Fuzzy and Multilayer Perceptron for Evaluation of HV Bushings
Artificial Intelligence
2007-05-23 v1 Neural and Evolutionary Computing
Abstract
The work proposes the application of fuzzy set theory (FST) to diagnose the condition of high voltage bushings. The diagnosis uses dissolved gas analysis (DGA) data from bushings based on IEC60599 and IEEE C57-104 criteria for oil impregnated paper (OIP) bushings. FST and neural networks are compared in terms of accuracy and computational efficiency. Both FST and NN simulations were able to diagnose the bushings condition with 10% error. By using fuzzy theory, the maintenance department can classify bushings and know the extent of degradation in the component.
Keywords
Cite
@article{arxiv.0705.2305,
title = {Fuzzy and Multilayer Perceptron for Evaluation of HV Bushings},
author = {Sizwe M. Dhlamini and Tshilidzi Marwala and Thokozani Majozi},
journal= {arXiv preprint arXiv:0705.2305},
year = {2007}
}
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7 pages