摘要
为识别列车荷载引起的桥梁结构损伤,基于车致振动的加速度响应,提出了一种损伤位置识别方法.该方法通过结构易损性分析,确定结构易损的部位,并根据易损部位的损伤状态,从列车行驶的时间区域中选择若干子区域;然后,假设在每一个子区域内特定易损部位的损伤状态保持不变,将损伤位置识别分为2个层次进行,每一层次均以加速度时程数据构建损伤指标,从多个角度优化样本库,并采用支持向量机作为分类工具,建立损伤位置识别模型.对一连续梁的实例分析表明:该方法能够考虑结构状态与列车荷载的相关性,在损伤最易出现的时间子区域内,对易损部位进行损伤识别,可获得较好的损伤位置识别结果;且在低水平噪声干扰下,识别结果变化不大.
In order to detect the bridge damage caused by train load,a method for damage location identification was put forward based on acceleration response caused by vehicles.With this method,structural damage vulnerability is firstly analyzed to find out vulnerable sections.From the damage states of these sections,several subdomains are selected from the time domain when a train is running.In every subdomain,the damage states of the studied sections are supposed to remain the same,and damage location identification of every subdomain is divided into 2 hierarchies,a model for damage location identification is established for each hierarchy by using the acceleration history data as damage indexes,sample sets are optimized from several viewpoints,and support vector machine is taken as a tool of classification.The analysis results for a continuous girder show that by taking the correlation between structural damage states and train load into account,this method can detect the vulnerable sections in the time subdomains when damage is prone to appear,and obtain the preferable results of damage location identification with only a little change under low-level noise disturbance.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2011年第5期719-725,769,共8页
Journal of Southwest Jiaotong University
基金
国家自然科学基金资助项目(51078316)
关键词
桥梁工程
损伤位置识别
子区域
加速度时程数据
支持向量机
bridge engineering
damage location identification
subdomain
acceleration history data
support vector machine