4.5 Article

Long-term condition monitoring of cables for in-service cable-stayed bridges using matched vehicle-induced cable tension ratios

期刊

SMART STRUCTURES AND SYSTEMS
卷 29, 期 1, 页码 167-179

出版社

TECHNO-PRESS
DOI: 10.12989/sss.2022.29.1.167

关键词

cable damage; cable-stayed bridges; cable tension ratio; damage detection; influence surface; sensor fault

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This article presents a long-term condition assessment method for stay cables in cable-stayed bridges using monitored cable tension forces during operation. The method utilizes the concept of influence surface and theoretically proves the relationship between the matched cable tension ratio and the condition of stay cables, regardless of vehicle positions on the bridge. A sensor grouping scheme is designed to ensure reliable damage detection even in the presence of sensor faults. The proposed method is demonstrated using cable forces measured from an in-service cable-stayed bridge in China, showing sensitivity to wire rupture damage and robustness to environmental effects, measurement noise, sensor fault, and traffic patterns.
This article develops a long-term condition assessment method for stay cables in cable stayed bridges using the monitored cable tension forces under operational condition. Based on the concept of influence surface, the matched cable tension ratio of two cables located at the same side (either in the upstream side or downstream side) is theoretically proven to be related to the condition of stay cables and independent of the positions of vehicles on the bridge. A sensor grouping scheme is designed to ensure that reliable damage detection result can be obtained even when sensor fault occurs in the neighbor of the damaged cable. Cable forces measured from an in-service cable-stayed bridge in China are used to demonstrate the accuracy and effectiveness of the proposed method. Damage detection results show that the proposed approach is sensitive to the rupture of wire damage in a specific cable and is robust to environmental effects, measurement noise, sensor fault and different traffic patterns. Using the damage sensitive feature in the proposed approach, the metrics such as accuracy, precision, recall and F1 score, which are used to evaluate the performance of damage detection, are 97.97%, 95.08%, 100% and 97.48%, respectively. These results indicate that the proposed approach can reliably detect the damage in stay cables. In addition, the proposed approach is efficient and promising with applications to the field monitoring of cables in cable-stayed bridges.

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