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Structural health monitoring via measured ritz vectors utilizing artificial neural networks
Lam H.-F.1; Yuen K.-V.2; Beck J.L.3
2006
Source PublicationComputer-Aided Civil and Infrastructure Engineering
ISSN10939687
Volume21Issue:4Pages:232
Abstract

A pattern recognition approach for structural health monitoring (SHM) is presented that uses damage inducedchanges in Ritz vectors as the features to characterize the damage patterns defined by the corresponding locations and severity of damage. Unlike most other pattern recognition methods, an artificial neural network (ANN) technique is employed as a tool for systematically identifying the damage pattern corresponding to an observed feature. An important aspect of using an ANN is its design but this is usually skipped in the literature on ANN-based SHM. The design of an ANN has significant effects on both the training and performance of the ANN. As the multi-layer perceptron ANN model is adopted in this work, ANN design refers to the selection of the number of hidden layers and the number of neurons in each hidden layer. A design method based on a Bayesian probabilistic approach for model selection is proposed. The combination of the pattern recognition method and the Bayesian ANN design method forms a practical SHM methodology. A truss model is employed to demonstrate the proposed methodology. © 2006 Computer-Aided Civil and Infrastructure Engineering.

DOI10.1111/j.1467-8667.2006.00431.x
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Construction & Building Technology ; Engineering ; Transportation
WOS SubjectComputer Science, Interdisciplinary Applications ; Construction & Building Technology ; Engineering, Civil ; Transportation Science & Technology
WOS IDWOS:000235842400002
The Source to ArticleScopus
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Cited Times [WOS]:69   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Affiliation1.City Univ Hong Kong, Dept Bldg & Construct, Hong Kong, Hong Kong, Peoples R China
2.Univ Macau, Fac Sci & Technol, Macao, Peoples R China
3.CALTECH, Div Engn & Appl Sci, Pasadena, CA 91125 USA
Recommended Citation
GB/T 7714
Lam H.-F.,Yuen K.-V.,Beck J.L.. Structural health monitoring via measured ritz vectors utilizing artificial neural networks[J]. Computer-Aided Civil and Infrastructure Engineering,2006,21(4):232.
APA Lam H.-F.,Yuen K.-V.,&Beck J.L..(2006).Structural health monitoring via measured ritz vectors utilizing artificial neural networks.Computer-Aided Civil and Infrastructure Engineering,21(4),232.
MLA Lam H.-F.,et al."Structural health monitoring via measured ritz vectors utilizing artificial neural networks".Computer-Aided Civil and Infrastructure Engineering 21.4(2006):232.
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