Characteristic parameter analysis for identification of vortex-induced vibrations of a long-span bridge

Abstract

As a wind-sensitive structure, long-span bridges are prone to the vibration excited by periodic shedding vortex called vortex-induced vibration (VIV). Timely warning and accurate identification of VIV are required for VIV detection and mitigation. To meet the above-mentioned requirements, the structural health monitoring system provides a wealth of field monitoring data, which serves as the basis for comprehensive analysis of bridge environmental conditions and structural states. In this paper, the wind field features and structural dynamic responses of a long-span suspension bridge were analyzed using field monitoring data from 2013, 2014, and 2017. First, the characteristic parameters with significant specificity, including the probability of wind speed, the probability of wind direction, root mean square (RMS), spectral peak difference rate, and energy proportion, were utilized as VIV early warning and identification indexes, the corresponding threshold of above index values was calculated based on the Pauta criterion. Meanwhile, different time intervals were selected to discuss early warning (identification)accuracy of the parameter thresholds. Then, the VIV early warning and identification strategy was established. Finally, the thresholds of each characteristic parameter were updated based on the VIV database and the accuracy of the strategy was verified. The results show that the probability of wind speed and direction in VIV ranges can provide early warning of the potential VIV. Based on the dynamic response characteristics, including the RMS of acceleration, power spectrum, and energy proportion, the proposed strategy can distinguish VIV from ambient vibration. The early warning and identification of VIV based on field monitoring data are successfully achieved by the proposed strategy, which can be applied to practical engineering.