By Topic

Development of dissolved gas analysis(DGA) expert system using new diagnostic algorithm for oil-immersed transformers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Y. M. Kim ; Power & Ind. Syst. R&D Center, Hyosung Corp., Changwon, South Korea ; S. J. Lee ; H. D. Seo ; J. R. Jung
more authors

Dissolved gas analysis(DGA) is one of the most widely used diagnostic tools to detect and evaluate faults in power transformers for a long time. IEEE Guide C57.104 and IEC Publication 60599 recommend several DGA diagnostic methods used for utilities and most of them are available to classify the different types of faults using gas ratios or %gas. However, the task of DGA interpretation is not easy because they often can provide unresolved diagnoses and wrong diagnoses. Therefore, it is necessary to develop new method for gas interpretation that has higher accuracy and more reliable diagnoses. This paper proposes new diagnostic methods to classify six types of faults specified in IEEE Guide C57.104 and IEC Publication 60599 using gas ratio and relative % of combustible gases (H2, C2H2, C2H4, C2H6 and CH4). And accuracy of the proposed diagnosis methods was verified using IEC TC10 and related databases. Also, on-line DGA diagnostic system, HiDGA(Hyosung intelligent Dissolved Gas Analysis), that is possible to continuously monitor transformer in service is developed and it is possible to identify faults of transformer by visual inspection using new diagnostic method that applied to diagnostic HMI(Human Machine Interface).

Published in:

Condition Monitoring and Diagnosis (CMD), 2012 International Conference on

Date of Conference:

23-27 Sept. 2012