Prediction of multiple magnetic dipole model parameters from near field measurements employing stochastic algorithms

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Abstract

In this paper, the problem of predicting far field magnitude from near field measurements of an equipment under test (EUT) is studied. Firstly, a multiple magnetic dipole model is developed to simulate the magnetic behavior of the EUT. The parameters of the model (dipoles positions and magnetic moments) are calculated using the values of the near field applying the Particle Swarm Optimization (PSO) algorithm. For the evaluation of the method, extended simulations were conducted, producing theoretical values and distorting them with noise, and then the developed algorithm was used to create the proper model. Finally, the theoretical results are compared to the field assessments the proper models produced.

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Kapsalis, N. C., Kakarakis, S. D. J., & Capsalis, C. N. (2012). Prediction of multiple magnetic dipole model parameters from near field measurements employing stochastic algorithms. Progress in Electromagnetics Research Letters, 34, 111–122. https://doi.org/10.2528/PIERL12030905

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