Using neural networks in the identification of Preisach-type magnetostriction and field-temperature models

Abstract

Two-dimensional Preisach models were proposed as a possible approach for modeling one-dimensional magnetostriction as well as field-temperature effects on magnetized bodies. The use of neural network machinery is suggested to solve identification problems of such models. The suggested technique was implemented and experimentally tested. Testing results show that this technique can lead to reasonably accurate simulation results.