relation: http://www.eledia.org/students-reports/712/
title: Fast Inversion of Eddy Current Testing Data Through a Learning-by-Examples Approach for Robust Crack Localization
creator: Salucci, M.
creator: Anselmi, N.
creator: Oliveri, G.
creator: Massa, A.
subject: M LBE Learning-by-Example Methods
description: 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.
publisher: University of Trento
date: 2016
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/712/1/Fast_Inversion_of_Eddy_Current_Testing_Data_Through_a_Learning-by-Examples_Approach_for_Robust_Crack_Localization.v2.pdf
identifier:   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.