An Improved Random Decrement Algorithm with Time-Varying Threshold Level for Ambient Modal Identification
Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional Random Decrement Algorithm, the threshold level for evaluating randomdec signatures is defined as the standard deviation value of response data of the reference channel. However, the distortion of randomdec signatures may be induced by the error involved in the noise obtained from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of more sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.
KeywordsModal identification Nonstationary ambient vibration Random decrement algorithm Time-varying threshold level Temporal root-mean-square function
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