Real-time crack characterization in conductive tubes through an adaptive partial least squares approach

Marco Salucci (1) , Shamim Ahmed (1, 2) , Nicola Anselmi (1) , Giacomo Oliveri (1) , Pierre Calmon (3) , Roberto Miorelli (2) , Christophe Reboud (2) , Andrea Massa (1)

1 DISI - Department of Information Engineering and Computer Science (University of Trento )
2 LSME (CEA, LIST) - Laboratoire de Simulation et de Modélisation Électromagnétique (CEA, LIST)
3 DISC (CEA, LIST) - Département Imagerie et Simulation pour le Contrôle (CEA, LIST)

This work deals with the real-time non-destructive testing and evaluation (NDT/NDE) of conductive tubes. An innovative learning-by-examples (LBE) strategy is proposed to address the inversion of eddy current testing (ECT) data. The partial least squares (PLS) features extraction technique is combined with an output space filling (OSF) adaptive sampling strategy in order to collect as much as possible information about the input/output (I/O) relationship to model, mitigating the negative effects of the curse of dimensionality. Robust and accurate predictions are then performed by means of support vector regression (SVR). A preliminary numerical validation is shown to prove the effectiveness of the approach.

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

Marco Salucci, Shamim Ahmed, Nicola Anselmi, Giacomo Oliveri, Pierre Calmon, et al.. Real-time crack characterization in conductive tubes through an adaptive partial least squares approach. 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, Jul 2017, San Diego, United States. pp.21-22, ⟨10.1109/APUSNCURSINRSM.2017.8072053⟩. ⟨hal-01767569⟩