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Estimation of The Partial Discharge Position Using Neural Networks in The Power Transformers

This paper presents a new method for estimating partial discharge position using improved cross-correlation technique and neural networks in the power transformer. When ultrasonic signal is occurred by partial discharge, we detected these signals and calculated cross-correlation values with Hamming window. Also, we estimated partial discharge position using neural network with cross-correlation values. In the result of case study, we can estimate more accurately the partial discharge position than any other algorithms.