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The free decays obtained from RD have been used for system modal identification using eigen-system realization algorithm (ERA).
In this work, a Bayesian statistical approach is developed for modal identification using the free vibration response of structures.
The modal identification using forward autoregressive approach has some problems in discriminating the structure modes from spurious modes.
However, there are relatively few researches on the application of Bayesian spectral method in the modal identification using SHM data sets.
Through the derivation of the equations for known input modal identification using the proposed mode shape scaling and parameterization scheme, the study provides insight into the relationship between the identified modal parameters and information required in the forced vibration test.
This paper presents an investigation into the feasibility and reliability of modal identification using operational modal analysis (OMA) techniques under such weak excitation circumstances and with responses measured by inexpensive stand-alone accelerometers/data recorders.
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As a consequence, the modal identification used to extract damage sensitive features has to face constricting requirements in terms of signals stationarity and performance accuracy.
A numerical example is carried out based a spinning finite element (SFE) model, and verified using ANSYS® Ver. 12. Finally, comments and observations are provided on how this subspace realization technique can be extended to the problem of modal-parameter identification using only ambient vibration data.
This paper deals with updating of the finite element model using the FRF data with damping identification using complex modal data and its subsequent use for predicting the effects of structure modifications.
A damage detection and assessment algorithm is developed based on system identification using a finite element model and the measured modal response of a structure.
Identification using pigmentation alone is not sufficient.
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