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Neural networks for delamination flaw detection in FRP laminated composite plates

DSpace at IIT Bombay

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Title Neural networks for delamination flaw detection in FRP laminated composite plates
 
Creator BAGE, AA
BANERJI, P
 
Subject quantitative nondestructive evaluation
multilayer perceptron
vibrations
guided waves
artificial neural networks (ann)
counter-propagation networks
cascaded networks
damage detection
laminated composite plates
delamination flaws
 
Description In this study, the detection of delamination flaws in laminated composite plates is carried out using artificial neural networks (ANN) in a two-level cascading manner. The three damage parameters detected using ANN are the size of the delamination, its vertical location (across the plate thickness) and horizontal location (along the plate surface). The numerical data in the form of frequency domain Green's function for the displacement response on the surface of the plate containing the delamination flaw is generated first using an available numerical method. Pseudo-experimental data is generated adding artificial random noise into the numerical data. At the first level, a counterpropagation neural network (CPN) is trained for qualitatively classifying the damage parameters using the numerical data generated above. Next, a second level back-propagation network (BPN) is used for each subclass to quantify the damage parameters. An overlapping data set is used for the training of each class of the second level network. As a result, any pattern misclassified by the CPN due to its closeness to the boundary of any two classes is still quantified correctly. By feeding pseudo-experimental data to the trained networks, it is seen that the classification success rate and noise tolerance level of CPN is excellent. The quantification of damage by the second level BPN is also good. It is possible to stop after the first level if only a qualitative assessment of the damage and its approximate location is required. These cascaded networks show promise in providing a successful delamination damage detection tool.
 
Publisher SPIE-INT SOC OPTICAL ENGINEERING
 
Date 2011-10-24T01:53:15Z
2011-12-15T09:11:22Z
2011-10-24T01:53:15Z
2011-12-15T09:11:22Z
2005
 
Type Proceedings Paper
 
Identifier Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems IV,5768,369-377
0-8194-5749-3
0277-786X
http://dx.doi.org/10.1117/12.599810
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15299
http://hdl.handle.net/100/2022
 
Source Conference on Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems IV,San Diego, CA,MAR 07-09, 2005
 
Language English