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Data fusion and non-destructive testing of damaged fiber-reinforced laminates

Abstract : Efficient strategies for non-destructive testing of damaged composite laminates modeled from homogenization of fiber-reinforced polymers could in- volve fused data. Here, those are from electromagnetic and infrared thermographic modalities, for which semi-analytical models of the interaction are available. Focus is on inter-layer delaminations. Paths forward are outlined, mostly within the realm of Bayesian approaches and of convolutional neural networks, both of wide breadth and the second ones not involving too many prior regularization factors.
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Contributor : Dominique Lesselier Connect in order to contact the contributor
Submitted on : Wednesday, March 23, 2022 - 5:23:04 PM
Last modification on : Friday, August 5, 2022 - 2:58:08 PM


  • HAL Id : hal-03617825, version 1


Valentin Noël, Thomas Rodet, Dominique Lesselier. Data fusion and non-destructive testing of damaged fiber-reinforced laminates. 25th International Workshop on Electromagnetic Nondestructive Evaluation (ENDE'22), Center for Energy Research, Jun 2022, Budapest, Hungary. ⟨hal-03617825⟩



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