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http://dx.doi.org/10.12989/sss.2018.21.5.695

Structural health monitoring of a high-speed railway bridge: five years review and lessons learned  

Ding, Youliang (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University)
Ren, Pu (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University)
Zhao, Hanwei (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University)
Miao, Changqing (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University)
Publication Information
Smart Structures and Systems / v.21, no.5, 2018 , pp. 695-703 More about this Journal
Abstract
Based on monitoring data collected from the Nanjing Dashengguan Bridge over the last five years, this paper systematically investigates the effects of temperature field and train loadings on the structural responses of this long-span high-speed railway bridge, and establishes the early warning thresholds for various structural responses. Then, some lessons drawn from the structural health monitoring system of this bridge are summarized. The main context includes: (1) Polynomial regression models are established for monitoring temperature effects on modal frequencies of the main girder and hangers, longitudinal displacements of the bearings, and static strains of the truss members; (2) The correlation between structural vibration accelerations and train speeds is investigated, focusing on the resonance characteristics of the bridge at the specific train speeds; (3) With regard to various static and dynamic responses of the bridge, early warning thresholds are established by using mean control chart analysis and probabilistic analysis; (4) Two lessons are drawn from the experiences in the bridge operation, which involves the lacks of the health monitoring for telescopic devices on the beam-end and bolt fractures in key members of the main truss.
Keywords
structural health monitoring; high-speed railway bridge; long-term monitoring data; bridge response; early warning threshold;
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Times Cited By KSCI : 2  (Citation Analysis)
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