Optimized FBG sensor network for efficient detection of a delamination in FRP structures
Paper
Paper/Presentation Title | Optimized FBG sensor network for efficient detection of a delamination in FRP structures |
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Presentation Type | Paper |
Authors | Kahandawa, G. C. (Author), Epaarachchi, J. A. (Author), Wang, H. (Author) and Lau, K. T. (Author) |
Editors | Jaafar, M., Azura, A. R., Leong, K. H. and Leong, A. Y. L. |
Journal or Proceedings Title | Proceedings of the 8th Asian-Australasian Conference on Composite Materials (ACCM 2012) |
ERA Conference ID | 60079 |
Journal Citation | 2, pp. 1443-1448 |
Number of Pages | 6 |
Year | 2012 |
Place of Publication | Kowloon, Hong Kong |
ISBN | 9781629930664 |
Conference/Event | 8th Asian-Australasian Conference on Composite Materials (ACCM 2012): Composites: Enabling Tomorrow's Industry Today |
Asian-Australian Conference on Composite Materials | |
Event Details | 8th Asian-Australasian Conference on Composite Materials (ACCM 2012): Composites: Enabling Tomorrow's Industry Today Event Date 06 to end of 08 Nov 2012 Event Location Kuala Lumpur, Malaysia |
Event Details | Asian-Australian Conference on Composite Materials |
Abstract | Delamination is a potential cause of failure of composite components. Due to the hidden nature of propagation, the detection of delaminations in composites is a time consuming and extremely difficult task. A few decades of research have shown the effectiveness of the embedded fibre Bragg grating (FBG) sensors to detect such damage in fibre reinforced polymeric (FRP) structures. However, a number of sensors are required to detect delaminations within a particular region of a composite structure due the limited receptive range of an FBG sensor. The complexity and the cost of manufacturing increases with the number of sensors attached and therefore, estimation of the optimum number of sensors for efficient identification of damage is an equally important factor to investigate. |
Keywords | FBG sensors; composite materials; finite element analysis; structural health monitoring; artificial neural networks |
ANZSRC Field of Research 2020 | 400102. Aerospace structures |
510204. Photonics, optoelectronics and optical communications | |
401602. Composite and hybrid materials | |
469999. Other information and computing sciences not elsewhere classified | |
Public Notes | Copyright© (2012) by Asian-Australasian Association for Composite Materials (AACM). Permanent restricted access to published version in accordance with the copyright policy of the publisher. |
Byline Affiliations | Centre of Excellence in Engineered Fibre Composites |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q1v67/optimized-fbg-sensor-network-for-efficient-detection-of-a-delamination-in-frp-structures
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