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Many long-span bridges are located at typhoon prone regions. With the continuous increase of the bridge span, the typhoon-induced buffeting becomes more and more prominent. In this study, based on the structural health monitoring system installed in the Sutong Bridge, the recorded buffeting responses of the main girder during typhoons Damrey and Haikui were analyzed. The run test method demonstrated that the recorded acceleration responses can be regarded as zero-mean non-stationary random processes. Hence, to capture the energy distribution of the recorded data in the time-frequency domain, the evolutionary power spectral density (EPSD) estimation was conducted using efficient generalized harmonic wavelet (GHW) and filtered harmonic wavelet (FHW), respectively. Compared with the GHW, narrower wavelet bandwidth is required by the FHW to yield a compromise between the time and frequency resolution. For the FHW-based method, the power spectral density amplitudes of the averaging EPSDs are slightly larger for certain major frequency components than those obtained by the Pwelch method. Results show that the non-stationary features of the buffeting of long-span bridges during Typhoon events should be considered. This study can also provide references for non-stationary buffeting analysis of other long-span bridges during extreme wind events.

This paper introduces the signal analysis method of harmonic wavelet. First, the human EEG data under +Gz acceleration is obtained, then the method of harmonic wavelet transformation is applied to the dynamic EEG data under +Gz acceleration. Through discrete harmonic wavelet transformation, the corresponding three-dimensional timefrequency graph and time-frequency contour graph are obtained, and EEG change feature under +Gz acceleration is analyzed. The merits and demerits of this analysis method are evaluated. Results show that, EEG shows obvious change feature under +Gz acceleration, that is the energy of slow wave such as delta, theta and so on increases, and the energy of alpha, beta wave and other waves decreases. The analysis method of harmonic wavelet has certain application values.