Salucci, M. and Anselmi, N. and Oliveri, G. and Massa, A. (2016) An Innovative Learning-by-Examples Approach for Crack Localization Based on Partial Least Squares and Adaptive Sampling. Technical Report. University of Trento.
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Abstract
This document presents an innovative adaptive learning-by-examples (LBE) strategy for accurate crack localization in planar conductive specimens. The developed approach exploits a Partial Least Squares (PLS) feature extraction technique and an adaptive sampling strategy in order to build optimal training sets of input/output (I/O) pairs. Such information is then used to train, during a preliminary off-line phase, a Support Vector Regressor (SVR) in order to build a fast surrogate model of the inverse operator linking ECT data and crack position. Finally, during the on-line test phase previously-unseen ECT measurements are given as input to the trained SVR in order to retrieve an estimation of the defect coordinates. Some numerical results are shown, in order to verify the effectiveness of the proposed LBE inversion methodology.
| Item Type: | Monograph (Technical Report) |
|---|---|
| Uncontrolled 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 |
| Subjects: | M Methodologies > M LBE Learning-by-Example Methods |
| URI: | http://www.eledia.org/students-reports/id/eprint/713 |
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