Field Monitoring and Analysis of the Vibration of Stay Cables under Typhoon Conditions

Abstract

Structural health monitoring systems provide many advantages for full-scale measurements in bridge monitoring. In this study, a strong landing typhoon event recorded at the Jintang Bridge (Zhejiang Province, China) in 2019 was selected to study the nonstationary wind and cable vibration characteristics. To study the characteristics of the recorded typhoon, the time-varying mean wind was extracted based on the adaptive method of the wavelet-matrix transform. The nonstationary characteristics of Typhoon Lekima, including the turbulence intensity, gust factor, and fluctuating wind power spectral density, were analyzed and compared with the stationary model characteristics of a typhoon, and the typical characteristics and parameters were obtained. In addition, the measured vibration response of the cables was analyzed. The vibration characteristics of the cables and the energy distribution of the wind speed wavelet packet were investigated. The vibrations at different positions were compared. A power spectrum analysis and a wavelet packet energy analysis of the cable were performed. The results of this study can be used as a basis for wind-resistant design and performance evaluation of bridges under similar operational conditions.

Semi-Active Cable Damping to Compensate for Damping Losses Due to Reduced Cable Motion Close to Cable Anchor

“…Stay cables are susceptible to vibrations because of their low inherent damping [1,2]. The transverse cable amplitude may become unacceptably large when the excitation frequency due to vertex-shedding matches one of the cable eigenfrequencies whereby the entire excitation energy is transmitted to one modal component [2][3][4][5][6][7][8][9][10]. Such cable vibrations with amplitudes in the range of 0.3 m to 0.6 m have been observed on several stay-cable bridges, e.g., the Dongting Lake Bridge in China [11], the Franjo Tudjman Bridge in Croatia [12] or the Alamillo Bridge in Spain [13].…”

Accurate Correlation Modeling between Wind Speed and Bridge Girder Displacement Based on a Multi-Rate Fusion Method

“…Direct correlation analysis of these monitoring data can realize damage identification performance for early-warning of bridge structures, which helps to monitor the performance of bridges and prevent catastrophic accidents through security warnings [ 4 , 5 ]. Structural health monitoring systems using sensors can monitor the deformation of bridges [ 6 , 7 , 8 ]. Damage identification of bridges can be carried out through big data analytics of a bridge monitoring system [ 9 ].…”