Real-Time Flaw Characterization Through Learning-by-Examples Techniques: A Comparative Study Applied to ECT

Shamim Ahmed (1) , Roberto Miorelli (1) , Marco Salucci (2, 3) , Andrea Massa (2, 3)

1 LSME (CEA, LIST) - Laboratoire de Simulation et de Modélisation Électromagnétique (CEA, LIST)
2 L2S - Laboratoire des signaux et systèmes
3 UNITN - Università degli Studi di Trento = University of Trento

In this paper, real time flaw characterization inside the structure under test (SUT) exploiting Learning by Examples (LBE) strategies is illustrated in the framework of Electromagnetic NDT (E-NDT). In particular, several LBE methodologies are investigated when dealing with the inversion of Eddy Current Testing (ECT) data. The performance of LBE algorithms is evaluated in terms of CPU time efficiency, and prediction accuracy on noisy data. Towards this end, a comparison between different regression techniques is shown by considering both synthetic and real experimental ECT data.

Domaines: Electromagnétisme; Traitement du signal et de l'image [eess.SP]

Shamim Ahmed, Roberto Miorelli, Marco Salucci, Andrea Massa. Real-Time Flaw Characterization Through Learning-by-Examples Techniques: A Comparative Study Applied to ECT. Studies in Applied Electromagnetics and Mechanics, 2017, 42, pp.228-235. ⟨10.3233/978-1-61499-767-2-228⟩. ⟨hal-01774317⟩