Magnetic Characterization of MR Fluid by Means of Neural Networks

Abstract

Magnetorheological and electrorheological fluids manifest a change in rheological behavior when subjected to a magnetic or electric field, respectively, such that they require electrical and magnetic characterization. In this paper, a simple and accurate mathematical model based on a small number of parameters provides the relative magnetic permeability of magnetorheological fluids as a function of the applied magnetic field. Furthermore, for the testing and magnetic characterization of magnetorheological fluids, a new metering equipment setup is implemented. Starting with the achieved experimental data, the mathematical relation μr=f(B) is represented by means of a radial basis function neural network, with neurons having a Gaussian activation function; by means of post-training pruning procedures, the trained neural network is applied using the proposed data. Therefore, the obtained mathematical relation μr=f(B) is in good agreement with the experimental data, with an approximate error of 8%.