Salucci, M. and Anselmi, N. and Oliveri, G. and Massa, A. (2016) Fast Inversion of Eddy Current Testing Data Through a Learning-by-Examples Approach for Robust Crack Localization. Technical Report. University of Trento.
Text
Fast_Inversion_of_Eddy_Current_Testing_Data_Through_a_Learning-by-Examples_Approach_for_Robust_Crack_Localization.v2.pdf Download (986kB) |
Abstract
This document presents a new learning-by-example (LBE) technique for the computationally-efficient inversion of eddy current testing (ECT) data in non-destructive testing and evaluation (NDT-NDE) scenarios. More precisely, the developed approach exploits a uniform sampling strategy to build a training set of input/output (I/O) pairs and exploits such information to train a Support Vector Regressor (SVR). During the on-line testing phase, previously-unseen ECT data are given as input to the trained model in order to predict the position of a single narrow crack within a planar conductive structure. Some representative numerical results are shown, in order to preliminarily assess the capabilities of the developed approach when dealing with the presence of a non-negligible amount of noise on test data.
Item Type: | Monograph (Technical Report) |
---|---|
Uncontrolled Keywords: | Eddy current testing, inverse scattering, nondestructive testing and evaluation, statistical learning, learning-by-examples, support vector regression |
Subjects: | M Methodologies > M LBE Learning-by-Example Methods |
Divisions: | University of Trento > Faculty of Telecommunications, Electronics Engineering > Department of Information Engineering and Computer Science > ELEDIA Research Center |
URI: | http://www.eledia.org/students-reports/id/eprint/712 |
Actions (login required)
View Item |