity between the wavelet and the PDS. The simulation results show that the selected optimal wavelet cansignificantly improve the PDS feature extraction. This capability has potential to improve the accuracy of real-time monitoring of PDS in power systems.

Keywords

feature extraction; partial discharges; power system faults; real-time systems; signal processing; wavelet transforms; complex wavelet selection; feature extraction; partial discharge signal processing; phase-spectrum similarity; real-time power system monitoring; Feature extraction; Information analysis; Monitoring; Partial discharges; Power system analysis computing; Power system simulation; Real time systems; Signal processing; Wavelet analysis; Wavelet coefficients; complex wavelet; partial discharge signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing, 2008. CISP '08. Congress on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3119-9

Type

conf

DOI

10.1109/CISP.2008.787

Filename

4566132