Time-varying modal identification of structures under seismic excitations using a novel time-frequency method

Civil engineering structures are susceptible to damage when subjected to seismic excitations, resulting in presenting nonlinear features and exhibiting time-varying dynamic behavior of structural modal properties. The instantaneous frequency (IF) of structures is thus an essential indicator to evaluate structural damage state. Time-varying filtering empirical mode decomposition (TVF-EMD) holds promise for non-stationary signals decomposition and IF identification due to its robustness against noise interference. However, the application of TVF-EMD is limited by the requirement for manually presetting the decomposition parameters (i.e., B-spline order and bandwidth threshold). In this study, a novel IF identification method based on an improved TVF-EMD algorithm is proposed. In this method, TVF-EMD is firstly improved to accurately decompose the measured responses into mono-component modal responses, which adopts orthogonal coefficient and energy kurtosis as the objective function of salp swarm algorithm (SSA) to adaptively determine the optimal decomposition parameters. Then, the resulting mono-component modal responses are analyzed by local maximum synchrosequencing transform (LMSST) to obtain structural IF under seismic excitations. Examples of non-stationary signals of sinusoidal function, Duffing system, and simulated two-story shear building model under El Centro seismic excitations are used to illustrate the advantages of the proposed method, which proves to be successful in signal decomposition and IF identification. Furthermore, the proposed method is applied to a shaking table test and a real building-Van Nuys hotel under seismic excitations to identify their IF and evaluate structural damage states. The results reveal that the proposed method is efficient for structural IF identification, and can be utilized to qualitatively evaluate the damage severity of structures subjected to strong seismic excitations.