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FRF-based probabilistic modal parameter identification of structures with known seismic input by Çağlayan Hızal is a Engineering article available to read on EtoBox.

What is FRF-based probabilistic modal parameter identification of structures with known seismic input about?

In this study, an FRF based Bayesian approach is presented for modal identification of civil structures with known seismic input. The proposed method utilizes the statistical properties of frequency response function (FRF) of the observed structure which is obtained from the acceleration response (output) and the seismic input recorded at the base level. In this context, first, the joint pdf of prediction error term and seismic input is derived. Then, applying a linear vector transformation, the output term in the derived joint pdf is defined as depending on the FRF and the seismic input. Finally, the marginal probability of FRF is obtained as a complex ratio distribution from the transformed joint pdf. The posterior probability function for modal parameters is obtained by using Bayes’ theorem. The modal parameters are obtained by maximum likelihood estimation of the constructed probability density function. Finally, the posterior uncertainties for modal parameters are calculated. Two numerical and two real data examples are presented to illustrate the computational efficiency of the proposed methodology against input–output and output only techniques.

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Author

Çağlayan Hızal

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Engineering (Physical Sciences)