TECHNICAL PAPERS
Apr 1, 1996

Neural Network Approach to Detection of Changes in Structural Parameters

Publication: Journal of Engineering Mechanics
Volume 122, Issue 4

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.

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Published In

Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 122Issue 4April 1996
Pages: 350 - 360

History

Published online: Apr 1, 1996
Published in print: Apr 1996

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Authors

Affiliations

S. F. Masri, Member, ASCE,
Prof., Dept. of Civ. Engrg., Univ. of Southern California, Los Angeles, CA 90089-2531.
M. Nakamura
Res. Engr., Vibration Engrg. Dept., Tech. Res. Inst., Obayashi Corp, Tokyo 204, Japan.
A. G. Chassiakos
Prof., School of Engrg., California State Univ., Long Beach, CA 90840.
T. K. Caughey
Prof., Div. Engrg. and Appl. Sci., California Inst. of Technol., Pasadena, CA 91125.

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