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Mathematical Problems in Engineering
Volume 2016, Article ID 6069784, 9 pages
Research Article

Calculation of a Health Index of Oil-Paper Transformers Insulation with Binary Logistic Regression

1School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
2Distribution System Department, China Electric Power Research Institute, Beijing 100192, China
3College of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China

Received 13 January 2016; Revised 25 April 2016; Accepted 24 May 2016

Academic Editor: Huaguang Zhang

Copyright © 2016 Weijie Zuo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a new method for calculating the insulation health index (HI) of oil-paper transformers rated under 110 kV to provide a snapshot of health condition using binary logistic regression. Oil breakdown voltage (BDV), total acidity of oil, 2-Furfuraldehyde content, and dissolved gas analysis (DGA) are singled out in this method as the input data for determining HI. A sample of transformers is used to test the proposed method. The results are compared with the results calculated for the same set of transformers using fuzzy logic. The comparison results show that the proposed method is reliable and effective in evaluating transformer health condition.