Vibration-based Damage Identification in Sandwich Beams using Artificial Neural Networks

Date

2010-09-17

Author

Şahin, Melin

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This study investigates the effectiveness of the combination of global (natural frequency) and local (curvature mode shape) vibration characteristics of a glass fibre reinforced plastic sandwich beam-like structure when introduced to artificial neural networks for severity and location prediction of various damage with different extent at different locations. A finite element modelling and analysis tool is used to obtain the dynamic characteristics of both intact and damaged cantilever sandwich structures and the sensitivity analyses aiming at finding the necessary features are performed. Finally, predictions are made for the damage quantification and localisation via designed supervised feed-forward backpropagation artificial neural networks.

Subject Keywords

Sandwich structures, Finite element analysis, Vibration-based features, Artificial neural networks, Damage identification

URI

https://hdl.handle.net/11511/54669

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Department of Aerospace Engineering, Conference / Seminar

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Citation Formats

M. Şahin, “Vibration-based Damage Identification in Sandwich Beams using Artificial Neural Networks,” 2010, vol. 93, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54669.