@techreport{elediasc12716,
       publisher = {University of Trento},
            year = {2016},
            type = {Technical Report},
           title = {An Innovative Adaptive LBE Technique for Real-Time Crack Characterization: An Experimental Study},
          author = {M. Salucci and N. Anselmi and G. Oliveri and A. Massa},
             url = {http://www.eledia.org/students-reports/716/},
        abstract = {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?.},
        keywords = {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}
}