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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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KoreaScience
2010
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7847/1/J8493_9d2fd2d9cd0cf45cad1f0dc769b13ae3.pdf |
| _version_ | 1825710459703001088 |
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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 |
| collection | UTHM |
| 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. |
| first_indexed | 2024-03-05T21:57:56Z |
| format | Article |
| id | uthm.eprints-7847 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:57:56Z |
| publishDate | 2010 |
| publisher | KoreaScience |
| record_format | dspace |
| spelling | 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 |
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