Machine learning techniques for robust classification of partial discharges in oil-paper insulation systems

IET Science, Measurement and Technology

Volumn 10, Issue 3, 2016, Pages 221-227

  Woon, Wei Lee ^a   El Hag, Ayman ^b   Harbaji, Mustafa ^b  

^a KHALIFA UNIVERSITY   (United Arab Emirates)

^b AMERICAN UNIVERSITY OF SHARJAH   (United Arab Emirates)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC EMISSION TESTING; ARTIFICIAL INTELLIGENCE; CLIMATE CHANGE; ELECTRIC POWER TRANSMISSION NETWORKS; INSULATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; OUTAGES; PAPER; PARTIAL DISCHARGES; POWER TRANSFORMERS; SMART POWER GRIDS;

ACOUSTIC EMISSION SENSORS; CLASSIFICATION ACCURACY; CLASSIFICATION ALGORITHM; CLASSIFICATION TECHNIQUE; INTELLIGENT MONITORING; MACHINE LEARNING TECHNIQUES; MEASUREMENT CONDITIONS; OIL-PAPER INSULATION SYSTEM;

CLASSIFICATION (OF INFORMATION);

ALGORITHMS; ELECTRICAL ENGINEERING; INSULATING PAPERS; INSULATION; TRANSFORMERS;

EID: 84964727290     PISSN: 17518822     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-smt.2015.0076     Document Type: Article

References (30)

1. Harbaji M. El-Hag A. Shaban K.: 'Accurate partial discharge classification from acoustic emission signals'. 2013 Third Int. Conf. on Electric Power and Energy Conversion Systems (EPECS), 2013, pp. 1-4
2. Brown M.H. Sedano R.P.: 'Electricity transmission: a primer'. National Conf. of State, 2004
3. Tichelman B.: 'Transformer asset management. new paradigm'. SERVERON Corporation.-2004, 2004
4. Bartley W.H.: 'Analysis of transformer failures'. Int. Association of Engineering Insurers 36th Annual Conf., 2003, pp. 1-5
5. Kuo C.-C. Shieh H.-L.: 'Artificial classification system of aging period based on insulation status of transformers'. 2009 Int. Conf. on Machine Learning and Cybernetics, 2009, vol. 6, pp. 3310-3315
6. Rubio-Serrano J. Rojas-Moreno M. Posada J.: 'Electro-acoustic detection, identification and location of partial discharge sources in oil-paper insulation systems', IEEE Trans. Dielectr. Electr. Insul., 2012, 19, (5), pp. 1569-1578
7. Hooshmand R.A. Parastegari M. Yazdanpanah M.: 'Simultaneous location of two partial discharge sources in power transformers based on acoustic emission using the modified binary partial swarm optimisation algorithm', IET Sci. Meas. Technol., 2013, 7, (2), pp. 119-127
8. Hikita M. Okabe S. Murase H.: 'Cross-equipment evaluation of partial discharge measurement and diagnosis techniques in electric power apparatus for transmission and distribution', IEEE Trans. Dielectr. Electr. Insul., 2008, 15, (2), pp. 505-518
9. Pinpart T. Judd M.: 'Differentiating between partial discharge sources using envelope comparison of ultra-high-frequency signals', IET Sci. Meas. Technol., 2010, 4, (5), pp. 256-267
10. Transformers Committee: 'IEEE guide for the interpretation of gases generated in oil-immersed transformers'. IEEE Std. C57.104-2008 (Revision IEEE Std. C57.104-1991), 2009, pp. C1-27
11. Duval M.: 'Dissolved gas analysis: it can save your transformer', IEEE Electr. Insul. Mag., 1989, 5, (6), pp. 22-27
12. Ramírez-Niño J. Pascacio A.: 'Acoustic measuring of partial discharge in power transformers', Meas. Sci. Technol., 2009, 20, (11), p. 115108
13. Boczar T.: 'Identification of a specific type of PD from acoustic emission frequency spectra', IEEE Trans. Dielectr. Electr. Insul., 2001, 8, (4), pp. 598-606
14. Harbaji M. Shaban K. El-Hag A.: 'Classification of common partial discharge types in oil-paper insulation system using acoustic signals', IEEE Trans. Dielectr. Electr. Insul., 2015, 22, (3), pp. 1674-1683
15. Ho T.K.: 'The random subspace method for constructing decision forests', IEEE Trans. Pattern Anal. Mach. Intell., 1998, 20, (8), pp. 832-844
16. Ma H. Chan J.C. Saha T.K.: 'Pattern recognition techniques and their applications for automatic classification of artificial partial discharge sources', IEEE Trans. Dielectr. Electr. Insul., 2013, 20, (2), pp. 468-478
17. Hao L. Lewin P.: 'Partial discharge source discrimination using a support vector machine', IEEE Trans. Dielectr. Electr. Insul., 2010, 17, (1), pp. 189-197
18. Hao L. Lewin P. Hunter J.: 'Discrimination of multiple PD sources using wavelet decomposition and principal component analysis', IEEE Trans. Dielectr. Electr. Insul., 2011, 18, (5), pp. 1702-1711
19. Jiang T. Li J. Zheng Y.: 'Improved bagging algorithm for pattern recognition in UHF signals of partial discharges', Energies, 2011, 4, (7), pp. 1087-1101
20. Boczar T. Zmarzly D.: 'Application of wavelet analysis to acoustic emission pulses generated by partial discharges', IEEE Trans. Dielectr. Electr. Insul., 2004, 11, (3), pp. 433-449
21. Boczar T. Borucki S. Cichon A.: 'Application possibilities of artificial neural networks for recognizing partial discharges measured by the acoustic emission method', IEEE Trans. Dielectr. Electr. Insul., 2009, 16, (1), pp. 214-223
22. Chai M. Thayoob Y.H.M. Ghosh P.: 'Identification of different types of partial discharge sources from acoustic emission signals in the time-frequency representation'. Power and Energy Conf., 2006. PECon'06. IEEE Int., 2006, pp. 581-586
23. Swedan A. El-Hag A. Assaleh K.: 'Acoustic detection of partial discharge using signal processing and pattern recognition techniques', Insight, Non-Destr. Test. Cond. Monit., 2012, 54, (12), pp. 667-672
24. Hand D.J. Mannila H. Smyth P.: 'Principles of data mining' (MIT Press, 2001)
25. Hastie T. Tibshirani R. Friedman J.: 'The elements of statistical learning' (Springer, 2009), vol. 2, no. 1
26. Breiman L. Friedman J. Olshen R.: 'CART: classification and regression trees' (Wadsworth: Belmont, CA, 1983), vol. 156
27. Breiman L.: 'Random forests', Mach. Learn., 2001, 45, (1), pp. 5-32
28. Loh W.-Y.: 'Classification and regression trees', Wiley Interdiscip. Rev., Data Min. Knowl. Discov., 2011, 1, (1), pp. 14-23
29. Gregersen E.: 'The Britannica Guide to sound and light' (Britannica Educational Publishing, 2010), ch. 1
30. Bishop C.M.: 'Training with noise is equivalent to Tikhonov regularization', Neural Comput., 1995, 7, (1), pp. 108-116