J. M. Díaz-Chacón, R. B. B. Ovando-Martinez, C. Hernández, M. Arjona
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A Neural-Network Based Model of the Magnetic Nonlinearity of a DC Electromagnet
This paper shows how an Artificial Neural Network model (ANN) can be used to fit the nonlinear magnetic behavior of a DC electromagnet. An ANN model is trained to obtain a generalized function of the B2-?r curve, which is commonly used in an electromagnetic model. Once the generalized function and its derivative are obtained, they are used to solve a magnetostatic nonlinear problem of a DC device using the finite element method and the Newton-Raphson algorithm.
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