Article

Selection of Measurement Modality for Magnetic Material Characterization of an Electromagnetic Device Using Stochastic Uncertainty Analysis

IEEE Transactions on Magnetics (Impact Factor: 1.42). 12/2011; DOI: 10.1109/TMAG.2011.2151870
Source: IEEE Xplore

ABSTRACT Magnetic material properties of an electromagnetic device (EMD) can be estimated by solving an inverse problem where electromagnetic or mechanical measurements are adequately interpreted by a numerical forward model. Due to measurement noise and uncertainties in the forward model, errors are made in the reconstruction of the material properties. This paper describes the formulation and implementation of a time-efficient numerical error estimation procedure for predicting the optimal measurement modality that leads to minimal error resolution in magnetic material characterization. We extended the traditional Cramér-Rao bound technique for error estimation due to measurement noise only, with stochastic uncertain geometrical model parameters. Moreover, we applied the method onto the magnetic material characterization of a Switched Reluctance Motor starting from different measurement modalities: mechanical; local and global magnetic measurements. The numerical results show that the local magnetic measurement modality needs to be selected for this test case. Moreover, the proposed methodology is validated numerically by Monte Carlo simulations, and experimentally by solving multiple inverse problems starting from real measurements. The presented numerical procedure is able to determine a priori error estimation, without performing the very time consuming Monte Carlo simulations.

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    ABSTRACT: The magnetic characteristics of the electromagnetic devices' core materials can be recovered by solving an inverse problem, where sets of measurements need to be properly interpreted using a forward numerical model of the device. However, the uncertainties of the geometrical parameter values in the forward model lead to appreciable recovery errors in the recovered values of the material parameters. In this paper, we propose an effective inverse approach technique, in which the influences of the uncertainties in the geometrical model parameters are minimized. In this proposed approach, the cost function that needs to be minimized is adapted with respect to the uncertain geometrical model parameters. The proposed methodology is applied onto the identification of the magnetizing B–H curve of the magnetic material of an EI core inductor. The numerical results show a significant reduction of the recovery errors in the identified magnetic material parameter values. Moreover, the proposed methodology is validated by solving an inverse problem starting from real magnetic measurements.
    Journal of Magnetism and Magnetic Materials 04/2012; 324(7):1353–1359. · 1.83 Impact Factor

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