基于敏感荷载效应概率统计特征的桥梁地震荷载辨识方法
Identification method of bridge earthquakes based on the probability statistical characteristics of sensitive load effect
邵雪军 1陈斌 2陈靖 3王高新3
作者信息
- 1. 南通市市政设施管理处,江苏 南京 315800
- 2. 中铁桥隧技术有限公司,江苏 南京 210061
- 3. 中国矿业大学 力学与土木工程学院,江苏 徐州 221116
- 折叠
摘要
为精准辨识实际服役环境下的桥梁地震荷载,采用实桥监测方法获取某桥挠度和加速度在地震发生前后的监测数据,筛选出了对地震荷载敏感的 6 组结构效应,分析了 6 组敏感地震效应在日常荷载和地震作用下的时变规律,研究了 6 种敏感地震效应的概率密度统计特性,选用了正态分布函数、威布尔分布函数和广义极值分布函数对概率密度进行拟合并得到了最佳概率密度函数,利用分布函数求解出 6 种敏感地震效应阈值并利用阈值进行地震荷载辨识.结果表明:加速度时变趋势具有平稳随机特性,受温度场影响很小,挠度时变趋势具有良好的日变化特征,受温度场影响较大;筛选出的 6 种效应对地震荷载敏感,能够明显区分出日常荷载效应与地震荷载效应,可用来辨识地震荷载;采用广义极值分布函数可以较好地描述加速度和挠度最大绝对值的概率密度统计特性;在地震发生时刻,6 种敏感荷载效应的实测最大绝对值均大于阈值,表明基于敏感荷载效应概率统计特征的桥梁结构地震荷载辨识方法是有效的.
Abstract
In order to accurately identify earthquake loads on bridges in actual service environment,the monitoring deflection and acceleration data of a bridge before and after earthquakes are obtained by bridge monitoring method,and six structural effects that are sensitive to earthquakes are selected.The time-varying regularities and probability statistical characteristics of the six structural effects under daily loads and earthquakes are analyzed.The normal distribution function,Weibull distribution function and generalized extreme value distribution function are used to fit the probability density,and the best probability density function is determined.The thresholds of the six structural effects are calculated using the probability density function,which are feasible to identify the occurs of earthquakes.The probability statistical characteristics of the monitoring deflection and acceleration data is well described by the generalized extreme value distribution function.The monitoring results show that when the earthquake occurred,all the measured maximum absolute values of the six structural effects were greater than that of the thresholds,indicating that the proposed identification method of bridge earthquakes is effective.
关键词
桥梁结构/地震荷载辨识/挠度/加速度/概率密度统计特性Key words
bridge structure/earthquake identification/deflection/acceleration/statistical characteristics of probability density引用本文复制引用
基金项目
南京江北新区重点研发计划(ZDYF20200118)
出版年
2024
NETL
NSTL
维普
万方数据