Novel methodology for identifying the weight of moving vehicles on bridges using structural response pattern extraction and deep learning algorithms

Author:

Zhou Yun,Pei Yilin,Zhou Sai,Zhao Yu,Hu Jianxin,Yi Weijian

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference75 articles.

1. Virtual axle method for bridge weigh-in-motion systems requiring no axle detector;He;J. Bridge Eng.,2019

2. Vehicle weight limits and overload permit checking considering the cumulative fatigue damage of bridges;Deng;J. Bridge Eng.,2018

3. Model updating of an existing bridge with high-dimensional variables using modified particle swarm optimization and ambient excitation data;Xia;Measurement.,2020

4. Prediction of bridge maximum load effects under growing traffic using non-stationary bayesian method;Yu;Eng. Struct.,2019

5. B.F. Spencer, F. Billie, M. Fernando, et al., Campaign monitoring of railroad bridges in high-speed rail shared corridors using wireless smart sensors, Newmark Structural Engineering Laboratory (NSEL) Report Series, Report No. NSEL-040, University of Illinois at Urbana-Champaign. 2015.

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