Open AccessFlaw characterization in conductive media based on pulsed Eddy current measurements: A fast non‐iterative inversion approach
Author(s) -
Miorelli Roberto,
Skarlatos Anastassios,
Reboud Christophe
Publication year - 2021
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/smt2.12027
Subject(s) - eddy current , electrical conductor , inversion (geology) , materials science , characterization (materials science) , iterative method , electronic engineering , acoustics , nuclear magnetic resonance , computer science , algorithm , electrical engineering , physics , engineering , geology , nanotechnology , composite material , paleontology , structural basin
This paper proposes a non‐iterative procedure for flaw(s) characterization based on Pulsed Eddy Current Testing (PECT) signals analysis. The adopted inversion strategy is based on the use of supervised statistical learning algorithms. A numerical forward solver, based on the Finite Integration Technique (FIT), is used for the generation of the training data (the input‐targets couples of the learning algorithm). Predictions are then carried out in almost real‐time using a non‐linear kernel based regression method, known as kernel ridge regression. It turns out that the direct fit of the regression model to the raw PECT signals may lead to poor prediction accuracy due to the large cardinality of PECT signals. To remedy this problem, an adaptive sampling strategy has been adopted in this work. The performance of the proposed methodology is discussed and compared with solutions proposed in the literature.