Statistical learning techniques and their applications for condition assessment of power transformer

IEEE Transactions on Dielectrics and Electrical Insulation

Volumn 19, Issue 2, 2012, Pages 481-489

  Ma, Hui ^a   Saha, Tapan K ^a   Ekanayake, Chandima ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

and power transformer; Condition monitoring; dissolved gas analysis; polarization depolarization currents

Indexed keywords

CONDITION ASSESSMENTS; DISSOLVED GAS ANALYSIS; ELECTRIC POWER GRIDS; MEASUREMENT DATA; NON-TRIVIAL TASKS; POLARIZATION/DEPOLARIZATION CURRENT; RELIABLE OPERATION; SIGNIFICANT IMPACTS; STATISTICAL LEARNING; STATISTICAL LEARNING TECHNIQUES; STATISTICAL PROPERTIES; SUPPORT VECTOR MACHINE ALGORITHM; SYSTEM OUTPUT;

CONDITION MONITORING; LEARNING ALGORITHMS; MEASUREMENTS; SUPPORT VECTOR MACHINES;

POWER TRANSFORMERS;

EID: 84860116265     PISSN: 10709878     EISSN: None     Source Type: Journal    
DOI: 10.1109/TDEI.2012.6180241     Document Type: Article

References (19)

1. M. Wang, A.J. Vandermaar, and K.D. Srivastava, "Review of condition assessment of power transformer in service", IEEE Electr. Insul. Mag., Vol.18, No. 6, pp.12-25, 2002.
2. A.Jahromi, R.Piercy, S.Cress, J.Service, and W.Fan, "An approach to power transformer asset management using health index", IEEE Electr. Insul. Mag., Vol. 25, No. 2, pp. 20-34, 2009.
3. T.K. Saha, "Review of modern diagnostic techniques for assessing insulation condition in aged transformers", IEEE Trans. Dielectr. Electr. Insul., Vol. 10, pp. 903-917, 2003.
4. IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers, IEEE Standard C57.104-2008, 2009.
5. T.K. Saha and P. Purkait, "Investigation of polarisation and depolarisation current measurements for the assessment of oil-paper insulation of aged transformers", IEEE Trans. Dielectr. Electr. Insul., Vol. 11, pp. 144-154, 2004.
6. T. Gradnik, M. Babuder, and M. Koncan-Gradnik, "Estimation of water content in power transformers in service by polarization and depolarization current measurements", IEEE Conf. Dielectr. Liquids, Futuroscope- Chasseneuil, France, pp.1-4, 2008.
7. H. Ma, T. K. Saha, A. Thomas and C. Ekanayake, "Intelligent Framework and Techniques for Power Transformer Insulation Diagnosis", IEEE Power and Energy Society, General Meeting, Paper No. PESGM2009-000425, Calgary, Alberta, Canada, 2009.
8. H. Ma, T.K. Saha, and C. Ekanayake, "Power transformer insulation diagnosis under measurement originated uncertainties", IEEE Power and Energy Society, General Meeting, Paper No. 2010GM0299, Minneapolis, Minnesota, USA, 2010.
9. M. Duval, "Dissolved gas analysis: It can save your transformer", IEEE Electr. Insul. Mag., Vol. 5, No.4, pp. 22-27,1989.
10. Z.Y. Wang, Y.L. Liu and P.J. Griffin, "A Combined ANN and expert system tool for transformer fault diagnosis", IEEE Trans. Power Delivery, Vol. 13, pp. 1224-1229, 1998.
11. M. Islam, T. Wu, and G. Ledwich, "A novel fuzzy logic approach to transformer fault diagnosis", IEEE Trans. Dielectr. Electr. Insul., Vol. 7, pp. 177-186, 2000.
12. K.F. Thang, R.K. Aggarwal, A.J. McGrail and D.G. Esp, "Analysis of power transformer dissolved gas data using the self-organizing map", IEEE Trans. Power Delivery, Vol. 18, pp. 1241-1248, 2008.
13. T.K. Saha, P. Purkait, and F. Muller, "Deriving an equivalent circuit of transformers insulation for understanding the dielectric response measurements", IEEE Trans. Power Delivery, Vol. 20, pp.149-157, 2005.
14. V. Cherkassky and F. Mulier, Learning from Data: Concepts, Theory, and Methods, John Wiley & Sons, Inc., Hoboken, New Jersey, 2007.
15. M.I. Schlesinger and V. Hlavac, Ten Lectures on Statistical and Structural Pattern Recognition, Kluwer Academic Publishers, The Netherlands, 2002.
16. V. Vapnik, The Nature of Statistical Learning Theory, Springer, 1995.
17. C.J.C. Burges, "A tutorial on support vector machines for pattern recognition", Data Mining and Knowledge Discovery, Vol. 2, pp. 121-167, 1998.
18. N. Cristianini and J. Shawe-Taylor, An Introduction of Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge University Press, 2001.
19. C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," available: Http://www.csie.ntu.edu.tw/~cjlin/libsvm.