Metamodel-based Markov-Chain-Monte-Carlo parameter inversion applied in eddy current flaw characterization

Caifang Cai 1 Roberto Miorelli 2 Marc Lambert 3 Thomas Rodet 4 Dominique Lesselier 1 Pierre-Emile Lhuillier 5
1 L2S - Laboratoire des signaux et systèmes
2 LSME - Laboratoire de Simulation et de Modélisation Électromagnetique
DISC - Département Imagerie et Simulation pour le Contrôle : DRT/LIST/DISC
3 GeePs - Laboratoire Génie électrique et électronique de Paris
4 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie
5 EDF R&D MMC - Matériaux et Mécanique des Composants
Abstract : Flaw characterization in eddy current testing usually requires to solve a nonlinear inverse problem. Due to high computational cost, Markov Chain Monte Carlo (MCMC) methods are hardly employed since often needing many forward evaluations. However, they have good potential in dealing with complicated forward models and they do not reduce to only providing the parameters sought. Here, we introduce a computationally-cheap surrogate forward model into a MCMC algorithm for eddy current flaw characterization. Due to the use of a database trained off-line, we benefit from the MCMC algorithm for getting more information and we do not suffer from the computational burden. Numerous experiments are carried out to validate the approach. The results include not only the estimated parameters, but also standard deviations, marginal densities and correlation coefficients between two parameters of interest.
Keywords : Bayesian flaw characterization inversion eddy-current non-destructive testing MCMC metamodel
Document type :
Journal articles
Complete list of metadatas
https://hal-centralesupelec.archives-ouvertes.fr/hal-01634071
Contributor : Dominique Lesselier <>
Submitted on : Monday, November 13, 2017 - 4:37:35 PM
Last modification on : Monday, August 12, 2019 - 1:24:02 PM

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CENTRALESUPELEC | CNRS | UNIV-CERGY | ENS-CACHAN | CNAM | INSMI | TDS-MACS | L2S | SATIE | CEA | IFSTTAR | SUP_LSS | SUP_SIGNAUX | UNIV-PARIS-SACLAY | PIEM | DRT | LIST | EDF | CEA-UPSAY | SATIE-SIAME | UNIV-HESAM | SORBONNE-UNIVERSITE | GEEPS | SU-SCIENCES

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Caifang Cai, Roberto Miorelli, Marc Lambert, Thomas Rodet, Dominique Lesselier, et al.. Metamodel-based Markov-Chain-Monte-Carlo parameter inversion applied in eddy current flaw characterization. NDT and E International, Elsevier, 2018, 99, pp.13-22. ⟨10.1016/j.ndteint.2018.02.004⟩. ⟨hal-01634071⟩

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