Power transformer fault diagnosis under measurement originated uncertainties

Ma, Hui, Ekanayake, Chandima and Saha, Tapan (2012) Power transformer fault diagnosis under measurement originated uncertainties. IEEE Transaction on Dielectrics and Electrical Insulation, 19 6: 1982-1990. doi:10.1109/TDEI.2012.6396956

Author Ma, Hui
Ekanayake, Chandima
Saha, Tapan
Title Power transformer fault diagnosis under measurement originated uncertainties
Journal name IEEE Transaction on Dielectrics and Electrical Insulation   Check publisher's open access policy
ISSN 1070-9878
Publication date 2012-12
Sub-type Article (original research)
DOI 10.1109/TDEI.2012.6396956
Volume 19
Issue 6
Start page 1982
End page 1990
Total pages 9
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2013
Language eng
Abstract This paper addresses the problem of diagnosing the fault symptoms of power transformers with measurement originated uncertainties, which arise from the imprecision of samples (i.e. due to noises and outliers) and the effect of class imbalance (i.e. samples are unequally distributed between different fault types) in a training dataset used to identify different fault types. Two fuzzy support vector machine (FSVM) algorithms namely fuzzy c-means clustering-based FSVM (FCM-FSVM) and kernel fuzzy c-means clustering-based FSVM (KFCM-FSVM) have been applied in this paper to deal with any noises and outliers in training dataset. In order to reduce the effect of class imbalance in training dataset, two approaches including between-class weighting and random oversampling have been adopted and integrated with FCM-FSVM and KFCM-FSVM. The case studies show that KFCM-FSVM algorithm and its variants have consistent tendency to attain satisfied classification accuracy in transformer fault diagnosis using dissolved gas analysis (DGA) measurements.
Keyword Condition monitoring
Dissolved gas analysis
Measurement originated uncertainties
Power transformer
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 9 times in Thomson Reuters Web of Science Article | Citations
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Created: Sat, 05 Jan 2013, 13:50:05 EST by Dr Hui Ma on behalf of School of Information Technol and Elec Engineering