Ambient modal identification using non-stationary correlation technique

in Sciences Citation Index(SCI), 科學引文索引資料庫(SCI)
標題Ambient modal identification using non-stationary correlation technique
出版類型SCI(Sciences Citation Index)
AuthorsLin, 林章生
出版日期2016 / 8

The topic of this paper is the modal identification from non-stationary ambient response data by
applying correlation technique. It is shown theoretically that by assuming the ambient excitation to be nonstationary
white noise in the form of a productmodel, the non-stationary response signals can be converted into
free vibration data via the correlation technique. Previous studies have showed that the practical problem of
insufficient data samples available for evaluating non-stationary correlation can be approximately resolved by
first extracting the amplitude-modulating function from the response and then transforming the non-stationary
responses into stationary ones. However, the errors involved in the approximate free-decay response would
generally lead to a distortion in the modal identification. In the present paper, we propose that, if the ambient
excitation can be represented by a product model with slowly time-varying function, without any additional
treatment of transforming the original nonstationary responses, the non-stationary responses of the system can
be treated approximately as a stationary random process; then, the nonstationary cross correlation functions
of structural response evaluated at an arbitrary, fixed time instants of structural response are of the same
mathematical form as that of free vibration of a structure, from which modal parameters of the original
system can thus be identified. Numerical simulations, including one example of using the practical earthquake
data served as the excitation input acting on a linear two-dimensional model of one-half of a railway vehicle,
confirm the validity of the proposed method for identification ofmodal parameters from non-stationary ambient
response data only.

期刊名稱Archive of Applied Mechanics
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