NDLI: Determination of transformer health condition using artificial neural networks

Content Provider	IEEE Xplore Digital Library
Author	Abu-Elanien, A.E.B. Salama, M.M.A. Ibrahim, M.
Copyright Year	2011
Description	Author affiliation: Department of Electrical and Computer Engineering, University of Waterloo Waterloo, ON, Canada (Abu-Elanien, A.E.B.; Salama, M.M.A.; Ibrahim, M.)
Abstract	This paper presents a method to estimate a transformer health condition based on diagnostic tests. A feed forward artificial neural network (FFANN) is used to find the health index of the transformer. The health index is used to find the health condition of the transformer. The training of the FFANN is done using real measurements of 59 working transformers. The testing of the trained neural network performance is done using real data for 29 working transformers. The performance evaluation of the trained FFANN shows that the trained neural network is reliable in finding the health condition of any working transformer.
Starting Page	1
Ending Page	5
File Size	277697
Page Count	5
File Format	PDF
ISBN	9781612849195
e-ISBN	9781612849225
DOI	10.1109/INISTA.2011.5946173
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-15
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Condition monitoring Health condition Transformer Health index Artificial neural networks Oil insulation Dissolved gas analysis Asset management Indexes Furans analysis Power transformer insulation Testing
Content Type	Text
Resource Type	Article

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