Optimization of wavelet and thresholding for partial discharge detection under HVDC

With the rapid development of HVDC technology, the detection and analysis of partial discharge (PD) under HVDC are new challenges to ensure reliable operation of the related power apparatus. The wavelet technique has been proposed for analyzing PD pulses under HVAC and ultra-high frequency signal, but its application for PD under HVDC has not been discussed. This paper dealt with the selection of the optimal wavelet and thresholding for PD pulses in order to apply the wavelet technique to PD detection under HVDC. Four electrode systems, namely protrusion on conductor, protrusion on enclosure, free particle, and crack inside spacer were fabricated to simulate typical defects in a gas insulated switchgear. The detected PD pulses were decomposed by multiresolution analysis. The correlation coefficient and dynamic time warping methods were used to select the optimal wavelet. The optimal threshold and thresholding function were chosen from various combinations with the simulated pulses. The results revealed that processing PD pulses with the mother wavelet of bior2.6, automatic threshold, and intermediate thresholding function presented the best performance.

[1]  M.D. Judd,et al.  Denoising UHF signal for PD detection in transformers based on wavelet technique , 2004, The 17th Annual Meeting of the IEEE Lasers and Electro-Optics Society, 2004. LEOS 2004..

[2]  Karl Woodbridge,et al.  Radar Micro-Doppler Signature Classification using Dynamic Time Warping , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[3]  C. Zhou,et al.  An improved methodology for application of wavelet transform to partial discharge measurement denoising , 2005, IEEE Transactions on Dielectrics and Electrical Insulation.

[4]  M. R. Petraglia,et al.  A new wavelet selection method for partial discharge denoising , 2015 .

[5]  Philip Chan,et al.  Toward accurate dynamic time warping in linear time and space , 2007, Intell. Data Anal..

[6]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[8]  Xiandong Ma,et al.  Interpretation of wavelet analysis and its application in partial discharge detection , 2002 .

[9]  Martin Vetterli,et al.  Wavelets and filter banks: theory and design , 1992, IEEE Trans. Signal Process..

[10]  Xiandong Ma,et al.  Automated wavelet selection and thresholding for PD detection , 2002 .

[11]  Min Wu,et al.  An overview of state-of-the-art partial discharge analysis techniques for condition monitoring , 2015, IEEE Electrical Insulation Magazine.

[12]  Sung-Wook Kim,et al.  Measurement and analysis of partial discharges in SF6 gas under HVDC , 2016 .

[13]  S. Tenbohlen,et al.  Partial discharge measurement in the ultra high frequency (UHF) range , 2008, IEEE Transactions on Dielectrics and Electrical Insulation.

[14]  John J. Soraghan,et al.  Detection of PD utilizing digital signal processing methods. Part 3: Open-loop noise reduction , 2001 .

[15]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[16]  Alain Girodet,et al.  Partial discharge analysis of gas insulated systems at high voltage AC and DC , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[17]  Jian Li,et al.  Scale dependent wavelet selection for de-noising of partial discharge detection , 2010, IEEE Transactions on Dielectrics and Electrical Insulation.

[18]  L. Satish,et al.  Wavelet-based denoising of partial discharge signals buried in excessive noise and interference , 2003 .

[19]  K. D. Srivastava,et al.  Review of condition assessment of power transformers in service , 2002 .

[20]  P. Morshuis,et al.  Partial discharges at DC voltage: their mechanism, detection and analysis , 2005, IEEE Transactions on Dielectrics and Electrical Insulation.

[21]  T. Sakoda,et al.  Diagnostics of insulation deterioration of ethylene propylene rubber using an acoustic emission technique , 2010, IEEE Transactions on Dielectrics and Electrical Insulation.

[22]  Bo Qi,et al.  Partial discharge initiated by free moving metallic particles on GIS insulator surface: severity diagnosis and assessment , 2014, IEEE Transactions on Dielectrics and Electrical Insulation.

[23]  M. Pompili,et al.  Partial discharge pulse sequence patterns and cavity development times in transformer oils under AC conditions , 2005, IEEE Transactions on Dielectrics and Electrical Insulation.

[24]  K. N. Dollman,et al.  - 1 , 1743 .

[25]  Hao Zhang,et al.  A novel wavelet transform technique for on-line partial discharge measurements. 1. WT de-noising algorithm , 2007, IEEE Transactions on Dielectrics and Electrical Insulation.

[26]  F. H. Kreuger,et al.  Partial Discharge Detection in High Voltage Equipment , 1990 .

[27]  C.S. Chang,et al.  Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations , 2005, IEEE Transactions on Power Delivery.

[28]  J. Ramirez-Niño,et al.  Analysis of partial electrical discharges in insulating materials through the wavelet transform , 1998 .

[29]  Gyung-Suk Kil,et al.  Measurements and analysis of the acoustic signals produced by partial discharges in insulation oil , 2009 .

[30]  M. Teguar,et al.  Characterization of discharges on non-uniformly polluted glass surfaces using a wavelet transform approach , 2013, IEEE Transactions on Dielectrics and Electrical Insulation.

[31]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[32]  M.D. Judd,et al.  Partial discharge monitoring of power transformers using UHF sensors. Part I: sensors and signal interpretation , 2005, IEEE Electrical Insulation Magazine.

[33]  R. Bartnikas,et al.  Trends in partial discharge pattern classification: a survey , 2005, IEEE Transactions on Dielectrics and Electrical Insulation.

[34]  Massimo Pompili,et al.  Simultaneous ultrawide and narrowband detection of PD pulses in dielectric liquids , 1998 .