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In this paper, the response function method (RFM) is extended to deal with the complexity of FRF and modal data using complex updating parameters.
Results show that the mean value and standard deviation of the uncertain effective parameters of braided composite can be identified from modal data using the proposed stochastic identification method.
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For instance, [19] presents a sparse estimation example of 1-D NMR (modal) data by using Lasso [20], LARS [21] and OMP [22].
Modal properties were extracted from collected data using the system identification technique, and variations of modal properties associated with the change in temperature and vibration amplitude (wind speed) were examined.
The simulated reduced modal data is expanded using the eigenvector projection method.
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.
This paper deals with the updating of a finite element model of a structure using measured modal data and its subsequent use for predicting the effects of structural modifications.
This paper introduces an original, non-destructive diagnosis tool using modal data only.
Different algorithms have recently been developed for the diagnosis of many types of civil and mechanical structures using modal data, such as natural frequencies and mode shapes.
It was observed that by using modal data as input, damage can be identified exactly if the reduction in thickness is more than 10%.
From the developed formulations, the perturbed force vector can be obtained from measured modal data and is then used for predicting the unmeasured components of the expanded experimental mode shapes.
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