Study on Stay Cable Anomaly Identification Method Based on Multi-Point Displacement of the Main Girder for River-Crossing Bridge

To enhance the accuracy and real-time performance of anomaly detection for stay cables in cable-stayed bridges, especially those in water-rich environments, this paper proposes a stay cable anomaly identification method based on multi-point displacement measurements of the main girder. First, combined with finite element modeling, two anomaly identification indicators—“fitted displacement” and “effective displacement” of the main girder—are constructed, and their correlations with the location and severity of cable damage are clarified. Second, a gray level–displacement mapping model based on the Eulerian perspective is established, enabling non-contact, high-precision displacement measurement suitable for remote and distributed monitoring conditions. Subsequently, using a scaled cable-stayed bridge model in the laboratory, the feasibility and effectiveness of the method are verified through multi-condition experiments. Finally, the whale optimization algorithm (WOA)-optimized random forest model, enhancing the accuracy and stability of cable anomaly classification and identification. The results demonstrate that the proposed method offers significant advantages in accuracy, real-time performance, and intelligent recognition. It shows great potential for application in the health monitoring and safety management of water-related cable-stayed bridges, providing a new approach and technical support for intelligent safety diagnosis and reinforcement.