NDLI: Computer applications in fault diagnosis of power transformers

Content Provider	IEEE Xplore Digital Library
Author	Singh, S. Joshi, D.
Copyright Year	2015
Description	Author affiliation: HRIT, Ghaziabad, India (Singh, S.) \|\| EE Dept., DTU, Delhi, India (Joshi, D.)
Abstract	Computers applications have found wide spread applications `human-like abilities', capabilities to make judgments, guesses, change of opinions in fault diagnosis of power transformers in last two decades. Computer has reduced vagueness, uncertainties, analysis times, but quicker remedial actions during off-line and on-line fault diagnostic on power transformers. Data of the dissolved gases in oil-insulation of a power transformer can be incorporated into expert systems to facilitate decision making for fault diagnosis. Due to the diverse gas content of transformer oil, computer based Artificial Intelligence (AI) techniques and expert systems have been applied by the various researchers, scientists, different organizations and utilities. Various AI techniques studied and applied by the researches for dissolved gas analysis (DGA) in power transformers. For high accuracy, time, easiness, economy and to overcome the short falls of individual AI techniques, the combination of two or/and more as hybrid AI techniques are proposed by many researchers.
Starting Page	1216
Ending Page	1223
File Size	211856
Page Count	8
File Format	PDF
ISBN	9789380544151
e-ISBN	9789380544168
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-11
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Bharati Vidyapeeth University, New Delhi
Subject Keyword	Fault diagnosis Support vector machines Dissolved gas analysis (DGA) Hybrid AI techniques Artificial neural networks Oil insulation Individual AI techniques Power transformers Expert systems
Content Type	Text
Resource Type	Article

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