Classification of Acoustic Emission Based Partial Discharge in Oil Pressboard Insulation System Using Wavelet Analysis
Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
[1] Y.Yan and Y.H.Song, "Condition monitoring techniques for electrical
equipment- A Literature survey", IEEE Transactions on Power Delivery,
Vol.18, No.1, January-2003, pp. 4 to 13.
[2] Abbas Zargari, Trevor R. Blackburn, "Modified optical fibre sensor for
PD detection in high voltage power equipment", Conference record of the
1996 IEEE International Symposium on Electrical Insulation, Montreal,
Quebec, Canada, June 16-19, 1996, pp. 424 to 427.
[3] L.E. Lundgaard, "Partial discharge. XIII. Acoustic partial discharge
detection-fundamental considerations", IEEE Electrical Insulation
Magazine, Volume 8, Issue 4, July-Aug. 1992, pp. 25 - 31
[4] L.E. Lundgaard, "Partial discharge. XIV. Acoustic partial discharge
detection-practical application", IEEE Electrical Insulation Magazine,
Volume 8, Issue 5, Sept.-Oct. 1992, pp. 34 - 43.
[5] R.T. Harrold, "Acoustical Techniques for Detecting and Locating
Electrical Discharges". Engineering Dielectrics Volume I: Corona
Measurement and Interpretation, ASTM Special Publication 669,
Philadelphia, 1979, pp. 327 - 408.
[6] N.C.Sahoo, M.M.A.Salama and R. Bartnikas, "Trends in partial discharge
pattern classification : A survey", IEEE Transactions on Dielectrics and
Electrical Insulation, Vol. 12, No. 2, April 2005, pp. 248 - 264.
[7] Deheng Zhu, Kexiong Tan, Xianhe Jin, "The study of acoustic emission
method for detection of partial discharge in power transformer",
Proceedings of Second International Conference on Properties and
Applications of Dielectric Materials, 12-16 Sept. 1988, Beijing, China, pp.
614 - 617. vol.2.
[8] T. Boczar, " Identification of a specific type of PD from acoustic emission
frequency spectra", IEEE Transactions on Dielectrics and Electrical
Insulation, Volume 8, Issue 4, Aug. 2001, pp. 598 - 606.
[9] Tomasz Boczar and Dariusz Zmarzly, "Application of wavelet analysis to
acoustic emission pulses generated by partial discharges", IEEE
Transactions on Dielectrics and Electrical Insulation, Vol.11, No.3, June
2004, pp. 433-448.
[10] L. Satish and B. Nazneen, "Wavelet-based de-noising of partial discharge
signals buried in excessive noise and interference", IEEE Transactions on
Dielectrics and Electrical Insulation, Vol. 10, No. 2, April 2003, pp. 354-
367.
[11] X. Ma, C. Zhou and I.J.Kemp, "Interpretation of wavelet analysis and its
application in partial discharge detection", IEEE Transactions on
Dielectrics and Electrical Insulation, Vol. 9, No. 3, June 2002, pp.446 -
457.
[12] Indrajit Dasgupta, "Design of Transformers", Tata McGraw-Hill
Publishing Company Limited, New Delhi, 2002, page 271 (Book).
[13] R. Meunier, G.H. Vaillancourt, "Propagation behaviour of acoustic partial
discharge signals in oil-filled transformers", 12th International
Conference on Conduction and Breakdown in Dielectric Liquids, 1996,
ICDL '96., 15-19 July 1996, pp. 401 - 404.
[14] Prasanta Kundu, N.K.Kishore and A.K. Sinha, "Simulation and analysis
of acoustic wave propagation due to partial discharge activity", 2006 IEEE
Conference on Electrical Insulation and Dielectric Phenomena, CEIDP,
October 2006, USA, pp. 607-610.
[15] Xiaodong Wang, Baoqing Li, Zhiwei Liu, Harry T. Roman, Onofrio L.
Russo, Ken K. Chin, and Kenneth R. Farmer, "Analysis of partial
discharge signal using Hilbert - Huang Transform", IEEE Transactions on
Power Delivery, Vol. 21, No. 3, July 2006, pp 1063 - 1067.
[16] C. Macia-Sanahuja and H. Lamela-Rivera, "Wavelet analysis of partial
discharges acoustic waves obtained using an optical fibre interferometric
sensor for transformer applications", IEEE International Symposium on
Industrial Electronics, 2003, Volume 2, June 2003, pp. 1071 - 1076.
[17] Robi Polikar, "The Wavelet Tutorial, Part IV",
http://users.rowan.edu/~polikar/WAVELETS/WTtutorial.html.
[18] Cheng Younghong, Xie Xiaojun, Chen Xiaolin and Xie Hengkun, " A
kind of fractal analyzing method of nano second order discharge signal",
Proceedings of the 7th International Conference on Properties and
Applications of Dielectric Materials, June 1-5, 2003, pp. 875 - 878.
[19] J.Jin, C. S. Chang, C. Chang, T. Hoshino, M. Hani and N. Kobayashi,
"Classification of partial discharge events in gas insulated substations
using wavelet packet transform and neural network approaches", IEE
Proc. Sci. Meas. Technol, Vol. 153, No. 2, March 2006, pp. 55 -63.
[1] Y.Yan and Y.H.Song, "Condition monitoring techniques for electrical
equipment- A Literature survey", IEEE Transactions on Power Delivery,
Vol.18, No.1, January-2003, pp. 4 to 13.
[2] Abbas Zargari, Trevor R. Blackburn, "Modified optical fibre sensor for
PD detection in high voltage power equipment", Conference record of the
1996 IEEE International Symposium on Electrical Insulation, Montreal,
Quebec, Canada, June 16-19, 1996, pp. 424 to 427.
[3] L.E. Lundgaard, "Partial discharge. XIII. Acoustic partial discharge
detection-fundamental considerations", IEEE Electrical Insulation
Magazine, Volume 8, Issue 4, July-Aug. 1992, pp. 25 - 31
[4] L.E. Lundgaard, "Partial discharge. XIV. Acoustic partial discharge
detection-practical application", IEEE Electrical Insulation Magazine,
Volume 8, Issue 5, Sept.-Oct. 1992, pp. 34 - 43.
[5] R.T. Harrold, "Acoustical Techniques for Detecting and Locating
Electrical Discharges". Engineering Dielectrics Volume I: Corona
Measurement and Interpretation, ASTM Special Publication 669,
Philadelphia, 1979, pp. 327 - 408.
[6] N.C.Sahoo, M.M.A.Salama and R. Bartnikas, "Trends in partial discharge
pattern classification : A survey", IEEE Transactions on Dielectrics and
Electrical Insulation, Vol. 12, No. 2, April 2005, pp. 248 - 264.
[7] Deheng Zhu, Kexiong Tan, Xianhe Jin, "The study of acoustic emission
method for detection of partial discharge in power transformer",
Proceedings of Second International Conference on Properties and
Applications of Dielectric Materials, 12-16 Sept. 1988, Beijing, China, pp.
614 - 617. vol.2.
[8] T. Boczar, " Identification of a specific type of PD from acoustic emission
frequency spectra", IEEE Transactions on Dielectrics and Electrical
Insulation, Volume 8, Issue 4, Aug. 2001, pp. 598 - 606.
[9] Tomasz Boczar and Dariusz Zmarzly, "Application of wavelet analysis to
acoustic emission pulses generated by partial discharges", IEEE
Transactions on Dielectrics and Electrical Insulation, Vol.11, No.3, June
2004, pp. 433-448.
[10] L. Satish and B. Nazneen, "Wavelet-based de-noising of partial discharge
signals buried in excessive noise and interference", IEEE Transactions on
Dielectrics and Electrical Insulation, Vol. 10, No. 2, April 2003, pp. 354-
367.
[11] X. Ma, C. Zhou and I.J.Kemp, "Interpretation of wavelet analysis and its
application in partial discharge detection", IEEE Transactions on
Dielectrics and Electrical Insulation, Vol. 9, No. 3, June 2002, pp.446 -
457.
[12] Indrajit Dasgupta, "Design of Transformers", Tata McGraw-Hill
Publishing Company Limited, New Delhi, 2002, page 271 (Book).
[13] R. Meunier, G.H. Vaillancourt, "Propagation behaviour of acoustic partial
discharge signals in oil-filled transformers", 12th International
Conference on Conduction and Breakdown in Dielectric Liquids, 1996,
ICDL '96., 15-19 July 1996, pp. 401 - 404.
[14] Prasanta Kundu, N.K.Kishore and A.K. Sinha, "Simulation and analysis
of acoustic wave propagation due to partial discharge activity", 2006 IEEE
Conference on Electrical Insulation and Dielectric Phenomena, CEIDP,
October 2006, USA, pp. 607-610.
[15] Xiaodong Wang, Baoqing Li, Zhiwei Liu, Harry T. Roman, Onofrio L.
Russo, Ken K. Chin, and Kenneth R. Farmer, "Analysis of partial
discharge signal using Hilbert - Huang Transform", IEEE Transactions on
Power Delivery, Vol. 21, No. 3, July 2006, pp 1063 - 1067.
[16] C. Macia-Sanahuja and H. Lamela-Rivera, "Wavelet analysis of partial
discharges acoustic waves obtained using an optical fibre interferometric
sensor for transformer applications", IEEE International Symposium on
Industrial Electronics, 2003, Volume 2, June 2003, pp. 1071 - 1076.
[17] Robi Polikar, "The Wavelet Tutorial, Part IV",
http://users.rowan.edu/~polikar/WAVELETS/WTtutorial.html.
[18] Cheng Younghong, Xie Xiaojun, Chen Xiaolin and Xie Hengkun, " A
kind of fractal analyzing method of nano second order discharge signal",
Proceedings of the 7th International Conference on Properties and
Applications of Dielectric Materials, June 1-5, 2003, pp. 875 - 878.
[19] J.Jin, C. S. Chang, C. Chang, T. Hoshino, M. Hani and N. Kobayashi,
"Classification of partial discharge events in gas insulated substations
using wavelet packet transform and neural network approaches", IEE
Proc. Sci. Meas. Technol, Vol. 153, No. 2, March 2006, pp. 55 -63.
@article{"International Journal of Electrical, Electronic and Communication Sciences:62589", author = "Prasanta Kundu and N.K. Kishore and A.K. Sinha", title = "Classification of Acoustic Emission Based Partial Discharge in Oil Pressboard Insulation System Using Wavelet Analysis", abstract = "Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
", keywords = "Acoustic emission, discrete wavelet transform, partial discharge, wavelet packet analysis.", volume = "2", number = "10", pages = "2357-8", }
