结构健康监测数据科学与工程  

DATA SCIENCE AND ENGINEERING FOR STRUCTURAL HEALTH MONITORING

作　　者：李惠[1] 鲍跃全[1] 李顺龙[1] 张东昱[1] 

机构地区：[1]哈尔滨工业大学土木工程学院,黑龙江哈尔滨150090

出　　处：《工程力学》2015年第8期1-7,共7页Engineering Mechanics

基　　金：国家973计划课题项目(2013CB036305);科技支撑计划项目(2011BAK02B02);国家自然科学基金项目(51378154;51161120359)

摘　　要：结构健康监测作为保障重大工程结构安全的重要技术,近些年来在世界范围内得到了快速的发展和应用,国内外许多大型工程结构安装了监测系统并且积累了海量的监测数据。结构健康监测数据分析与挖掘越来越受到国内外学者的关注,成为当前国际上土木工程领域的热点研究方向,该文结合国际上应用数学和信息领域的最新成果,总结课题组在结构健康监测数据分析与挖掘方面的最新研究进展,主要包括:基于压缩感知理论结构健康监测数据处理、车辆荷载空间分布识别、斜拉索实时索力识别、复杂因素耦合作用下斜拉索安全评定、结构健康监测的Benchmark模型、结构健康监测的数据分析与挖掘软件系统以及桥梁结构安全监测技术规程等方面的内容。Structural health monitoring （SHM） technology has been developed approximately for a decade, and many civil infrastructures have been installed SHM systems. These systems produce huge quantities of data each day. It is well-recognized that data mining and analysis for the massive volume of measurement data collected from SHM system of long-span bridge structures is increasingly becoming a world-wide research focus. This paper reviews the recently development of data mining and analysis on our research group, mainly including compressive sensing based data analysis for SHM, the identification of distribution of vehicle loads, the identification of time-varying cable tension forces, the assessment of cable under multiple factors coupling effects, the benchmark model of SHM, the software for SHM data analysis and design code for SHM systems.

关 键 词：结构健康监测 数据挖掘 压缩感知 车辆荷载空间分布 BENCHMARK模型 

分 类 号：U446[建筑科学—桥梁与隧道工程]