Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks

Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite ai...

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Main Authors: Mahzan, Shahruddin, J. Staszewski, Wieslaw, Worden, Keith
Format: Article
Language:en
Published: KoreaScience 2010
Subjects:
Online Access:http://eprints.uthm.edu.my/7847/1/J8493_9d2fd2d9cd0cf45cad1f0dc769b13ae3.pdf
http://eprints.uthm.edu.my/7847/
http://dx.doi.org/10.12989/sss.2010.6.2.147
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author Mahzan, Shahruddin
J. Staszewski, Wieslaw
Worden, Keith
author_facet Mahzan, Shahruddin
J. Staszewski, Wieslaw
Worden, Keith
author_sort Mahzan, Shahruddin
building UTHM Library
collection Institutional Repository
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
continent Asia
country Malaysia
description Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. A series of impacts is performed experimentally on a composite aircraft wing�box structure instrumented with low-profile, bonded piezoceramic sensors. The strain data are used for learning in the Neural Network approach. The triangulation procedure utilises the same data to establish impact velocities for various angles of strain wave propagation. The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.
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institution Universiti Tun Hussein Onn Malaysia
language en
publishDate 2010
publisher KoreaScience
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spelling my.uthm.eprints-78472022-10-17T06:16:04Z http://eprints.uthm.edu.my/7847/ Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks Mahzan, Shahruddin J. Staszewski, Wieslaw Worden, Keith T Technology (General) Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. A series of impacts is performed experimentally on a composite aircraft wing�box structure instrumented with low-profile, bonded piezoceramic sensors. The strain data are used for learning in the Neural Network approach. The triangulation procedure utilises the same data to establish impact velocities for various angles of strain wave propagation. The study demonstrates that both approaches are capable of good impact location estimates in this complex structure. KoreaScience 2010 Article PeerReviewed text en http://eprints.uthm.edu.my/7847/1/J8493_9d2fd2d9cd0cf45cad1f0dc769b13ae3.pdf Mahzan, Shahruddin and J. Staszewski, Wieslaw and Worden, Keith (2010) Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks. Smart Structures and Systems, 6 (2). pp. 147-165. ISSN 1738-1584 http://dx.doi.org/10.12989/sss.2010.6.2.147
spellingShingle T Technology (General)
Mahzan, Shahruddin
J. Staszewski, Wieslaw
Worden, Keith
Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title_full Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title_fullStr Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title_full_unstemmed Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title_short Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
title_sort experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
topic T Technology (General)
url http://eprints.uthm.edu.my/7847/1/J8493_9d2fd2d9cd0cf45cad1f0dc769b13ae3.pdf
http://eprints.uthm.edu.my/7847/
http://dx.doi.org/10.12989/sss.2010.6.2.147
url_provider http://eprints.uthm.edu.my/