Data science and engineering for structural health monitoring

被引：0
|
作者：
School of Civil Engineering, Harbin Institute of Technology, Harbin [1 ]
Heilongjiang
150090, China
机构：
[1] School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, Heilongjiang
来源：
Gongcheng Lixue | / 8卷 / 1-7期
关键词：
Benchmark model; Compressive sensing; Data mining; Spatial distribution of vehicle loads; Structural health monitoring;
D O I：
10.6052/j.issn.1000-4750.2014.08.ST11
中图分类号：
学科分类号：
摘要：
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. ©, 2015, Tsinghua University. All right reserved.
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页码：1 / 7
页数：6
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