Please use this identifier to cite or link to this item: https://doi.org/10.1061/(ASCE)0733-9445(2006)132:12(2018)
Title: Condensed model identification and recovery for structural damage assessment
Authors: Koh, C.G. 
Tee, K.F.
Quek, S.T. 
Keywords: Damage
Experimentation
Numerical analysis
Structural dynamics
Issue Date: 2006
Source: Koh, C.G., Tee, K.F., Quek, S.T. (2006). Condensed model identification and recovery for structural damage assessment. Journal of Structural Engineering 132 (12) : 2018-2026. ScholarBank@NUS Repository. https://doi.org/10.1061/(ASCE)0733-9445(2006)132:12(2018)
Abstract: This study aims to develop a system identification methodology for determining structural parameters of linear dynamic system, taking into consideration of practical constraints such as insufficient sensors. A new methodology called the condensed model identification and recovery method is presented for identification of full stiffness matrices for damage assessment based on incomplete measurement. With the proposed methodology, it is possible to obtain several condensed stiffness matrices, so as to identify individual stiffness coefficients for the structure. Three different model condensation methods, namely static condensation, dynamic condensation, and system equivalent reduction expansion process, are adopted. Having identified the condensed model, the stiffness parameters in the entire system are recovered by extracting sufficient information with either fixed sensor or repositioned sensor approach. The efficiency of the proposed technique is shown by numerical simulation study for multistory shear buildings subjected to random forces, accounting for effects of signal noise. In addition, laboratory experiments are carried out to illustrate the performance of the proposed method. It is shown both numerically and experimentally that the proposed methodology gives reasonably accurate identification in terms of locating and quantifying structural damage. © 2006 ASCE.
Source Title: Journal of Structural Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/65338
ISSN: 07339445
DOI: 10.1061/(ASCE)0733-9445(2006)132:12(2018)
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

12
checked on Dec 6, 2017

WEB OF SCIENCETM
Citations

9
checked on Nov 18, 2017

Page view(s)

20
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.