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Mathematical Problems in Engineering - Volume 2014 2014, Article ID 130274, 11 pages -

Research Article

School of Civil Engineering, Southeast University, Nanjing 210096, China

College of EMPS, University of Exeter, Exeter EX4 4QF, UK

Received 21 December 2013; Revised 27 February 2014; Accepted 27 February 2014; Published 6 April 2014

Academic Editor: Ying Lei

Copyright © 2014 Rumian Zhong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Based on the basic theory of wavelet neural networks and finite element model updating method, a basic framework of damage prognosis method is proposed in this paper. Firstly, a damaged I-steel beam model testing is used to verify the feasibility and effectiveness of the proposed damage prognosis method. The results show that the predicted results of the damage prognosis method and the measured results are very well consistent, and the maximum error is less than 5%. Furthermore, Xinyihe Bridge in the Beijing-Shanghai Highway is selected as the engineering background, and the damage prognosis is conducted based on the data from the structural health monitoring system. The results show that the traffic volume will increase and seasonal differences will decrease in the next year and a half. The displacement has a slight increase and seasonal characters in the critical section of mid span, but the strain will increase distinctly. The analysis results indicate that the proposed method can be applied to the damage prognosis of girder bridge structures and has the potential for the bridge health monitoring and safety prognosis.

Autor: Rumian Zhong, Zhouhong Zong, Jie Niu, and Sujing Yuan

Fuente: https://www.hindawi.com/


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