Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric

Djamel Eddin Abdelli (1) , Thanh Hung Nguyen (2) , Stéphane Clenet (2) , Ahmed Cheriet (1)

1 LGEB - Laboratoire de Génie Electrique [Univ. Biskra]
2 L2EP - Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697

The calculation of the Probability Of Detection (POD) in Non Destructive Eddy Current Testing requires the solution of a stochastic model requiring numerous calls of a numerical model leading to a huge computation time. To reduce this computation time, we propose in this paper to combine either the use of a stochastic metamodel and a mapping which avoids the remeshing step. The stochastic metamodel is constructed using the Least Angle Regression Method. This approach is tested on a axisymmetric problem with 6 random input paramters which shows its efficiency and its accuracy.

Mots clés: Eddy Current Testing; Optical and Magnetic Materials; Probability Of Detection; Electrical and Electronic Engineering; Electronic; Least Angle Regression Method; Stochastic Model

Domaines: Electronique; Energie électrique

Djamel Eddin Abdelli, Thanh Hung Nguyen, Stéphane Clenet, Ahmed Cheriet. Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric. IEEE Transactions on Magnetics, 2019, 55 (6), pp.1-4. ⟨10.1109/TMAG.2019.2893421⟩. ⟨hal-02282008⟩