A robust inversion method for quantitative 3D shape reconstruction from coaxial eddy-current measurements

Houssem Haddar 1 Zixian Jiang 1 Mohamed-Kamel Riahi 2
1 DeFI - Shape reconstruction and identification
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France, Polytechnique - X, CNRS - Centre National de la Recherche Scientifique : UMR7641
Abstract : This work is motivated by the monitoring of conductive clogging deposits in steam generator at the level of support plates. One would like to use multistatic measurements from coaxial coils in order to obtain estimates on the clogging volume. We propose a 3D shape optimization technique based on simplified shape parametrization of the deposit. This parametrization is adapted to the measurement nature and resolution. The direct problem is modeled by the eddy current approximation of time-harmonic Maxwell’s equations in the low frequency regime. A potential formulation is adopted in order to easily handle the complex topology of the industrial problem setting. We first characterize the shape derivatives of the deposit impedance signal using an adjoint field technique. For the inversion procedure, the direct and adjoint problems have to be solved for each vertical probe position which is excessively time- and memory-consuming. To overcome this difficulty, we propose and discuss a steepest descent method based on a invariant mesh. Numerical experiments are presented to illustrate the convergence and the efficiency of the method.
Type de document :
Article dans une revue
Journal of Scientific Computing, Springer Verlag, 2016, pp.31. 〈10.1007/s10915-016-0241-6〉
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https://hal.inria.fr/hal-01110299
Contributeur : Houssem Haddar <>
Soumis le : mardi 27 janvier 2015 - 18:53:42
Dernière modification le : jeudi 11 janvier 2018 - 06:22:14

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Houssem Haddar, Zixian Jiang, Mohamed-Kamel Riahi. A robust inversion method for quantitative 3D shape reconstruction from coaxial eddy-current measurements. Journal of Scientific Computing, Springer Verlag, 2016, pp.31. 〈10.1007/s10915-016-0241-6〉. 〈hal-01110299〉

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