DocumentCode :
3214416
Title :
A wavelet transform approach to adaptive extraction of partial discharge pulses from interferences
Author :
Zhang, Zhousheng ; Xiao, Dengming ; Liu, Yilu
Author_Institution :
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai
fYear :
2009
fDate :
15-18 March 2009
Firstpage :
1
Lastpage :
7
Abstract :
This paper is concerned with an application of discrete wavelet transform (DWT) to adaptive extraction of partial discharge signals (PDs) from unknown and variable noise. The proposed method can be applied to both on-line energized network (energized with power frequency voltage) and some offline energized network (energized with approximate power frequency voltage). This paper describes an adaptive extraction system (AES) which performs partition of original discrete sequences to more than one time-frames, implements DWT of each time-frame and identifies noise from PDs. AES tunes sets of thresholds according to obtained noise characteristics, and then it modifies DWT coefficients on different scales of DWT to separate noise from PDs. The AES approach produces a significantly improved signal-to-noise ratio (SNR) and almost undistorted partial discharge pulse waveshape at the output of AES. Simulation and experiment studies associated with this AES approach are presented in this paper.
Keywords :
discrete wavelet transforms; electromagnetic interference; insulation testing; partial discharges; power cable insulation; DWT; adaptive extraction system; discrete wavelet transform; electromagnetic interference; partial discharge pulses; power cable insulation assessment; power frequency voltage; signal-to-noise ratio; Discrete wavelet transforms; Frequency; Interference; Partial discharges; Power cable insulation; Power cables; Power system reliability; Signal to noise ratio; Voltage; Wavelet transforms; Adaptive signal detection; Distortion; Electromagnetic interference; Partial discharges; Power cable insulation; Signal decomposition; Signal reconstruction; Time domain analysis; Waveforms; Wavelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-3810-5
Electronic_ISBN :
978-1-4244-3811-2
Type :
conf
DOI :
10.1109/PSCE.2009.4839981
Filename :
4839981
Link To Document :
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