Monitoring of Vehicle-Bridge Interaction using Mobile and Static Wireless Sensor Networks

被引:0
|
作者
Kim, Junhee [1 ]
Lynch, Jerome P. [1 ,2 ]
Lee, Jong-Jae [3 ]
Lee, Chang-Geun [4 ]
机构
[1] Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
[3] Sejong Univ, Dept Civil & Environm Engn, Seoul, South Korea
[4] Korea Expressway Corp, Expressway & Transportat Res Inst, Gyeonggi Do, South Korea
基金
美国国家科学基金会;
关键词
wireless sensors; vehicle-bridge interaction; structural health monitoring; acceleration integration; Kalman filtering;
D O I
10.1117/12.880150
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Bridges undergo dynamic vehicle-bridge interaction when heavy vehicles drive over them at high speeds. Traditionally, analytical models representing the dynamics of the bridge and vehicle have been utilized to understand the complex vehicle-bridge interaction. Analytical approaches have dominated the field due to the numerous challenges associated with field testing. Foremost among the challenges is the cost and difficulties associated with the measurement of two different systems, i.e. mobile vehicle and static bridge. The recent emergence of wireless sensors in the field of structural monitoring has created an opportunity to directly monitor the vehicle-bridge interaction. In this study, the unrestricted mobility of wireless sensors is utilized to monitor the dynamics of test vehicle driving over a bridge. The integration of the mobile wireless sensor network in the vehicle with a static wireless monitoring system installed in the bridge provides a time-synchronized data set from which vehicle-bridge interaction can be studied. A network of Narada wireless sensor nodes are installed in a test truck to measure vertical vibrations, rotational pitching, and horizontal acceleration. A complementary Narada wireless sensor network is installed on the Geumdang Bridge (Icheon, Korea) to measure the vertical acceleration response of the bridge under the influence of the truck. The horizontal acceleration of the vehicle is used to estimate the position trajectory of the truck on the bridge using Kalman filtering techniques. Experimental results reveal accurate truck position estimation and highly reliable wireless data collection from both the vehicle and the bridge.
引用
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页数:11
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