基于桥梁挠度监测的斜拉桥拉索损伤识别的预测函数模型研究

发布时间：2018-04-01 23:35

本文选题：斜拉桥　切入点：损伤识别　出处：《石家庄铁道大学》2015年硕士论文

【摘要】：近年来,随着交通事业蓬勃发展,我国在桥梁结构的建设中投入了大量的精力,并且桥梁在交通建设中起着重要枢纽作用,随之而来桥梁垮塌事故也不断增多,桥梁的安全性问题成为了人们关注的焦点。为了保证桥梁结构能够正常安全运营,需要对桥梁结构的损伤识别问题提出更高的要求,关于桥梁结构损伤识别方法和技术的研究也已成为现今研究的热点。本文是以芜湖长江大桥(180+312+180)m斜拉桥作为研究背景,主要进行了以下几项研究工作:首先利用ANSYS工程结构仿真软件建立了斜拉桥的有限元模型并对其进行了模型修正,得到了与实桥结构基本一致的相对可靠的桥梁模型;其次根据建立的模型进行了相关计算,提取了在梁体自重、不同温度荷载和不同列车荷载工况下,引起桥梁完好状态下的挠度与索力值,并分析其规律;然后采用数理统计中基于最小二乘法的多元回归分析对计算得到的样本数据进行回归分析,利用MATLAB建立了因变量(挠度值、索力值)与自变量(温度荷载、列车荷载)之间的预测函数模型,并对该模型进行了检验评价;最后基于静力识别的统计对比诊断方法,利用预测函数模型来识别桥梁结构是否发生损伤,并根据相关的桥梁检定规范确定了两个诊断标准值。经过研究分析可知,利用多元回归分析建立的预测函数模型通过了模型检验,说明该模型具有可用性,可以用于结构的损伤识别中,并且此方法考虑了多种因素对结构响应量的影响,可以有效识别出结构是否出现损伤,适用性强。在不同的荷载工况下对芜湖长江大桥斜拉桥进行损伤识别,识别结果表明该方法可以识别出拉索是否发生损伤。如果识别出已发生损伤,则还能初步识别出损伤位置,但不能精确识别出损伤的程度,后者需要进一步研究。
[Abstract]:In recent years, with the vigorous development of transportation, our country has invested a lot of energy in the construction of bridge structure, and bridge plays an important role in traffic construction. The problem of bridge safety has become the focus of attention. In order to ensure the normal operation of bridge structure, it is necessary to put forward higher requirements for damage identification of bridge structure. The research on damage identification methods and techniques of bridge structures has also become a hot topic. This paper takes Wuhu Yangtze River Bridge 180,312 180m cable-stayed bridge as the research background. The main research work is as follows: firstly, the finite element model of cable-stayed bridge is established by using ANSYS engineering structure simulation software, and the model is modified, and a relatively reliable bridge model is obtained, which is basically consistent with the real bridge structure; Secondly, according to the established model, the deflection and cable force of the bridge under the condition of dead weight, different temperature load and different train load are extracted, and the rules are analyzed. Then the multivariate regression analysis based on the least square method in mathematical statistics is used to regress the calculated sample data, and the dependent variables (deflection value, cable force value) and independent variable (temperature load) are established by MATLAB. The prediction function model between train loads) is tested and evaluated. Finally, based on the statistical and comparative diagnosis method of static identification, the prediction function model is used to identify whether the bridge structure is damaged or not. Two diagnostic standard values are determined according to the relevant bridge verification criteria. Through research and analysis, we can see that the prediction function model established by multiple regression analysis has passed the model test, which shows that the model is available. It can be used in structural damage identification, and this method takes into account the influence of many factors on the structural response, and can effectively identify whether the structure is damaged or not. The results show that the method can identify whether the cable is damaged or not. The damage location can be preliminarily identified, but the degree of damage can not be accurately identified, which needs further study.
【学位授予单位】：石家庄铁道大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U446

【共引文献】