%0 Report
%9 Technical Report
%A Salucci, M.
%A Anselmi, N.
%A Oliveri, G.
%A Massa, A.
%D 2016
%F elediasc12:716
%K Eddy current testing, inverse scattering, nondestructive testing and evaluation, statistical learning, learning-by-examples, support vector regression, output space filling, partial least squares, adaptive sampling
%T An Innovative Adaptive LBE Technique for Real-Time Crack Characterization: An Experimental Study
%U http://www.eledia.org/students-reports/716/
%X This document deals with the real-time retrieval of the position of a crack embedded within a conductive planar structure starting from eddy current testing (ECT) measurements in a non-destructive testing and evaluation (NDT-NDE) scenario. Towards this end, an innovative adaptive learning-by-examples (LBE) technique has been developed. It is based on the innovative combination of a Partial Least Squares (PLS) features extraction technique and an adaptive sampling strategy to generate optimal training sets. Such information is used to train a Support Vector Regressor (SVR) in order to build a fast but accurate predictor of the crack descriptors staring from previously-unseen ECT measurements during the on-line testing phase.  The proposed LBE inversion strategy, previously validated on numerical simulations, is here tested against real laboratory-controlled experimental data coming from the World Federation of NDE Centers (FNDEC) “2008 Eddy Current Benchmarks”.