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Application of fuzzy support vector machine for determining the health index of the insulation system of in-service power transformers

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4 Author(s)
Ashkezari, A.D. ; Univ. of Queensland, Brisbane, QLD, Australia ; Hui Ma ; Saha, T.K. ; Ekanayake, C.

With the integration of data and information obtained from a variety of chemical and electrical tests on transformer insulating oil, it is possible to evaluate the health condition of the insulation system of an in-service power transformer. This paper develops an intelligent algorithm for automatically processing the data collected from oil tests and determining a health index for the transformer insulation system. This intelligent algorithm adopts a fuzzy support vector machine (FSVM) approach, which constructs a statistical model using a training database based on the historic data collected from 181 in-service power transformers. The procedure of constructing the training database, the formulation and implementation of FSVM and the data preprocessing methods for dealing with a class imbalanced training database is presented in this paper. Numerical experiments are also conducted to evaluate the performance of the algorithms developed in the paper.

Published in:

Dielectrics and Electrical Insulation, IEEE Transactions on  (Volume:20 ,  Issue: 3 )