Using statistical analysis of an acceleration-based bridge weigh-in-motion system for damage detection

Files in This Item:
 File SizeFormat
DownloadRevised_manuscript.docx2.19 MBUnknown
Title: Using statistical analysis of an acceleration-based bridge weigh-in-motion system for damage detection
Authors: O'Brien, Eugene J.Khan, Muhammad ArslanMcCrum, DanielZnidaric, Ales
Permanent link: http://hdl.handle.net/10197/12902
Date: 17-Jan-2020
Online since: 2022-06-03T12:06:19Z
Abstract: This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles-data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition.
Funding Details: Science Foundation Ireland
Funding Details: National Science Foundation (USA)
Invest Northern Ireland
Type of material: Journal Article
Publisher: MDPI
Journal: Applied Sciences
Volume: 10
Issue: 2
Start page: 1
End page: 20
Copyright (published version): 2020 the Authors
Keywords: Bridge health monitoringBWIMStructure dynamicsDamage detectionSHMVehicle-bridge interaction
DOI: 10.3390/app10020663
Language: en
Status of Item: Peer reviewed
ISSN: 2076-3417
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by/3.0/ie/
Appears in Collections:Civil Engineering Research Collection

Show full item record

Page view(s)

81
Last Week
19
Last month
checked on Jun 25, 2022

Download(s)

12
checked on Jun 25, 2022

Google ScholarTM

Check

Altmetric


If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.