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International Society for Industrial Process Tomography

5th World Congress on Industrial Process Tomography

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:

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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