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Blind modal identification of structures from spatially sparse seismic response signals
Author(s) -
Ghahari S. F.,
Abazarsa F.,
Ghannad M. A.,
Çelebi M.,
Taciroglu E.
Publication year - 2014
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1593
Subject(s) - modal , normal mode , subspace topology , seismic noise , identification (biology) , acoustics , vibration , inversion (geology) , modal analysis , computer science , modal analysis using fem , underdetermined system , algorithm , modal testing , physics , geology , artificial intelligence , seismology , botany , polymer chemistry , biology , chemistry , tectonics
SUMMARY Response‐only identification of civil structures has attracted much attention during recent years, as input excitations are rarely measurable for ambient vibrations. Although various techniques have been developed by which identification can be carried out using ambient responses, these techniques are generally not applicable to non‐stationary excitations that structures experience during moderate‐to‐severe earthquakes. Recently, the authors proposed a new response‐only modal identification method that is applicable to strong shaking data. This new method is highly attractive for cases in which the true input motions are unavailable. For example, when soil–structure interaction effects are non‐negligible, neither the free‐field motions nor the recorded foundation responses may be assumed as input. Even in the absence of soil–structure interaction, in many instances, the foundation responses are not recorded (or are recorded with low signal‐to‐noise ratios). Thus far, the said method has been only applicable to fully instrumented systems wherein the number of sensors is equal to or greater than the number of active modes. In this study, we offer various improvements, including an extension that enables the treatment of sparsely instrumented systems. Specifically, a cluster‐based underdetermined time–frequency method is employed at judiciously selected auto‐source points to determine the mode shapes. The mode shape matrix identified in this manner is not square, which precludes the use of simple matrix inversion to extract the modal coordinates. As such, natural frequencies and damping ratios are identified from the recovered modal coordinates' time–frequency distributions using a subspace method. Simulated data are used for verifying the proposed identification method. Copyright © 2013 John Wiley & Sons, Ltd.