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钢桥面板疲劳损伤智能监测与评估系统研究
引用本文:张清华,崔闯,魏川,李俊,卜一之.钢桥面板疲劳损伤智能监测与评估系统研究[J].中国公路学报,2018,31(11):66.
作者姓名:张清华  崔闯  魏川  李俊  卜一之
作者单位:西南交通大学 桥梁工程系, 四川 成都 610031
基金项目:国家自然科学基金项目(51878561,51778533,51578455);“十二五”国家科技支撑计划项目(2011BAG07B03);湖北省交通运输厅科技项目(2017-538-2-4);西南交通大学“竢实之星--新世纪优秀人才后备人选培养项目
摘    要:正交异性钢桥面板作为大跨度桥梁的首选桥面板结构,实时监测并准确识别其重要构造细节的疲劳损伤程度,在此基础上预测剩余疲劳寿命,对于大跨度桥梁的服役期管理维护决策至关重要;但正交异性钢桥面板的疲劳问题具有多尺度、多模式、随机性、隐蔽性等特性,且其对结构静动力响应的影响仅限于疲劳裂纹附近的局部区域,传统的损伤识别方法难以准确识别。结合智能技术的最新发展和正交异性钢桥面板疲劳问题的基本属性,构建了其疲劳损伤智能监测与评估系统,并对其疲劳损伤指标和疲劳损伤智能评估的相关关键问题进行研究。提出了基于等效结构应力的正交异性钢桥面板多尺度疲劳损伤评估方法;建立了考虑随机因素的结构体系实时疲劳损伤评估及剩余寿命预测方法;构建了正交异性钢桥面板疲劳损伤智能监测与评估系统;基于实际桥梁结构的交通量和结构响应监测信息,对所建立的正交异性钢桥面板疲劳损伤智能监测与评估系统进行了验证。研究结果表明:在实际交通荷载作用下,顶板与纵肋连接细节的疲劳主导失效模式为焊根部位起裂沿顶板扩展,所提出的疲劳损伤评估方法的评估结果与实际结构一致,表明所提出的方法能够准确确定结构体系的疲劳失效模式;疲劳损伤智能监测与评估系统所确定的实桥疲劳损伤及剩余寿命预测结果与实际桥梁疲劳损伤开裂时间基本一致;所建立的智能监测与评估系统可为正交异性钢桥面板疲劳损伤过程和寿命评估提供理论依据及支撑,并为实桥的运营管理养护决策提供科学依据。

关 键 词:桥梁工程  正交异性钢桥面板  智能监测与评估系统  疲劳损伤  评估方法  
收稿时间:2018-08-15

Research on Intelligent Monitoring and Assessment System for Fatigue Damage of Orthotropic Steel Deck Structural System
ZHANG Qing-hua,CUI Chuang,WEI Chuan,LI Jun,BU Yi-zhi.Research on Intelligent Monitoring and Assessment System for Fatigue Damage of Orthotropic Steel Deck Structural System[J].China Journal of Highway and Transport,2018,31(11):66.
Authors:ZHANG Qing-hua  CUI Chuang  WEI Chuan  LI Jun  BU Yi-zhi
Institution:Department of Bridge Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
Abstract:Orthotropic steel deck (OSD) is the first choice for long-span bridge deck. It is great of importance for management and maintenance of OSD in service to monitor and detect the real-time fatigue damage and residual life at the critical fatigue vulnerable details. The initiation of fatigue cracks in orthotropic steel deck (OSD) is difficultly detected by the conventional damage detection method due to the multiscale, multimode, randomicity, and concealment of fatigue damage. And the effect of fatigue damage on static and dynamic response of structure is limited in the extremely vicinity. In addition, the conventional health monitoring is faced with a challenge in respect of fatigue damage identification. Taking the basic properties of fatigue damage and intelligent monitoring evaluation as the orientations, the intelligent monitoring and evaluation system of fatigue damage was constructed, and the related issues about fatigue damage index and intelligent evaluation were studied. Fatigue damage evaluation method considering the multiscale damage was developed by using effective structure stress method. Integrating with the traffic loads information, the real-time fatigue damage and residual life of OSD using the real monitoring information of traffic flow and structural responses were investigated. Then, the intelligent fatigue damage monitoring and evaluation system associated with visual indexes for OSD system was established. Moreover, the proposed the system for intelligent monitoring and assessment of OSD fatigue damage was validated. It is indicated that the fatigue crack initiation at weld root of rib-to-deck joints and then propagation along the thickness of deck is the dominant fatigue failure mode which is same to the real failure mode in OSD under stochastic traffic flow. A close agreement with the real fatigue failure mode can demonstrate that the developed fatigue evaluation for OSD system can accurately monitor the fatigue failure mode of OSD. The evaluation and prognosis of fatigue damage and residual life based on the intelligent monitoring and evaluation system keep good accordance with the real fatigue life, revealing that the proposed intelligent monitoring and evaluation system is utilized to predict the fatigue life accurately. The theoretical reference and assistance can be offered for evaluation of fatigue damage and life, and the technological support for the management and maintenance of bridge in service can be given.
Keywords:bridge engineering  orthotropic steel deck  intelligent monitoring and evaluation system  fatigue damage  assessment approach  
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