To address the challenge of identifying damage in the hangers and bridge deck systems of long-span suspension bridges, this paper proposes a non-contact monitoring method based on video image recognition. This method extracts structural vibration displacement responses through video acquisition and image analysis, and combined with the strain mode change rate index, it achieves damage localization, type identification, and severity assessment. The principle of extracting displacement time-history data from video images is first elaborated, and MATLAB-based computational code is developed, including pixel tracking and time-history curve generation methods. The eigensystem realization algorithm is used to identify displacement mode shapes, which are then converted into strain mode shapes via the central difference method. The strain mode change rate and its deviation rate are proposed as damage indicators: under undamaged conditions, the curve is smooth; at damage locations, peaks appear; the distribution range of peaks can distinguish between hanger damage and bridge deck cracks; the deviation rate quantifies damage severity. The feasibility of the method is validated through finite element simulations and physical model experiments. The results show that hanger damage causes broad peaks, while bridge deck cracks present narrow peaks; the deviation rate increases monotonically with damage severity. Applied to an in-service suspension bridge, the method successfully identified hanger bending and weld cracking, with assessment results consistent with on-site inspections. This study demonstrates that the strain mode change rate analysis based on video images enables damage identification without prior knowledge of the structural health state, relying solely on the damaged state response. Offering advantages such as non-contact measurement, full-field monitoring, and no need for sensor deployment, it provides a new technical approach for the long-term monitoring of suspension bridge hanger systems.
Liu et al. (Fri,) studied this question.