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Shock and Vibration
Volume 2015 (2015), Article ID 627852, 13 pages
Research Article

Modal Parameters Estimation of Building Structures from Vibration Test Data Using Observability Measurement

1School of Architecture, Chonnam National University, Gwangju 500-757, Republic of Korea
2School of Architecture & Civil Engineering, Kyungpook National University, Daegu 702-701, Republic of Korea
3School of Architecture, Ajou University, Gyeonggi-do 443-749, Republic of Korea

Received 13 October 2014; Revised 21 January 2015; Accepted 26 January 2015

Academic Editor: Roger Serra

Copyright © 2015 Jae-Seung Hwang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The load distribution to each mode of a structure under seismic loading depends on the modal participation factors and mode shapes and thus the exact estimation of modal participation factors and mode shapes is essential to analyze the seismic response of a structure. In this study, an identification procedure for modal participation factors and mode shapes from a vibration test is proposed. The modal participation factors and mode shapes are obtained from the relationship between observability matrices realized from the system identification. Using the observability matrices, it is possible to transform an arbitrarily identified state space model obtained from the experimental data into a state space model which is defined in a domain with physical meaning. Then, the modal participation factor can be estimated based on the transformation matrix between two state space models. The numerical simulation is performed to evaluate the proposed procedure, and the results show that the modal participation factor and mode shapes are estimated from the structural responses accurately. The procedure is also applied to the experimental data obtained from the shaking table test of a three-story shear building model.