Identification of partial discharges immersed in noise in large hydro-generators based on improved wavelet selection methods

Measurement: Journal of the International Measurement Confederation

Volumn 75, Issue , 2015, Pages 122-133

  Carvalho, Andre T ^a,b   Lima, Antonio C S ^b   Cunha, Caio F F C ^a,b   Petraglia, Mariane ^b  

^a CEPEL   (Brazil)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Partial discharges; Signal denoising; Wavelet base selection; Wavelet transform

Indexed keywords

ELECTRIC GENERATORS; ELECTRIC MACHINE INSULATION; HYDROELECTRIC GENERATORS; MACHINE WINDINGS; NOISE GENERATORS; PARTIAL DISCHARGES; PULSE GENERATORS; SIGNAL DENOISING; SIGNAL TO NOISE RATIO; WAVELET ANALYSIS; WAVELET DECOMPOSITION; WAVELET TRANSFORMS; WINDING;

AUTOMATIC SELECTION; DECOMPOSITION LEVEL; DECOMPOSITION TREES; DENOISING METHODS; HIGH SIGNAL-TO-NOISE RATIO; ON-LINE PARTIAL DISCHARGE; PROPAGATION CHARACTERISTICS; WAVELET BASE;

ELECTRIC MACHINE THEORY;

EID: 84940202775     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2015.07.050     Document Type: Article

References (40)

1. X. Ma, C. Zhou, and I. Kemp Interpretation of wavelet analysis and its application in partial discharge detection IEEE Trans. Dielectr. Electr. Insul. 9 Jun 2002 446 457
2. L. Satish, and B. Nazneen Wavelet-based denoising of partial discharge signals buried in excessive noise and interference IEEE Trans. Dielectr. Electr. Insul. 10 April 2003 354 367
3. M. Hasmi, M. Lehtonen, M. Nordman, R. Jabbar, and S. Qureshi Wavelet-based de-noising of on-line PD signals captured by Pearson coil in covered-conductor overhead distribution networks Electr. Power Energy Syst. 43 2012 1185 1192
4. M. Nafar, T. Nikman, and A. Gheisari Using correlation coefficients for locating partial discharge in power transformer Electr. Power Energy Syst. 33 2011 493 499
5. R. Sarathi, and R. Umamaheswari Understanding the partial discharge activity generated due to particle movement in a composite insulation under AC voltages Electr. Power Energy Syst 48 2013 1 9
6. D. Evagorou, A. Kyprianou, P. Lewin, A. Stavrou, V. Efthymiou, A. Metaxas, and G. Georghiou Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network IET Sci. Meas. Technol. 4 May 2010 177 192
7. L. Hao, P. Lewin, J. Hunter, D. Swaffield, A. Contin, C. Walton, and M. Michel Discrimination of multiple PD sources using wavelet decomposition and principal component analysis IEEE Trans. Dielectr. Electr. Insul. 18 Oct. 2011 1702 1711
8. Y. Lin Using k-means clustering and parameter weighting for partial-discharge noise suppression IEEE Trans. Power Delivery 26 4 2011 2380 2390
9. J. Tang, W. Li, and Y. Liu Blind source separation of mixed PD signals produced by multiple insulation defects in GIS IEEE Trans. Power Delivery 25 1 2010 170 176
10. M. Su, J. Lin, and Y. Chen Phase determination of partial discharge source in three-phase transmission lines using discrete wavelet transform and probabilistic neural networks Electr. Power Energy Syst. 51 2013 27 34
11. H. Ma, J. Chan, T. Saha, and C. Ekanayake Pattern recognition techniques and their applications for automatic classification of artificial partial discharge sources IEEE Trans. Dielectr. Electr. Insul. 20 2 2013 468 478
12. Raymonda Wong Jee Keen, Illiasa Hazlee Azil, Bakarb Ab Halim Abu, and Mokhlisa Hazlie Partial discharge classifications: review of recent progress Measurement 68 2015 164 181
13. U. Kopf, and K. Feser Rejection of narrow-band noise and repetitive pulses in on-site PD measurements (corrected version) IEEE Trans. Dielectr. Electr. Insul. 2 6 1995 1180 1191
14. S. Sriram, S. Nitin, K. Prabhu, and M. Bastiaans Signal denoising techniques for partial discharge measurements IEEE Trans. Dielectr. Electr. Insul. 12 Dec. 2005 1182 1191
15. S. Mortazavi, S. Shahrtash, Comparing denoising performance of dwt, wpt, swt and dt-cwt for partial discharge signals, in: Universities Power Engineering Conference, 2008. UPEC 2008. 43rd International, September 2008, pp. 1-6.
16. A.J.M. Pemen, P.C.T. van der Laan, and Wout de Leeuw Propagation of partial discharge signals in stator windings of turbine generators IEEE Trans. Energy Convers. 21 1 2006 155 161
17. IEEE guide for the measurement of partial discharges in AC electric machinery, IEEE Std 1434-2014 (Revision of IEEE Std 1434-2000), 2014.
18. IEC 60034-27-2 Rotating electrical machines - on-line partial discharge measurements on the stator winding insulation of rotating electrical machines, 2012.
19. A. Mertins Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications (Ultrasound in Biomedicine Research Series) 1999 Wiley
20. N. Ahuja, S. Lertrattanapanich, and N. Bose Properties determining choice of mother wavelet IEE Proc. - Vision, Image Signal Process. 152 5 2005 659 664
21. X. Ma, C. Zhou, and I. Kemp Automated wavelet selection and thresholding for PD detection IEEE Electr. Insul. Mag. 18 March 2002 37 45
22. J. Li, T. Jiang, S. Grzybowski, and C. Cheng Scale dependent wavelet selection for de-noising of partial discharge detection IEEE Trans. Dielectr. Electr. Insul. 17 Dec. 2010 1705 1714
23. C. Cunha, A. Carvalho, M. Petraglia, and A. Lima An improved scale dependent wavelet selection for data denoising of partial discharge measurement IEEE Int. Conf. Solid Dielectr. (ICSD) 2013 100 104
24. J.K.M. Vetterli, V.K. Goyal, Signal Processing: Fourier and Wavelet Representations, Fourier and Wavelets.org, a3.1 ed., March 2012.
25. I. Shim, J. Soraghan, and W. Siew Detection of PD utilizing digital signal processing methods. Part 3: open-loop noise reduction IEEE Electr. Insul. Mag. 17 Jan. 2001 6 13
26. D. ZhaoHeng, L. ShangHe, W. Lei, Selection of the optimal wavelet bases for wavelet de-noising of partial discharge signal, in: 2010 2nd International Conference on Signal Processing Systems (ICSPS), vol. 3, July 2010, pp. 400-404.
27. W. Xiaorong, G. Zongjun, S. Yong, Y. Zhang, Extraction of partial discharge pulse via wavelet shrinkage, in: Proceedings of the 6th International Conference on Properties and Applications of Dielectric Materials, vol. 2, 2000, pp. 685-688.
28. O. Altay, and O. Kalenderli Wavelet base selection for de-noising and extraction of partial discharge pulses in noisy environment IET Sci. Meas. Technol. 9 3 2015 276 284
29. X. Zhou, C. Zhou, and I. Kemp An improved methodology for application of wavelet transform to partial discharge measurement denoising IEEE Trans. Dielectr. Electr. Insul. 12 Jun. 2005 586 594
30. G.O.J.-M.P. Michel Misiti, and Yves Misiti Wavelet Toolbox Users Guide fourth ed. March 2012 The MathWorks Inc Natick
31. M. Shensa The discrete wavelet transform: wedding the a trous and mallat algorithms IEEE Trans. Signal Process. 40 10 1992 2464 2482
32. C.H. Kim, and R. Aggarwal Wavelet transforms in power systems. ii. Examples of application to actual power system transients Power Eng. J. 15 August 2001 193 202
33. X. Song, C. Zhou, D. Hepburn, G. Zhang, and M. Michel Second generation wavelet transform for data denoising in pd measurement IEEE Trans. Dielectr. Electr. Insul. 14 December 2007 1531 1537
34. H. Zhang, T. Blackburn, B. Phung, and D. Sen A novel wavelet transform technique for on-line partial discharge measurements. 1. wt de-noising algorithm IEEE Trans. Dielectr. Electr. Insul. 14 February 2007 3 14
35. H. Zhang, T. Blackburn, B. Phung, and D. Sen A novel wavelet transform technique for on-line partial discharge measurements. 2. On-site noise rejection application IEEE Trans. Dielectr. Electr. Insul. 14 February 2007 15 22
36. C. Cunha, A. Carvalho, M. Petraglia, and A. Lima A new wavelet selection method for partial discharge denoising Electr. Power Syst. Res. 125 2015 184 195
37. J.K.M. Vetterli, V.K. Goyal, Signal Processing Foundations, FourierAndWavelets.org, b1.0 ed., March 2012.
38. P. Shetty, T. Ramu, An undecimated wavelet transform based enhancement, statistical feature extraction and detection-classification of pd signals [partial discharges], in: Proceedings. (ICASSP '04). IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 5, May 2004, pp. V - 401-4.
39. X. Zhongrong, T. Ju, and S. Caixin Application of complex wavelet transform to suppress white noise in GIS UHF PD signals IEEE Trans. Power Delivery 22 July 2007 1498 1504
40. G. Strang, and T. Nguyen Wavelets and Filter Banks 1996 Wellesley College