DocumentCode
3392991
Title
Transformer Fault Diagnosis Based on Rough Sets and Support Vector Machine
Author
Li Zhi-bin ; Xie Zhi-hui
Author_Institution
Coll. of Power & Autom., Shanghai Univ. of Electr. Power, Shanghai, China
fYear
2012
fDate
27-29 March 2012
Firstpage
1
Lastpage
4
Abstract
For the problem of little sample size and incomplete sample information which leads to the fact that fault diagnosis results are not ideal in the transformer fault diagnosis process, we combine the simplifying of rough sets with support vector machine classification .Then, we build the model of transformer fault diagnosis which is based on the rough sets and support vector machine .Proved by the simulation of true sample, this model can diagnosis the transformer fault effectively and has very high accuracy rate.
Keywords
fault diagnosis; pattern classification; power engineering computing; power transformers; rough set theory; support vector machines; rough set theory; support vector machine classification; transformer fault diagnosis process; Accuracy; Fault diagnosis; Kernel; Power transformers; Support vector machines; Testing; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location
Shanghai
ISSN
2157-4839
Print_ISBN
978-1-4577-0545-8
Type
conf
DOI
10.1109/APPEEC.2012.6307355
Filename
6307355
Link To Document