Assessment of delamination in composite beams using shear horizontal (SH) wave mode

Su, Zhongqing, Yang, Chunhui, Pan, Nan, Ye, Lin and Zhou, Li-Min 2007, Assessment of delamination in composite beams using shear horizontal (SH) wave mode, Composites science and technology, vol. 67, no. 2, pp. 244-251.

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Title Assessment of delamination in composite beams using shear horizontal (SH) wave mode
Author(s) Su, Zhongqing
Yang, Chunhui
Pan, Nan
Ye, Lin
Zhou, Li-Min
Journal name Composites science and technology
Volume number 67
Issue number 2
Start page 244
End page 251
Publisher Elsevier Ltd
Place of publication Amsterdam, The Netherlands
Publication date 2007-02
ISSN 0266-3538
1879-1050
Keyword(s) lamb wave
delamination
damage identification
composite laminate
artificial neural network
Summary Interaction of Lamb waves with structural damage can lead to wave mode conversion. In this study, the shear horizontal (SH) wave, from the mode conversion of the fundamental symmetric Lamb wave (S0), was used for quantitative identification of delamination in composite beams, based on advanced signal processing using an inverse approach. SH wave propagation under various delamination conditions in CF/EP beams made of orthotropic plain woven fabrics was simulated, and signal characteristics were extracted in terms of the concept of digital damage fingerprints (DDF). With the aid of an artificial neural algorithm, the relation between the DDF of delamination-scattered SH mode and damage parameters was calibrated, whereby the occurrence, location and size of delamination in the composite beams were assessed. The approach was experimentally validated, and the results demonstrate the effectiveness of SH mode for quantitative damage evaluation of composite structures.
Language eng
Field of Research 091202 Composite and Hybrid Materials
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Elsevier Ltd
Persistent URL http://hdl.handle.net/10536/DRO/DU:30007342

Document type: Journal Article
Collection: School of Engineering and Information Technology
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