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Advances in Materials Science and Engineering
Volume 2017 (2017), Article ID 7460378, 10 pages
Research Article

Cubic Function-Based Bayesian Dynamic Linear Prediction Approach of Bridge Extreme Stress

1Key Laboratory of Mechanics on Disaster and Environment in Western China, Ministry of Education of China, Lanzhou University, Lanzhou, China
2School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China

Correspondence should be addressed to Xueping Fan

Received 17 June 2017; Accepted 10 September 2017; Published 24 October 2017

Academic Editor: Francesco Ruffino

Copyright © 2017 Yuefei Liu 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.


In structural health monitoring (SHM) field, the structural stress prediction and assessment are the research bottleneck. To reasonably and dynamically predict structural extreme stress based on the time-variant monitored data, the objectives of this paper are to present (a) cubic function-based Bayesian dynamic linear models (BDLM) about monitored extreme stress, (b) choosing method of optimum probability distribution functions about initial stress state, (c) monitoring mechanism of the optimum BDLM, and (d) an effective way of taking advantage of BDLM to incorporate the time-variant monitored data into structural extreme stress prediction. The monitored data of an existing bridge is adopted to illustrate the feasibility and application of the proposed models and procedures.