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Neural Network Approach to Detection of Changes in Structural Parameters

Masri, S. F. and Nakamura, M. and Chassiakos, A. G. and Caughey, T. K. (1996) Neural Network Approach to Detection of Changes in Structural Parameters. Journal of Engineering Mechanics, 122 (4). pp. 350-360. ISSN 0733-9399. http://resolver.caltech.edu/CaltechAUTHORS:20120202-131238608

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Abstract

A neural network-based approach is presented for the detection of changes in the characteristics of structure-unknown systems. The approach relies on the use of vibration measurements from a “healthy” system to train a neural network for identification purposes. Subsequently, the trained network is fed comparable vibration measurements from the same structure under different episodes of response in order to monitor the health of the structure. It is shown, through simulation studies with linear as well as nonlinear models typically encountered in the applied mechanics field, that the proposed damage detection methodology is capable of detecting relatively small changes in the structural parameters, even when the vibration measurements are noise-polluted.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1061/(ASCE)0733-9399(1996)122:4(350)DOIArticle
http://ascelibrary.org/emo/resource/1/jenmdt/v122/i4/p350_s1PublisherArticle
Additional Information:© 1996 American Society of Civil Engineers. The present study was supported in part by grants from the U.S. National Science Foundation and the Carpenters/Contractors Cooperation Committee, Inc.
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Carpenters/Contractors Cooperation CommitteeUNSPECIFIED
Record Number:CaltechAUTHORS:20120202-131238608
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20120202-131238608
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:29095
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Feb 2012 21:37
Last Modified:24 Feb 2014 19:08

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