Wavelet-based denoising of partial discharge signals buried in excessive noise and interference
作者： L. Satish , B. Nazneen
DOI: 10.1109/TDEI.2003.1194122
关键词: Infinite impulse response 、 Signal processing 、 Control theory 、 Wavelet transform 、 Digital filter 、 Noise reduction 、 Noise (signal processing) 、 Finite impulse response 、 Computer science 、 Acoustics 、 Wavelet
摘要: Achieving acceptable levels of sensitivity during online and/or onsite partial discharge (PD) measurements still continues to remain a very challenging task, primarily due strong coupling external (random, discrete spectral and stochastic pulsive) interferences. Many analog digital approaches have been proposed for suppressing these interferences, amongst these, rejection the pulsive type interferences is known be difficult, if not impossible. The time frequency characteristics interference being similar that PD pulses main reason posing difficulty in their separation. In this paper, novel, semi-automatic, empirical wavelet-based method (using multi-resolution signal analysis) recover pulses, buried excessive noise/interference comprising random, spectral, pulsive, any combination occurring simultaneously overlapping-in-time with pulses. A critical assessment carried out, by processing both simulated practically acquired signals. results obtained are also compared those from best filter (infinite impulse response, IIR finite FIR) literature. From it emerges that, wavelet approach superior further, has unique capability successfully rejecting all three kinds even when signals one or occur overlap-in-time.
sci-hub.se 参考文章(14)
G. Konig, J. Ott, P. Seitz, K. Feser, An adaptive filter algorithm for on-site partial discharge measurements ieee international symposium on electrical insulation. pp. 242- 245 ,(1988) , 10.1109/ELINSL.1988.13914
Q. Su, Application of digital signal processing techniques for noise suppression in partial discharge measurements ieee international conference on properties and applications of dielectric materials. ,vol. 2, pp. 602- 605 ,(1994) , 10.1109/ICPADM.1994.414082
K. Arii, M. Shibahara, M. Fujii, Separation of noise from partial discharge signals by wavelet ieee international conference on properties and applications of dielectric materials. ,vol. 1, pp. 232- 235 ,(1997) , 10.1109/ICPADM.1997.617570
G.C. Stone, Partial discharge. VII. Practical techniques for measuring PD in operating equipment IEEE Electrical Insulation Magazine. ,vol. 7, pp. 9- 19 ,(1991) , 10.1109/57.87656
I Shim, J J Soraghan, W H Siew, A noise reduction technique for on-line detection and location of partial discharges in high voltage cable networks Measurement Science and Technology. ,vol. 11, pp. 1708- 1713 ,(2000) , 10.1088/0957-0233/11/12/309
M. Florkowski, Wavelet based partial discharge image de-noising 11th International Symposium on High-Voltage Engineering (ISH 99). ,vol. 5, pp. 21- 24 ,(1999) , 10.1049/CP:19990876
I. Shim, J.J. Soraghan, W.H. Siew, Detection of PD utilizing digital signal processing methods. Part 3: Open-loop noise reduction IEEE Electrical Insulation Magazine. ,vol. 17, pp. 6- 13 ,(2001) , 10.1109/57.901611
Wang Hang, Tan Kexiong, Zhu Deheng, Extraction of partial discharge signals using wavelet transform ieee international conference on properties and applications of dielectric materials. ,vol. 1, pp. 322- 325 ,(1997) , 10.1109/ICPADM.1997.617593
Yusheng Quan, Ning Gao, Guanjun Zhang, Zhang Yan, Wavelet transform applying in partial discharge measurement ieee international symposium on electrical insulation. ,vol. 2, pp. 428- 431 ,(1998) , 10.1109/ELINSL.1998.694825
G. Zingales, The requirements of a PD measuring system analyzed in the time domain IEEE Transactions on Dielectrics and Electrical Insulation. ,vol. 7, pp. 2- 5 ,(2000) , 10.1109/94.839334