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This paper proposes a modal identification system based on vector backward auto-regressive with exogeneous (VBARX) model.
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.
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The free decays obtained from RD have been used for system modal identification using eigen-system realization algorithm (ERA).
The modal identification of dynamical systems under operational conditions, when subjected to wide-band unmeasured excitations, is today a viable alternative to more traditional modal identification approaches based on processing sets of measured FRFs or impulse responses.
The capability of spectral methods to deal with the modal identification of non-stationary systems is enhanced by a curve-fitting procedure based on nonlinear least squares optimization.
Three independent but complementary output-only modal identification techniques are used for system identification.
In this way, the natural frequency of each region can be identified using any modal identification approach applicable to linear systems.
A new time-domain modal identification method of the linear time-invariant system driven by the non-stationary Gaussian random force is presented in this paper.
This work proposes a Moving Kriging (MK) shape function modeling method for modal identification of linear time-varying (LTV) structural systems based on vector time-dependent autoregressive moving average (VTARMA) models.
Based on the incomplete modal identification results, the most probable structural model parameters, the most probable system eigenvalues and partial modes shapes together with the associated uncertainties can be identified simultaneously.
The order of the system is an essential piece of information for modal identification and analysis, but it is often not available, and a good engineering estimate is needed.
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