Please use this identifier to cite or link to this item:
|Title:||Condensed model identification and recovery for structural damage assessment||Authors:||Koh, C.G.
|Issue Date:||2006||Citation:||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.
checked on Feb 3, 2023
WEB OF SCIENCETM
checked on Feb 3, 2023
checked on Feb 2, 2023
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.