Abstract
Structural systems subject to non-stationary excitations can often exhibit time-varying nonlinear behavior. In such cases, a reliable identification approach is critical for successful damage detection and for designing an effective structural health monitoring (SHM) framework. In this regard, an identification approach for nonlinear time-variant systems based on the localization properties of the harmonic wavelet transform is developed herein. The developed approach can be viewed as a generalization of the well established reverse MISO spectral identification approach to account for non-stationary inputs and time-varying system parameters. Several linear and nonlinear time-variant systems are used to demonstrate the reliability of the approach. The approach is found to perform satisfactorily even in the case of noise-corrupted data.
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