Modal identification from nonstationary ambient vibration data using random decrement algorithm

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Abstract

An effective identification method is developed for the determination of modal parameters of a structure from its measured ambient nonstationary vibration data. It has been shown in a previous paper of the authors that by assuming the ambient excitation to be nonstationary white noise in the form of a product model, the nonstationary response signals can be converted into free-vibration data via the correlation technique. In the present paper, if the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross random decrement signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions. The practical problem of insufficient data samples available for evaluating nonstationary random decrement signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain technique, which is effective at identifying closely spaced modes. Numerical simulations confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data. © The Society for Experimental Mechanics, Inc. 2012.

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APA

Lin, C. S., & Chiang, D. Y. (2012). Modal identification from nonstationary ambient vibration data using random decrement algorithm. In Conference Proceedings of the Society for Experimental Mechanics Series (Vol. 5, pp. 223–232). https://doi.org/10.1007/978-1-4614-2425-3_20

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