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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Mustapha, F.
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Topics
Publications (9/9 displayed)
- 2016The Effect of Customized Woven and Stacked Layer Orientation on Tensile and Flexural Properties of Woven Kenaf Fibre Reinforced Epoxy Compositescitations
- 2011Optimal Sintering Procedure to Fabrication of Functionally Graded Hydroxyapatite-titaniumcitations
- 2011Fabrication of Functionally Graded Hydroxyapatite-Titanium by Applying Optimal Sintering Procedure and Powder Metallurgy
- 2008Damage localisation in a stiffened composite panel
- 2008Damage localisation in a stiffened composite panelcitations
- 2007Damage location in a stiffened composite panel using lamb waves and neural networks
- 2007Damage detection using stress waves and multivariate statistics, an experimental case study of an aircraft componentcitations
- 2007Damage location in a stiffened composite panel using Lamb waves and neural networks
- 2002A prototype knowledge-based system for material selection of ceramic matrix composites of automotive engine componentscitations
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article
Damage localisation in a stiffened composite panel
Abstract
This work was conducted as part of the Aircraft Reliability Through Intelligent Materials Application (ARTIMA) European Union project. It presents a case study of damage detection in a curved carbon-fibre reinforced panel with two omega stiffeners which was investigated using ultrasonic Lamb waves. The statistical technique of outlier analysis was used here as a way of pre-processing experimental data prior to damage classification. Multilayer perceptron neural networks were used here for both classification and regression problems of damage detection. It was then investigated whether using wavelet analysis to perform prior wavelet decompositions of experimental data could facilitate damage classification.<br/>