Traffic & Transportation Engineering

Big Data-Based Fatigue Life Analysis of Steel Box Girder in Large-Span Suspension Bridge

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  • Department of Bridge Engineering,Tongji University,Shanghai 200092,China
马如进(1978-),男,博士,副教授,主要从事桥梁养护管理理论研究. E-mail:rjma@tongji.edu.cn

Received date: 2016-07-14

  Revised date: 2017-02-08

  Online published: 2017-05-02

Supported by

Supported by the Natural Science Foundation of Zhejiang Province(LQ14E08001)

Abstract

In order to effectively use the mass data accumulated by bridge monitoring system to analyze the perform- ance of a bridge,first,by taking Xihoumen Bridge as an object,a multi-scale nonlinear finite element model is established,and a method to verify the reliability of the proposed model according to such monitoring data as wind speed,temperature,vehicle load and displacement is presented.Next,on the basis of mass data recorded by the WIM system,six types of standard fatigue vehicles are determined and applied to the multi-scale finite element model to calculate the stress response of the details of steel box girder.Then,by combining Palmgren-Miner linear cumulative damage theory with the stress amplitude,the theoretical fatigue life of structural details in the steel box girder is obtained.Moreover,by means of filtering,denoising and other big data processing methods,the moni- tored stress data are analyzed to calculate the actual fatigue life of the weld details and to determine the correction coefficient of the theoretical fatigue life.Finally,according to the corrected fatigue life,the structural details of the steel box girder in different positions are divided into four fatigue grades.This research provides a new ap- proach to obtaining the fatigue life of the details without laying sensors.It also serves as a guidance for the daily maintenance and management of steel box girders in long-span bridges.

Cite this article

MA Ru-jin XU Shi-qiao WANG Da-lei CHEN Ai-rong . Big Data-Based Fatigue Life Analysis of Steel Box Girder in Large-Span Suspension Bridge[J]. Journal of South China University of Technology(Natural Science), 2017 , 45(6) : 66 -73 . DOI: 10.3969/j.issn.1000-565X.2017.06.011

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