Preliminary evaluation of precise inclination sensor and GPS for monitoring full-scale dynamic response of a tall reinforced concrete building

被引:30
|
作者
Yigit, Cemal Ozer [1 ,2 ]
Li, Xiaojing [3 ]
Inal, Cevat [1 ]
Ge, Linlin [2 ]
Yetkin, Mevlut [1 ]
机构
[1] Selcuk Univ, Dept Geomat Engn, Konya, Turkey
[2] Univ New South Wales, Sch Surveying & Spatial Informat Syst, Sydney, NSW 2052, Australia
[3] Univ New South Wales, Sch Civil & Environm Engn, Sydney, NSW 2052, Australia
关键词
Full-scale monitoring; GPS and inclination sensor; tall building; wind load; dynamic response;
D O I
10.1515/JAG.2010.010
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
It is necessary to use different sensors in an integrated manner - GPS, accelerometer, inclination sensor and so on - in order to monitor and identify static, quasi-static and resonant response of tall buildings subjected to wind loading. There are some differences among these sensors with respect to data sampling rate, data quality, and their measurement accuracy. Therefore, using different sensors together for a monitoring project is important because of the complementary nature of each sensor. In this study, the behaviour of a tall reinforced concrete building ( 30 stories high) under wind load has been monitored using GPS and inclination sensors. This paper assesses the dynamic measurement quality and reliability of inclinometers for building monitoring applications, and discusses the strengths and weaknesses of GPS vis-a-vis the use of inclination sensors for monitoring the dynamic response of tall buildings under wind load. Data collected by these sensors have been analysed in the time and frequency domains. It was found that GPS observations were distorted by multipath caused by a reflecting surface on top of the building. From the analyses in the frequency domain, the 1st mode natural frequencies of the building determined from both sensors agree very well with each other. The discrepancy of this measured 1st mode natural frequency compared to that derived from FEM (Finite Element Model) prediction is 7%.
引用
收藏
页码:103 / 113
页数:11
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