Meshfree formulation for inverse frequencies analysis incorporating artificial neural network

This study concerns on the formulation of meshfree method for the inverse frequency analysis of damage detection incorporating Artificial Neural Network (ANN). Meshfree is used in developing the characteristic dynamic equation of the structure where as ANN is utilized to obtain the damaged stiffness...

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Main Author:	Abd. Nazir, Mohd. Zhafri Jamil
Format:	Thesis
Published:	2013
Subjects:	TH Building construction
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spelling	my-utm-ep.416782020-06-24T01:24:41Z Meshfree formulation for inverse frequencies analysis incorporating artificial neural network 2013 Abd. Nazir, Mohd. Zhafri Jamil TH Building construction This study concerns on the formulation of meshfree method for the inverse frequency analysis of damage detection incorporating Artificial Neural Network (ANN). Meshfree is used in developing the characteristic dynamic equation of the structure where as ANN is utilized to obtain the damaged stiffness matrix through the inverse process. Input data for the process are the frequencies and the mode shapes of the structure. The architecture used in developing the artificial neural network model is multilayer perceptron and the supervised learning process applied in this study is back propagation algorithm. The training data are randomly generated to cover all possible damage areas by using meshfree method. Output from the process is the stiffness reduction ratio. The performance of meshfree is first assessed against finite element method. Classical plate theory based on Kirchoff assumption has been discretized by both methods. The results are in good agreement between both methods, thus validate the meshfree formulation. The parametric study is then conducted to obtain the optimum value for the parameters of meshfree method. These parameters are shape parameters which involved; dimensionless shape parameter, ac and q, dimensionless size of support domain, as , background cell, gauss points and polynomial basis. The optimum values of these parameters are then used in constructing the random input and output data for the training process of artificial neural network model. The performance of the ANN model is verified against previous work based on the generated data. It can be concluded that ANN exhibits excellent performance thus highly potential as an analysis method in the study of inverse frequency analysis for damage detection incorporating Artificial Neural Network 2013 Thesis http://eprints.utm.my/id/eprint/41678/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:78903?queryType=vitalDismax&query=Meshfree+formulation+for+inverse+frequencies&public=true masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TH Building construction
spellingShingle	TH Building construction Abd. Nazir, Mohd. Zhafri Jamil Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
description	This study concerns on the formulation of meshfree method for the inverse frequency analysis of damage detection incorporating Artificial Neural Network (ANN). Meshfree is used in developing the characteristic dynamic equation of the structure where as ANN is utilized to obtain the damaged stiffness matrix through the inverse process. Input data for the process are the frequencies and the mode shapes of the structure. The architecture used in developing the artificial neural network model is multilayer perceptron and the supervised learning process applied in this study is back propagation algorithm. The training data are randomly generated to cover all possible damage areas by using meshfree method. Output from the process is the stiffness reduction ratio. The performance of meshfree is first assessed against finite element method. Classical plate theory based on Kirchoff assumption has been discretized by both methods. The results are in good agreement between both methods, thus validate the meshfree formulation. The parametric study is then conducted to obtain the optimum value for the parameters of meshfree method. These parameters are shape parameters which involved; dimensionless shape parameter, ac and q, dimensionless size of support domain, as , background cell, gauss points and polynomial basis. The optimum values of these parameters are then used in constructing the random input and output data for the training process of artificial neural network model. The performance of the ANN model is verified against previous work based on the generated data. It can be concluded that ANN exhibits excellent performance thus highly potential as an analysis method in the study of inverse frequency analysis for damage detection incorporating Artificial Neural Network
format	Thesis
qualification_level	Master's degree
author	Abd. Nazir, Mohd. Zhafri Jamil
author_facet	Abd. Nazir, Mohd. Zhafri Jamil
author_sort	Abd. Nazir, Mohd. Zhafri Jamil
title	Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
title_short	Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
title_full	Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
title_fullStr	Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
title_full_unstemmed	Meshfree formulation for inverse frequencies analysis incorporating artificial neural network
title_sort	meshfree formulation for inverse frequencies analysis incorporating artificial neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department	Faculty of Civil Engineering
publishDate	2013
_version_	1747816595761135616

Meshfree formulation for inverse frequencies analysis incorporating artificial neural network

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