Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM))
Online ISSN : 2185-4661
ISSN-L : 2185-4661
Journal of Applied Mechanics Vol.22 (Special Feature)
UNCERTAINTY QUANTIFICATION OF ESTIMATED MODES OF BRIDGES USING BAYESIAN INFERENCE
Yoshinao GOIChul-Woo KIM
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2019 Volume 75 Issue 2 Pages I_647-I_657

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Abstract

This study aims to propose an efficient modal identification method for bridges under operation. The noisy condition caused by the traffic loadings is one of the difficulties involved in the operational modal identification. To cope with the problem, this study quantifies uncertainty involved in the modal properties utilizing Bayesian statistics. The quantified uncertainty enables to determine the reasonable model order and to extract the stably estimated modal properties from the determined model. The proposed method is applied to traffic induced vibration measured from an actual truss bridge. The extracted modal frequencies well correspond to peaks in power spectral density curves. Twelve bending and tortional modes are efficiently extracted by the proposed method. Six modes in the twelve is possibly newly observed modes.

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© 2019 by Japan Society of Civil Engineers
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