Narrow Results

Modal identification aims at identifying the dynamic properties including natural frequency, damping ratio, and mode shape, which is an important step in further structural damage detection, finite element model updating, and condition assessment. This paper presents the work on the investigation of the dynamic characteristics of a long-span cable-stayed bridge-Sutong Bridge by a Bayesian modal identification method. Sutong Bridge is the second longest cable-stayed bridge in the world, situated on the Yangtze River in Jiangsu Province, China, with a total length of 2 088m. A short-term nondestructive on-site vibration test was conducted to collect the structural response and determine the actual dynamic characteristics of the bridge before it was opened to traffic. Due to the limited number of sensors, multiple setups were designed to complete the whole measurement. Based on the data collected in the field tests, modal parameters were identified by a fast Bayesian FFT method. The first three modes in both vertical and transverse directions were identified and studied. In order to obtain modal parameter variation with temperature and vibration levels, long-term tests have also been performed in different seasons. The variation of natural frequency and damping ratios with temperature and vibration level were investigated. The future distribution of the modal parameters was also predicted using these data.

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.