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An application of the inverse solution for electric current distribution from magnetic field measurements in aluminium electrolysis cells

An application of the inverse solution for electric current distribution from magnetic field measurements in aluminium electrolysis cells

Bojarevics, Valdis ORCID logoORCID: https://orcid.org/0000-0002-7326-7748 and Evans, James W. (2012) An application of the inverse solution for electric current distribution from magnetic field measurements in aluminium electrolysis cells. Journal of Iron and Steel Research International, 19 (S1-1). pp. 561-565. ISSN 1006-706X

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Abstract

A mathematical theory and the software application based on the full MHD model of the electrolysis cell is used to predict the electric current distribution over the anodes from the measurement of magnetic fields at specifically defined node points assumed to be available from the wireless sensors. The full 3d busbar configuration of two different commercial cells are used for the model simulations. It is demonstrated that a unique solution for the electric current can be obtained when two sensors per each anode are used to detect the single component of magnetic field. The mathematical software is tested for the sensitivity to the busbar configuration complexity. The ability to monitor continuously the electric current distribution to high accuracy helps to control disturbances and deviations from a normal production process.

Item Type: Article
Additional Information: [1] This article is in the hardcopy of the Journal of Iron and Steel Research International, Vol. 19, Supplement 1-[Part]1. [2] The Journal of Iron and Steel Research International is sponsored by China Iron and Steel Research Institute Group.
Uncontrolled Keywords: aluminium electrolysis cell, inverse electromagnetic problem, electric current network, magnetic field
Subjects: Q Science > QC Physics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Science & Engineering Group
Related URLs:
Last Modified: 27 Apr 2020 22:57
URI: http://gala.gre.ac.uk/id/eprint/9242

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