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contributor authorS. F. Masri
contributor authorM. Nakamura
contributor authorA. G. Chassiakos
contributor authorT. K. Caughey
date accessioned2017-05-08T22:37:53Z
date available2017-05-08T22:37:53Z
date copyrightApril 1996
date issued1996
identifier other%28asce%290733-9399%281996%29122%3A4%28350%29.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/84393
description abstractA 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.
publisherAmerican Society of Civil Engineers
titleNeural Network Approach to Detection of Changes in Structural Parameters
typeJournal Paper
journal volume122
journal issue4
journal titleJournal of Engineering Mechanics
identifier doi10.1061/(ASCE)0733-9399(1996)122:4(350)
treeJournal of Engineering Mechanics:;1996:;Volume ( 122 ):;issue: 004
contenttypeFulltext


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