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Characterisation of multiple conducting permeable objects in metal detection by polarizability tensors
Mathematical Methods in the Applied Sciences, Volume: 42, Issue: 3, Pages: 830 - 860
Swansea University Authors:
Paul Ledger, Alan Amad
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DOI (Published version): 10.1002/mma.5387
Abstract
Realistic applications in metal detection involve multiple inhomogeneousâconducting permeable objects, and the aim of this paper is to characterise such objects by polarizability tensors. We show that, for the eddy current model, the leading order terms for the perturbation in the magnetic field, du...
Published in: | Mathematical Methods in the Applied Sciences |
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ISSN: | 0170-4214 1099-1476 |
Published: |
2019
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa45292 |
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Abstract: |
Realistic applications in metal detection involve multiple inhomogeneousâconducting permeable objects, and the aim of this paper is to characterise such objects by polarizability tensors. We show that, for the eddy current model, the leading order terms for the perturbation in the magnetic field, due to the presence of N small conducting permeable homogeneous inclusions, comprises of a sum of N terms with each containing a complex symmetric rank 2 polarizability tensor. Each tensor contains information about the shape and material properties of one of the objects and is independent of its position. The asymptotic expansion we obtain extends a previously known result for a single isolated object and applies in situations where the object sizes are small and the objects are sufficiently well separated. We also obtain a second expansion that describes the perturbed magnetic field for inhomogeneous and closely spaced objects, which again characterises the objects by a complex symmetric rank 2 tensor. The tensor's coefficients can be computed by solving a vector valued transmission problem, and we include numerical examples to illustrate the agreement between the asymptotic formula describing the perturbed fields and the numerical prediction. We also include algorithms for the localisation and identification of multiple inhomogeneous objects. |
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College: |
Faculty of Science and Engineering |
Issue: |
3 |
Start Page: |
830 |
End Page: |
860 |