Simultaneous identification method of damage and vehicle parameters on bridges utilizing long-gauge strain influence line under moving vehicle loads

Shizhi Chen; Gang Wu; Bitao Wu

doi:10.1117/12.2257403

12 April 2017 Simultaneous identification method of damage and vehicle parameters on bridges utilizing long-gauge strain influence line under moving vehicle loads

Shizhi Chen, Gang Wu, Bitao Wu

Author Affiliations +

Proceedings Volume 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017; 1016821 (2017) https://doi.org/10.1117/12.2257403
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2017, Portland, Oregon, United States

Abstract

Currently, there have been plenty of researches conducted for two main problems in structural health monitoring, damage and vehicle parameter identification on bridges. However, only a handful of methods could achieve these two functions synchronously, which would cause the redundancy of sensors also the rise of cost in monitoring system. In this paper, a method to identify damage and vehicle parameters, such as axle load, wheelbase and velocity on a bridge simultaneously was proposed, based on the influence line of long-gauge strain. The influence line of long-gauge strain was derived primarily according to conventional strain influence line theory, at the basis of which the relationships among the local element bending stiffness of bridge, vehicle parameters and long-gauge strain were figured out then. The two order difference of long-gauge strain was chosen as the key index to found this identification method. Finally, to verify the reliability of this method, a set of numerical simulations was conducted, whose results showed that this method exhibited good performance.

Citation Download Citation

Shizhi Chen, Gang Wu, and Bitao Wu "Simultaneous identification method of damage and vehicle parameters on bridges utilizing long-gauge strain influence line under moving vehicle loads", Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 1016821 (12 April 2017); https://doi.org/10.1117/12.2257403

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