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Focus is on applicability of the SOBI technique for extracting the modal responses from analytic signals built from a set of vibratory responses.
Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data.
The analytical mode decomposition is developed with Hilbert transform to decompose the extracted free vibration with closely spaced natural frequencies into a series of modal responses from which modal parameters are evaluated.
By selectively utilizing "effective" information in local regions of the time frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties.
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A more sophisticated and involved approach is to create different coupling vectors for regions of an object by comparing the modal responses taken from those regions.
The results show that the use of CQC rule with the modal responses obtained from the UHS is adequate if the peak responses of MDOF system are dominated by the response of one mode.
Each item was given the full range of scores from 0 to 5, with zero the modal response for 15 of the 17 items.
It is demonstrated that vibration modal responses can be estimated from single channel data and order tracking can be performed without measured tachometer data.
This paper discusses the use of blind source separation (BSS) techniques to extract and identify modal responses and mode shapes from simulated data.
Natural frequencies and damping ratios are extracted from the modal responses recovered by smoothed l0-norm algorithm.
Natural frequencies and damping ratios were extracted from the recovered modal responses.
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