Paper
8 April 2010 Identification and health monitoring of an instrumented building using earthquake response data
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Abstract
This paper describes the identification of finite dimensional, linear, time-invariant models of a 4-story building in the state space representation using multiple data sets of earthquake response. The building, instrumented with 31 accelerometers, is located on the University of California, Irvine campus. Multiple data sets, recorded during the 2005 Yucaipa, 2005 San Clemente, 2008 Chino Hills, and 2009 Inglewood earthquakes, are used for identification and validation. Considering the response of the building as the output and the ground motion as the input, the state space models that represent the underlying dynamics of the building in the discrete-time domain corresponding to each data set are identified. The four state space models identified demonstrate that the response of the building is amplitude dependent with the response frequency, and damping, being dependent on the magnitude of ground excitation. The practical application of this finding is that the consistency of this building response to future earthquakes can be quickly assessed, within the range of ground excitations considered (0.005g - 0.074g), for consistency with prior response - this assessment of consistent response is discussed and demonstrated with reference to the four earthquake events considered in this study. Inclusion of data sets relating to future earthquakes will enable the findings to be extended to a wider range of ground excitation magnitudes.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hasan S. Ulusoy, Maria Q. Feng, and Paul J. Fanning "Identification and health monitoring of an instrumented building using earthquake response data", Proc. SPIE 7649, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2010, 76491L (8 April 2010); https://doi.org/10.1117/12.847693
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KEYWORDS
Data modeling

Earthquakes

Sensors

Motion models

Civil engineering

System identification

Mathematical modeling

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