4.7 Article

Testing and long-term monitoring of a curved concrete box girder bridge

期刊

ENGINEERING STRUCTURES
卷 33, 期 10, 页码 2861-2869

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2011.05.026

关键词

Bridge; Test vehicle; Natural frequencies; Long-term monitoring; System identification; Ambient vibration; Curved concrete box girder

资金

  1. California Department of Transportation

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Capital investment in national infrastructure is significant. The need to maintain and protect critical infrastructure links has led in recent years to significant developments in the area of structural health monitoring. The objective is to track a structure's long-term performance, typically using sensors, and to successively compare the most recently measured responses with prior response history. During construction of the West Street On-Ramp, a curved concrete box girder bridge, located in the city of Anaheim (California), eleven accelerometers were permanently installed on its bridge deck. The associated data acquisition system was configured to record once a specified threshold acceleration response was exceeded; during the period 2002-2010 a total of 1350 datasets including six earthquakes, for each of the eleven sensors, were acquired. This automatically acquired data was supplemented, during the summer of 2009, with responses measured during controlled vehicle tests. Six accelerometers were additionally installed on the frame of the weighed test vehicle. This paper presents the findings of the analyses of these measured data sets and serves to inform owners and managers as to the potential feedback from their instrumentation investment. All response histories were analyzed using frequency domain techniques for system identification. Extraction of the modal characteristics revealed a continuous reduction, of approximately 5%, in the first three natural frequencies over the period of the study. The measured responses from the vehicle sensors are discussed in the context of identifying the potential for bridge frequency measurement using instrumented vehicles. (C) 2011 Elsevier Ltd. All rights reserved.

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