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A recently developed fast Bayesian frequency domain method is used for modal identification based on the measured ambient data.
Modal identification based on vibration response measured from real structures is becoming more popular, especially after benefiting from the great improvement of the measurement technology.
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Vibrational measurement data are often nonstationary and modal parameter identification based on these data is of practical value for structural health monitoring and condition assessment.
The natural modes of vibration, frequencies and damping were determined using (i) a conventional input output modal identification technique, based on the Rational Fraction Polynomial method, and (ii) a simple output-only method directly based on the Fast Fourier Transform (FFT) of the response (mode frequencies only).
This paper proposes a modal identification system based on vector backward auto-regressive with exogeneous (VBARX) model.
Four methods are proposed that allow construction of the unobserved part of the square dynamic flexibility matrix Γ∈Cc,cwithout performing a modal identification and based on the information contained in the known rectangular sub-matrix Γ1∈Cc,p,p
Feasibility of damage identification based on the detection of this local variation of modal reactive power flow in a structure is studied.
A complete procedure for modal identification from free responses based on the continuous wavelet transform is presented.
In this paper, a modal identification system that is based on the vector backward autoregressive (VBAR) model has been developed for the identification of natural frequencies, damping ratios and mode shapes of structures from measured output data.
Both a Reduced Model (RM), based on the Modal Identification Method (MIM), and a Finite Element Model (FEM) using COMSOL software were developed and optimized by comparison with the experimental results.
This paper introduced a modal parameter based identification procedure to identify the equivalent system of structures under harmonic excitations.
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