Structural monitoring by system identification in time domain

Chan Ghee Koh; C. Y. Liaw; B. Hong

doi:10.1117/12.348684

18 May 1999 Structural monitoring by system identification in time domain

Chan Ghee Koh, C. Y. Liaw, B. Hong

Proceedings Volume 3671, Smart Structures and Materials 1999: Smart Systems for Bridges, Structures, and Highways; (1999) https://doi.org/10.1117/12.348684
Event: 1999 Symposium on Smart Structures and Materials, 1999, Newport Beach, CA, United States

Abstract

A system identification (SI) procedure to identify structural parameters is proposed in this paper. Instead of identifying parameters in the physical domain, which involves search in a large-dimensional parameter space, the search is made easier computationally in sub-domains orders. Modal decomposition technique is employed. The objective function is the minimization of error of modal response history. Physical parameters are then recovered by making use of modal orthogonality properties. The genetic algorithm is employed based on the principle of natural selection whereby better genes survive and propagate and therefore increase the change of converging to the best parameter set. For numerical study, a 10-story shear building is considered to illustrate the efficiency of the proposed procedure.

Citation Download Citation

Chan Ghee Koh, C. Y. Liaw, and B. Hong "Structural monitoring by system identification in time domain", Proc. SPIE 3671, Smart Structures and Materials 1999: Smart Systems for Bridges, Structures, and Highways, (18 May 1999); https://doi.org/10.1117/12.348684

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available