Eddy-current testing with the Expected Improvement optimization algorithm

Abstract : This paper presents an inverse problem methodology in the domain of non-destructive testing, and more precisely eddy-current testing. Our objective is to use a precise but expensive-to-evaluate model of the electromagnetic induction phenomenon in a conductive material and to estimate the characteristics of a flaw by minimization of a regularized criterion with the \emph{Expected Improvement (EI)} global optimization algorithm. The EI algorithm is designed to estimate a global optimum of a function with a restricted budget of function evaluations. Thus, we expect to be able to estimate the characteristics of a flaw with a relatively low cost despite resorting to an expensive model of the induction phenomenon. The efficiency of the approach is discussed in the light of preliminary numerical examples obtained using synthetic data.
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Sandor Bilicz, Emmanuel Vazquez, Jozsef Pavo, Marc Lambert, Szabolcs Gyimothy. Eddy-current testing with the Expected Improvement optimization algorithm. 15th IFAC Symposium on System Identification, SYSID 2009, Jul 2009, Saint-Malo, France. ⟨hal-00446202⟩

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