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An alternative technique for obtaining modal parameters from multiple measured signals is the stochastic subspace identification (SSI) method.
The processing of this data – i.e. extracting modal parameters from the FRFs – can be a time consuming task.
An approach to estimate modal parameters, from only output data in the time domain using the wavelet transform, is presented.
In [14], the eigensystem realization algorithm (ERA) combining with linear filter decomposition and Teager-Kaiser energy (TKE) has been adopted to identify the modal parameters from measured data.
In this paper a new OMA approach to identify modal parameters from output-only transmissibility measurements is introduced.
When identifying the modal parameters from noisy measurement data, the information on their uncertainty is most relevant.
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The modal parameters obtained from different tests were investigated separately and then compared with each other.
There is a good correlation among the modal parameters identified from the three independent identification techniques.
This paper focuses on the calibration of a numerical model of a stone masonry arch railway bridge using dynamic modal parameters estimated from an ambient vibration test.
Existing methods are classified into two main groups: matrix methods which use directly the measured FRF matrix, and modal methods which use modal parameters deduced from the FRFs.
The geometrical parameters of the delaminated zone are identified by comparing the modal parameters calculated from impedance measurements with those obtained using our model.
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