Design of a high-torque machine with two integrated motors axes reducing the electric vehicle consumption

This paper proposes a method for discrimination between internal faults and inrush currents in power transformers based on mathematical morphology (MM), a well-established theory in computer vision. Here, the feature extraction property of MM is used for the discrimination. It is shown that mathematical morphology (MM) is as efficient as that of wavelet technique in discriminating inrush and internal fault currents and enjoys much less computational complexity than wavelet technique. Extensive simulations have verified that this method is more reliable and simple for various load conditions and over excitation condition.