Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23169
Title: Efficiency of genetic algorithms and artificial neural networks for evaluating delamination in composite structures using fibre Bragg grating sensors
Authors: Su, Z
Ling, HY
Zhou, LM 
Lau, KT 
Ye, L
Issue Date: 2005
Publisher: Institute of Physics Publishing
Source: Smart materials and structures, 2005, v. 14, no. 6, p. 1541-1553 How to cite?
Journal: Smart materials and structures 
Abstract: The efficiency of genetic algorithms (GAs) and artificial neural networks (ANNs) in the quantitative assessment of delamination in glass fibre-reinforced epoxy (GF/EP) composite laminates was evaluated comparatively. For GA-based identification, a theoretical model and a vibration-based objective function were established to relate the delamination parameters to the shift in structural eigenvalues. For the ANN-based approach, feedforward artificial neural networks were configured and trained using the structural eigenvalues obtained from different damage groups, under the supervision of an error-backpropagation neural algorithm. By way of validation, dynamic responses of selected GF/EP laminate beams containing various delaminations were captured using embedded fibre Bragg grating sensors, from which the structural eigenvalues were extracted and used inversely to implement the damage assessment via the GA and the ANN. The performances of the two algorithms were addressed as regards the prediction precision and computational cost.
URI: http://hdl.handle.net/10397/23169
ISSN: 0964-1726
EISSN: 1361-665X
DOI: 10.1088/0964-1726/14/6/047
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

17
Last Week
0
Last month
1
Citations as of Oct 10, 2017

WEB OF SCIENCETM
Citations

14
Last Week
0
Last month
0
Citations as of Oct 16, 2017

Page view(s)

64
Last Week
1
Last month
Checked on Oct 15, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.