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  5. A drive-by inspection system via vehicle moving force identification
 
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A drive-by inspection system via vehicle moving force identification

Author(s)
O'Brien, Eugene J.  
McGetrick, P.  
González, Arturo  
Uri
http://hdl.handle.net/10197/6357
Date Issued
2014-05
Date Available
2015-02-12T11:07:09Z
Abstract
This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.
Sponsorship
European Commission - Seventh Framework Programme (FP7)
Type of Material
Journal Article
Publisher
Techno-Press
Journal
Smart Structures and Systems
Volume
13
Issue
5
Start Page
821
End Page
848
Subjects

Acceleration

Bridge

Global stiffness

Inverse dynamics

Road profiles

Vehicle-bridge intera...

Vehicle forces

DOI
10.12989/sss.2014.13.5.821
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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OBrien_etal_2014_a_drive_by_inspectino_system_via_vehicle_moving_force_identification.pdf

Size

1.68 MB

Format

Adobe PDF

Checksum (MD5)

f785d39a66d72d30ac6e582102c58aa4

Owning collection
Civil Engineering Research Collection
Mapped collections
Earth Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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