Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations

With the introduction of damage tolerance-based design philosophies, the demand for reliable and robust structural health monitoring (SHM) procedures for aerospace composite structures is increasing rapidly. The performance of supervised learning algorithms for SHM depends on the amount of labeled a...

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Bibliographic Details

Published in:	Composite structures Vol. 291; p. 115579
Main Authors:	Rautela, Mahindra, Senthilnath, J., Monaco, Ernesto, Gopalakrishnan, S.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.07.2022
Subjects:	Convolutional autoencoders (CAE) Delamination detection Independent component analysis (ICA) One-class support vector machines (ocSVM) Principal component analysis (PCA) Delamination detection Independent component analysis (ICA) One-class support vector machines (ocSVM) Principal component analysis (PCA) Convolutional autoencoders (CAE)
ISSN:	0263-8223, 1879-1085
Online Access:	Get full text
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