Neural network and Fourier descriptor macromodeling dynamic hysteresis

For the evaluation of the dynamic hysteresis loops, a Neural Network (NN) c ombined with the Fourier Descriptor (FD) technique can be a simple computat ional instrument alternative to the classical approach. This method is suit able in those cases in which a distorted periodic magnetic held H, or flux density B, excites, in steady state, the ferromagnetic nucleus of a de,ice. The dependence of the hysteresis loop from the magnetic field frequency; h as been successfully evaluated by NN while, by means of the Fourier Descrip tor, the effects of the magnetic field distortion have been efficiently pre dicted. Numerical results compared with those from other models (i.e. Jiles model) and experimental data are presented in the end.