Advanced analysis of monitored data for high-order, small-amplitude vortex-induced vibration of long-span suspension bridge hangers

Hangers of long-span suspension bridges are highly susceptible to vortex-induced vibration (VIV), which may influence structural safety and service life. Traditional field measurement studies typically adopt a 10-min window to process wind and vibration data. However, this approach may obscure the temporal evolution of VIV events and misrepresent VIV characteristics. Moreover, the identification method for girder VIV has limitations when applied to hanger VIV. To address this issue, this paper proposes an advanced analysis method based on the Gaussian mixture model combined with the expectation–maximization algorithm. The method enables complete reconstruction of VIV events, identification of inlet and outlet, and extraction of representative wind and vibration parameters. Field measurements from a long-span suspension bridge were analyzed to evaluate the method. Results demonstrate that the proposed approach significantly reduces false detections compared with the traditional method and identifies VIV evolution across development, maturity, and decay stages. Statistical analysis of 183 detected events reveals clear occurrence conditions: VIV primarily arises under mean wind velocities of 4.5–7.5 m/s and persists when wind direction remains stable within the ranges of 325°–25° and 145°–205°. Moreover, higher-order multimodal lock-in behavior is observed, with overlapping excitation ranges among multiple modes, indicating complex aerodynamic interactions. These findings provide new insights into the dynamic mechanisms of hanger VIV and demonstrate the importance of advanced data processing for structural health monitoring. The proposed method offers practical value for bridge operation and maintenance by enabling more accurate identification of VIV conditions and supporting the design of vibration control strategies.