Neural network and Fourier descriptor macromodeling dynamic hysteresis

For the evaluation of the dynamic hysteresis loops, a Neural Network (NN) combined with the Fourier Descriptor (FD) technique can be a simple computational instrument alternative to the classical approach. This method is suitable in those cases in which a distorted periodic magnetic field H, or flux density B, excites, in steady state, the ferromagnetic nucleus of a device. The dependence of the hysteresis loop from the magnetic field frequency, has been successfully evaluated by NN, while, by means of the Fourier Descriptor, the effects of the magnetic field distortion have been efficiently predicted. Numerical results compared with those from other models (i.e. Jiles model) and experimental data are presented in the end.