Identification of forced time-varying systems via intrinsic chirp component decomposition

Modal parameter identification is significant in the field of vibration and control for tracking structural vibrations and evaluating structural performances. A novel parameter identification method based on the intrinsic chirp component decomposition (ICCD) and the Hilbert transform is proposed for forced time-varying systems. The developed ICCD decomposes the measured response signal into a limited number of intrinsic chirp components, and instantaneous modal parameters of the system are identified by the Hilbert transform of each intrinsic chirp component. The effectiveness and the accuracy of the proposed approach are investigated in two case studies, that is, a discrete mass-spring-damper oscillator and a cantilever beam. Smooth and periodical parameter variations are discussed in each case. Comparison with the empirical mode decomposition based method validates that the proposed method has better identification ability on estimating the instantaneous natural frequency of the system with the presence of noise. Results demonstrate that the ICCD-based approach could be a reasonable alternative for identification of forced time-varying systems in a noise environment.