Neural network based model for incorporating the thermal effect on the magnetic hysteresis of the 3F3 material

Article type: Research Article

Authors: Nouicer, Abdelmadjid^a

Affiliations: [a] Department of Electrical Engineering, University of Skikda, Route Elkhadaik BP26, Skikda 21000, Algeria. E-mail: [email protected]

Abstract: This paper presents a new approach for incorporating the thermal effect on the magnetic hysteresis of the 3F3 material. The proposed algorithm is based on the knowledge of the magnetic flux density spectrum for some temperatures. So, a feed-forward neural network is trained to learn the relation between the rank of harmonics, the temperature and the amplitude of each harmonic. To construct the hysteresis loop for a new value of the temperature, the neural network predicts the spectrum of the magnetic flux density B which is transformed back to the time domain.

Keywords: Discrete fourier transform (DFT), ferrite 3f3 material, magnetic hysteresis, neural networks, thermal behaviour

DOI: 10.3233/JAE-141778

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 46, no. 1, pp. 281-286, 2014