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Drive-by Bridge Damage Detection Using Curvatures in Uncertain Environments
Date Issued
2016-08-30
Date Available
2016-09-20T09:59:45Z
Abstract
Considerable effort has been dedicated in recent years to the development of bridge damage detection techniques. Recently, drive-by monitoring has become popular as it allows the bridge to be monitored without installing sensors on it. In this work, the Traffic Speed Deflectometer (TSD), which incorporates a set of laser Doppler sensors on a straight beam to obtain the relative velocity between the vehicle and the pavement surface, is modelled to obtain deflections on the bridge as the vehicle drives. From these deflections it is possible to obtain the curvature of the bridge, from which inferences on damage can be made. However, most of the time, the measurements taken by drive-by sensors are subject to a set of uncertainties or noise that can lead the damage detection procedure to either give false positives or to miss damage. For that reason, an analysis is needed in order to determine if these methods can work properly in uncertain or noisy environments. Moreover, as the road surface roughness affects the dynamic interaction between the vehicle and the bridge, this may also have an effect on the damage predictions. Hence, the goal of this paper is to study the sensitivity of curvature measurements to both the presence of environmental noise and the effect of the road surface roughness.
Sponsorship
European Commission Horizon 2020
Other Sponsorship
Innovation Programme
Marie Sklodowska-Curie grant
Type of Material
Conference Publication
Publisher
Civil Engineering Research Association of Ireland
Web versions
Language
English
Status of Item
Not peer reviewed
Conference Details
Civil Engineering Research in Ireland Conference (CERI2016), Galway, Ireland, 29-30 August 2016
This item is made available under a Creative Commons License
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Drive-by_Bridge_Damage_Detection_Using_Curvatures_in_Uncertain_Environments.pdf
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