DocumentCode
3497863
Title
Application of fuzzy data processing for fault diagnosis of power transformers
Author
Zhang, Guanjun ; Liu, Yuan-Shing ; Ibuka, Shinji ; Yasuoka, Koichi ; Ishii, Shozo ; Shang, Yong ; Yan, Zhang
Author_Institution
Tokyo Inst. of Technol., Japan
Volume
5
fYear
1999
fDate
1999
Firstpage
160
Abstract
Based on the data of dissolved gas analysis (DGA), fuzzy cluster analysis (FCA) technique is applied to identify the fault patterns of power transformers in this paper. FCA consists of some trial and instructive strategies absorbing useful experiences from the mid-results. Its clustering centers are dynamic, as a result, the approach can classify and recombine different samples sucessfully. Compared with the conventional methods, it reveals the practical advantages of unsupervised systems, including the ability to produce categories without supervision
Keywords
power transformer testing; ISODATA; dissolved gas analysis; dynamic clustering centers; fault diagnosis; fault patterns identification; fuzzy cluster analysis; fuzzy data processing; iterative self-organising data analysis technique algorithm; power transformers; unsupervised systems;
fLanguage
English
Publisher
iet
Conference_Titel
High Voltage Engineering, 1999. Eleventh International Symposium on (Conf. Publ. No. 467)
Conference_Location
London
ISSN
0537-9989
Print_ISBN
0-85296-719-5
Type
conf
DOI
10.1049/cp:19990910
Filename
818262
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