Vibration-based damage detection of slab structure using artificial neural network

This paper investigates the effectiveness of artificial neural network (ANN) in identifying damages in structures. Global (natural frequencies) and local (mode shapes) vibration-based data has been used as the input to ANN for location and severity prediction of damages in a slab-like structure. A...

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Main Author: Bakhary, Norhisham
Format: Article
Language:English
Published: Penerbit UTM Press 2006
Subjects:
Online Access:http://eprints.utm.my/5845/
http://eprints.utm.my/5845/1/bab2.pdf
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author Bakhary, Norhisham
author_facet Bakhary, Norhisham
author_sort Bakhary, Norhisham
building UTeM Institutional Repository
collection Online Access
description This paper investigates the effectiveness of artificial neural network (ANN) in identifying damages in structures. Global (natural frequencies) and local (mode shapes) vibration-based data has been used as the input to ANN for location and severity prediction of damages in a slab-like structure. A finite element analysis has been used to obtain the dynamic characteristics of intact and damaged structure to train the neural network model. Different damage scenarios have been introduced by reducing the local stiffness of the selected elements at different locations along the structure. Several combinations of input variables in different modes have been used in order to obtain a reliable ANN model. The trained ANN model is validated using laboratory test data. The results show that ANN is capable of providing acceptable result on damage prediction of tested slab structure.
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spelling utm-58452017-09-18T01:18:08Z http://eprints.utm.my/5845/ Vibration-based damage detection of slab structure using artificial neural network Bakhary, Norhisham TA Engineering (General). Civil engineering (General) This paper investigates the effectiveness of artificial neural network (ANN) in identifying damages in structures. Global (natural frequencies) and local (mode shapes) vibration-based data has been used as the input to ANN for location and severity prediction of damages in a slab-like structure. A finite element analysis has been used to obtain the dynamic characteristics of intact and damaged structure to train the neural network model. Different damage scenarios have been introduced by reducing the local stiffness of the selected elements at different locations along the structure. Several combinations of input variables in different modes have been used in order to obtain a reliable ANN model. The trained ANN model is validated using laboratory test data. The results show that ANN is capable of providing acceptable result on damage prediction of tested slab structure. Penerbit UTM Press 2006-06 Article PeerReviewed application/pdf en http://eprints.utm.my/5845/1/bab2.pdf Bakhary, Norhisham (2006) Vibration-based damage detection of slab structure using artificial neural network. Jurnal Teknologi B (44B). pp. 17-30. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v44.359
spellingShingle TA Engineering (General). Civil engineering (General)
Bakhary, Norhisham
Vibration-based damage detection of slab structure using artificial neural network
title Vibration-based damage detection of slab structure using artificial neural network
title_full Vibration-based damage detection of slab structure using artificial neural network
title_fullStr Vibration-based damage detection of slab structure using artificial neural network
title_full_unstemmed Vibration-based damage detection of slab structure using artificial neural network
title_short Vibration-based damage detection of slab structure using artificial neural network
title_sort vibration-based damage detection of slab structure using artificial neural network
topic TA Engineering (General). Civil engineering (General)
url http://eprints.utm.my/5845/
http://eprints.utm.my/5845/
http://eprints.utm.my/5845/1/bab2.pdf