Please use this identifier to cite or link to this item: https://doi.org/10.1002/eqe.769
Title: Output-only structural identification in time domain: Numerical and experimental studies
Authors: Perry, M.J.
Koh, C.G. 
Keywords: Damage detection
Experiment
Genetic algorithm
Output-only identification
Structural dynamics
System identification
Issue Date: 10-Apr-2008
Citation: Perry, M.J., Koh, C.G. (2008-04-10). Output-only structural identification in time domain: Numerical and experimental studies. Earthquake Engineering and Structural Dynamics 37 (4) : 517-533. ScholarBank@NUS Repository. https://doi.org/10.1002/eqe.769
Abstract: By identifying changes in stiffness parameters, structural damage can be detected and monitored. Although considerable progress has been made in this research area, many challenges remain in achieving robust structural identification based on incomplete and noisy measurement signals. The identification task is made even more difficult if measurement of input force is to be eliminated. To this end, an output-only structural identification strategy is proposed to identify unknown stiffness and damping parameters. A non-classical approach based on genetic algorithms (GAs) is adopted. The proposed strategy makes use of the recently developed GA-based method of search space reduction, which has shown to be able to accurately and reliably identify structural parameters from measured input and output signals. By modifying the numerical integration scheme, input can be computed as the parameter identification task is in progress, thereby eliminating the need to measure forces. Numerical and experimental results demonstrate the power of the strategy in accurate and efficient identification of structural parameters and damage using only incomplete acceleration measurement. Copyright © 2007 John Wiley & Sons, Ltd.
Source Title: Earthquake Engineering and Structural Dynamics
URI: http://scholarbank.nus.edu.sg/handle/10635/65957
ISSN: 00988847
DOI: 10.1002/eqe.769
Appears in Collections:Staff Publications

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