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Railway Bridge Condition Monitoring Using Numerically Calculated Responses from Batches of Trains
Date Issued
14 May 2022
Date Available
04T15:36:25Z July 2022
Abstract
This study introduces a novel method to determine apparent profile of the track and detect railway bridge condition using sensors on in-service trains. The concept uses a type of Inverse Newmark-β integration scheme on data from a batch of trains. In a self-calibration process, an optimization algorithm is used to find vehicle dynamic properties and speed. For bridge health monitoring, the apparent profile of the bridge is first determined, i.e., the true profile plus components of ballast and bridge deflection under the moving train. The apparent profile is used, in turn, to calculate the moving reference deflection influence line, i.e., the deflection due to a moving (static) unit load. The moving reference influence line is shown to be a good indicator of bridge stiffness. This numerical approach is assessed using an elaborate finite element model operated by an independent research group. The results show that the moving reference influence line can be found accurately and that it constitutes an effective indicator of the condition of a bridge.
Sponsorship
University College Dublin
Other Sponsorship
Chinese Scholarship Council
Type of Material
Journal Article
Publisher
MDPI
Journal
Applied Sciences
Volume
12
Issue
10
Start Page
1
End Page
24
Copyright (Published Version)
2022 The Authors
Language
English
Status of Item
Peer reviewed
ISSN
2076-3417
This item is made available under a Creative Commons License
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2022_Railway bridge condition monitoring using a batch of in-service trains.pdf
Size
3.77 MB
Format
Owning collection
Scopus© citations
5
Acquisition Date
Dec 7, 2023
Dec 7, 2023
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