Continuous automatic batch identification and characteristic analysis of vortex-induced vibrations of stay cables based on long-term monitoring

Abstract

Vortex-induced vibration (VIV) is a typical abnormal vibration of stay cables, and long-term monitoring of VIV with in-depth information extraction is critical for bridge safety and maintenance. This study establishes an automatic batch framework for continuous VIV identification based on long-term monitoring data. The framework is applied to one-year monitoring data of 24 stay cables in a cable-stayed bridge to identify the VIVs, from which the information behind the long-term identification results is examined and lessons from the analysis are summarised. Results show that long cables exhibit more frequent, larger-amplitude VIV dominated by high-order modes, while short cables mainly experience low-order VIV, which suggests that higher modes should be considered in VIV mitigation for long cables. VIVs of stay cables are highly dependent on wind conditions and show significant variability in vibration amplitude. Significant differences in VIV occurrences and amplitudes between stay cables in symmetric positions were observed, which indicates potential degradation in damping systems for those with severe VIV. The findings are based on large-scale and long-term monitoring, and can provide valuable insights for the maintenance strategies of stay cables.