收稿日期: 2016-07-14
修回日期: 2017-02-08
网络出版日期: 2017-05-02
基金资助
浙江省自然科学基金资助项目(LQ14E08001);浙江省交通运输厅科研计划项目(2013H25)
Big Data-Based Fatigue Life Analysis of Steel Box Girder in Large-Span Suspension Bridge
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)
马如进 徐世桥 王达磊 陈艾荣 . 基于大数据的大跨悬索桥钢箱梁疲劳寿命分析[J]. 华南理工大学学报(自然科学版), 2017 , 45(6) : 66 -73 . DOI: 10.3969/j.issn.1000-565X.2017.06.011
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.
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