Dynamic Electromagnetic Induction Imaging of Molten Metal Flow using the Kalman Filter
M. Soleimani1, X. Ma2, A. J. Peyton2
1 William Lee Innovation Centre, School of Materials, The University of Manchester, PO Box 88, Manchester M60 1QD, UK, Email: M.Soleimaniemail@example.com
2 School of Electrical and Electronic Engineering, The University of Manchester, PO Box 88, Manchester M60 1QD, UK
A dynamic complex electromagnetic induction imaging technique is developed with the aid of the linear Kalman filter (LKF) for real-time reconstruction of molten metal flow. The forward problem is solved by an edge finite element method. The inverse problem is treated as a state estimation problem. The conductivity distribution is estimated with the aid of the Kalman estimator. The Kalman gain matrix is pre-computed and stored off-line to minimize the on-line computational time. Simulation and experimental tests are reported to illustrate the reconstruction performances in the sense of spatio-temporal resolution in a simplified geometry of the metal flow in continuous casting.
Keywords Electromagnetic induction tomography, permittivity and conductivity distribution, inverse problem, dynamic imaging, Kalman filter
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