DocumentCode :
2244128
Title :
Study of transformer fault diagnosis by Fuzzy C-Means method
Author :
Tingfang, Yang ; Xin, Yang
Author_Institution :
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Volume :
2
fYear :
2010
fDate :
6-7 March 2010
Firstpage :
306
Lastpage :
308
Abstract :
Power transformer is one of key devices in electric power system. And monitoring the components of dissolved gas-in-oil can discover its incipient fault to avoid availably electric power grid running accidents. As uncertain factors such as fuzziness and random exist among fault causes, fault phenomenon and fault type of power transformer, no correct one to one corresponding relations indwell in fault characteristic quantity and symptom of fault. According to the ideal of cluster analysis, Fuzzy C-Means (FCM) combined is adopted based on thorough analysis of dissolved gas in transformer to quantificational depict aggregation effect of characteristic gas space, which can categorize faults automatically and reasonably in power transformer. Simulation results show the high feasibility and effectiveness of this way.
Keywords :
fault diagnosis; fuzzy set theory; power transformers; electric power system; fuzzy C means method; power transformer; quantificational depict aggregation effect; transformer fault diagnosis; Clustering algorithms; Dissolved gas analysis; Educational institutions; Fault diagnosis; Oil insulation; Partitioning algorithms; Power engineering and energy; Power systems; Power transformers; Robotics and automation; Fuzzy C-Means Method; aggregation effect; cluster analysis; dissolved gas-in-oil; fault diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
ISSN :
1948-3414
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
Type :
conf
DOI :
10.1109/CAR.2010.5456541
Filename :
5456541
Link To Document :
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