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Determination of transformer health condition using artificial neural networks

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3 Author(s)
Abu-Elanien, A.E.B. ; Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada ; Salama, M.M.A. ; Ibrahim, M.

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.

Published in:

Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on

Date of Conference:

15-18 June 2011

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