Monitoring data-based traffic load effect model statistical analysis for arch bridge suspender

Xin Gao; Jinping Ou

doi:10.1117/12.817805

30 March 2009 Monitoring data-based traffic load effect model statistical analysis for arch bridge suspender

Xin Gao, Jinping Ou

Proceedings Volume 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009; 729236 (2009) https://doi.org/10.1117/12.817805
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2009, San Diego, California, United States

Abstract

Based on the bridge health monitoring data, the traffic-load effect model for arch bridge suspender was set up using direct statistical method. Firstly, the Bridge Health Monitoring System (BSHM) set up on the Ebian Dadu River Bridge in Sichuan province to obtain daily traffic-load effect of suspenders was introduced. Secondly, the section distribution of suspender traffic-load effect was researched by statistical approach using monitoring data. Finally, the probability distribution of maximum traffic-load effect during design period was given. The statistical result shows that the section distribution of suspender traffic-load effect follows lognormal distribution and the probability distribution of maximum traffic-load effect during design period follows generalized extreme-value distribution. The traffic-load effect model of suspender was different with the design code given which may underestimates the real load effect level. It's the first time in China to determine the traffic-load effect probability model for arch bridge suspenders based on actual acquired monitoring data using statistical and probabilistic approach.

Citation Download Citation

Xin Gao and Jinping Ou "Monitoring data-based traffic load effect model statistical analysis for arch bridge suspender", Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009, 729236 (30 March 2009); https://doi.org/10.1117/12.817805

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