Affiliations: [a] College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, China
Correspondence:
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Corresponding author: Xiucheng Liu, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
Abstract: Ising model is a promising tool for predicting magnetic Barkhausen noise (MBN) signal on electromagnetic nondestructive evaluation (ENDE). However, theoretical prediction of MBN of composite ferromagnetic materials using Ising model is seldom reported. In this study, we incorporate double Boltzmann transition function with the exchange coupling efficiency (J) of Ising model to achieve simulation of MBN in layered materials. The transition behavior of J was assumed to represent the changes in magnetic properties from hard layer to soft layer. Monte Carlo algorithm is used to solve the Ising model to obtain the MBN of layered material. The influence of the volume fraction (p) of hard layer in the double Boltzmann transition function on the shape of MBN profiles was investigated through both simulation and experiments. In the experiments, two-layer ferromagnetic materials was laminated using SAE 1065 carbon steel films of different thickness and a base strip of SAE 1045 carbon steel with a thickness of 20 mm. Both simulation and experimental results show that the MBN peak of soft layer gradually descends with the increase in thickness of SAE 1065 (or the volume fraction of hard layer). The second-order Gaussian function was used to fit the MBN envelop for extract the peaks of hard and soft layers from both experimental and simulation results. The ratio of the MBN peak of hard layer to soft layer demonstrates monotonously increasing trend as the value of p increases. Therefore, ratio of the MBN peak can act as good indicator for qualitative characterization of the changes of thickness or volume fraction of hard layer in two-layer ferromagnetic materials.
Keywords: magnetic Barkhausen noise, Ising model, layered ferromagnetic materials, Monte Carlo algorithm
