Characterization of Surface Cracks Using Eddy Current NDT Simulation by 3D-FEM and Inversion by Neural Network

Authors

  • B. Helifa Laboratoire de Physique des Matériaux Université de Laghouat, BP 37G, Laghouat 03000, Algérie
  • M. Féliachi IREENA-IUT Université de Nantes – L’UNAM, CRTT, BP 406, 44602 Saint-Nazaire cedex, France
  • I. K. Lefkaier Laboratoire de Physique des Matériaux Université de Laghouat, BP 37G, Laghouat 03000, Algérie
  • F. Boubenider Laboratoire de Physique des Matériaux USTHB, Bab-Ezzouar, Alger 016000, Algérie
  • A. Zaoui EMP BP 17 Bordj El Bahri 16100 Alger, Algérie
  • N. Lagraa Laboratoire d’Informatique et de Mathématique Université de Laghouat, BP 37G, Laghouat 03000, Algérie

Keywords:

3D finite element simulation, eddy current NDT, neural network, surface cracks

Abstract

In this work, we suggest an approach of signal inversion from sensors used in eddy current (EC) nondestructive testing (NDT). The aim is to characterize surface cracks from the EC signal. A methodology that combines 3D finite element (FEM) simulation and a data inversion by neural networks (NN) is proposed. We show that the use of a set of numerical measurements representing the EC signature of surface crack enables to remedy of the unicity problem. The obtained results show that the developed approach leads to the quantification of the crack.

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References

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Published

2021-08-18

How to Cite

[1]
B. . Helifa, M. . Féliachi, . I. K. . Lefkaier, F. . Boubenider, A. . Zaoui, and N. . Lagraa, “Characterization of Surface Cracks Using Eddy Current NDT Simulation by 3D-FEM and Inversion by Neural Network”, ACES Journal, vol. 31, no. 02, pp. 187–194, Aug. 2021.

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