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First, a modal filtering by is performed and then for each analyzed mode, its phase is calculated through a Fourier transform.
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It is based on a residual generated from a modal filtering approach by the calculation of the error between the measurements at the current state and their projections onto the incomplete modal basis of the structure as identified at reference state.
For the mono-dimensional approach, modes cannot be filtered by conventional modal filtering techniques.
First, a modal filtering is performed on real and simulated data by approach, and then for each analyzed mode, its mode excitation factor modulus is calculated as a mean over frequency.
The modal filtering is then done in the adapted frequency domain (Pekeris frequency) by a simple bandpass filtering defined by the user.
The modal co-ordinates are extracted from the system output by interpolation of the sensors measurements and use of the expansion theorem, a process known as modal filtering.
The spatial characteristics, modal filtering and modal sensitivities of distributed segmented sensor patches laminated on a cylindrical shell are investigated.
Application of the modal filtering technique to active control can be effectively used to suppress vibration of floor panels by increasing the damping of the natural vibration modes involved.
The idea is to find a representation well adapted for modal signal structure to achieve modal filtering.
As modes have nonstationary properties, the only way to filter modes is to integrate modal time-frequency characteristics [12] into modal filtering.
We discuss modal filtering tools, then the localization itself is performed.
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