环境风激励下超高层建筑模态参数识别

In this paper, a new modal parameter identification approach for super tall buildings is developed based on empirical wavelet transform (EWT) and improved random decrement technique (IRDT). In the proposed method, the measured vibration signal is firstly decomposed by EWT to obtain several single mode signals. Secondly, the free vibration response of each mono component is obtained by using IRDT. Finally, Hilbert transform and curve fitting are used to estimate the natural frequency and damping ratio. A numerical simulation of a five-story frame structure is employed to validate the effectiveness of the proposed method. Furthermore, the measured acceleration responses of Ping’an Financial Center during Typhoon Nida are analyzed based on the newly developed approach. The damping ratios and vibration frequencies of Ping’an Financial Center are identified. Meanwhile, the instantaneous characteristics (including the instantaneous amplitude and the instantaneous frequency) of the building are investigated in details. Each natural frequency of this building is above 0.1Hz, and corresponding damping ratios of the translational mode are all below 1%. The findings of this study are valuable for health monitoring and vibration control of super tall structures.