Abstract
A novel identification approach for linear and nonlinear time-variant systems subject to non-stationary excitations based on the localization properties of the harmonic wavelet transform is developed. Specifically, a single-input/single-output (SISO) structural system model is transformed into an equivalent multiple-input/single-output (MISO) system in the wavelet domain. Next, time and frequency dependent generalized harmonic wavelet based frequency response functions (GHW-FRFs) are appropriately defined. Finally, measured (non-stationary) input–output (excitation–response) data are utilized to identify the unknown GHW-FRFs and related system parameters. 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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
