Pattern recognition techniques for power transformer insulation diagnosis: a comparative study. Part 1: framework, literature,and illustration

Cui, Yi, Ma, Hui and Saha, Tapan (2014) Pattern recognition techniques for power transformer insulation diagnosis: a comparative study. Part 1: framework, literature,and illustration. International Transactions on Electrical Energy Systems, 25 10: 2247-2259. doi:10.1002/etep.1959

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Author Cui, Yi
Ma, Hui
Saha, Tapan
Title Pattern recognition techniques for power transformer insulation diagnosis: a comparative study. Part 1: framework, literature,and illustration
Journal name International Transactions on Electrical Energy Systems   Check publisher's open access policy
ISSN 2050-7038
Publication date 2014-07-21
Year available 2014
Sub-type Article (original research)
DOI 10.1002/etep.1959
Open Access Status
Volume 25
Issue 10
Start page 2247
End page 2259
Total pages 13
Place of publication Chichester, West Sussex, United Kingdom
Publisher John Wiley & Sons
Collection year 2015
Language eng
Formatted abstract
The condition of the insulation system of a power transformer has a significant impact on its overall reliability and serviceability. Transformer oil tests including breakdown voltage, acidity, dielectric dissipation factor, 2-furfuraldehyde, water content, and dissolved gases analysis have been commonly performed in utility companies to provide information regarding the conditions of transformer insulation. Over the past two decades, various pattern recognition techniques are proposed to interpret the oil tests results and make diagnosis on transformer insulation. However, there are still considerable challenging issues to be investigated before the pattern recognition technique can become a “ready-to-use” tool at utility companies. This paper provides a comparative study of pattern recognition techniques for power transformer insulation diagnosis using oil tests results. A general pattern recognition application framework will be outlined in the paper. And a comprehensive literature review on various pattern recognition techniques for transformer insulation diagnosis will be provided in the paper. The important issues for improving the applicability of pattern recognition techniques for transformer insulation diagnosis will also be discussed. A case study will be presented to demonstrate the procedure of applying pattern recognition techniques to practical transformer insulation diagnosis using oil test results.
Keyword Dissolved gas analysis
Insulation
Oil characteristics
Pattern recognition
Power transformer
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article first published online: 21 JUN 2014.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Information Technology and Electrical Engineering Publications
 
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Created: Thu, 04 Dec 2014, 13:51:58 EST by Dr Hui Ma on behalf of School of Information Technol and Elec Engineering