期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：10
出版社：S.S. Mishra
摘要：Power transformer is a prime equipment of the transmission and distribution system. It is to be continuously monitored for all the types of incipient faults. Many conventional methods are available to diagnose its performance .In this paper, artificial intelligence methods especially neural networks are applied in fault diagnosis of power transformer. Their diagnosis ability in terms of accuracy and network structure using supervised and unsupervised learning is presented. The approach revealed better performance of some of the networks; which is summarized at the end
关键词：Artificial intelligence; dissolved gas in oil analysis (DGA); fault diagnosis; RBF; SOM; supervised and ;unsupervised networks
