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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Kougioumtzoglou, I.A., Spanos, P.D. (2012). Harmonic Wavelets Based Identification of Nonlinear and Time-Variant Systems. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds) Scalable Uncertainty Management. SUM 2012. Lecture Notes in Computer Science(), vol 7520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33362-0_19
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DOI: https://doi.org/10.1007/978-3-642-33362-0_19
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