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A multi-sensing monitoring system to study deterioration of a railway bridge

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Alexakis, H 
Franza, A 
Acikgoz, S 
DeJong, MJ 

Abstract

This study presents a multi-sensing monitoring system recently installed in a Victorian railway viaduct in Leeds, UK. The viaduct is in continuous use since its construction during the 19th century and suffers extensive cracking due to the combined action of increased train loads and environmental effects. The bridge was retrofitted in 2015 and there was the need to assess the effectiveness of the intervention and better understand the ongoing deterioration process. For this reason, a multi-sensing system was designed that comprises a fibre Bragg grating network to measure distributed dynamic deformation across three arch spans of the bridge, acoustic emission sensors to detect rates of cracking, and high sensitivity accelerometers to study the dynamic response at critical locations. The system is self-sustaining, self-powered and remotely controlled, and uses an algorithm that combines information from the three different types of sensors to track variations of response parameters of the bridge over time.

Description

Keywords

Journal Title

9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - Conference Proceedings

Conference Name

9th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-9), St. Louis, Missouri, USA

Journal ISSN

Volume Title

2

Publisher

Rights

All rights reserved
Sponsorship
Engineering and Physical Sciences Research Council (EP/N021614/1)
Technology Strategy Board (920035)
Engineering and Physical Sciences Research Council (EP/I019308/1)
Engineering and Physical Sciences Research Council (EP/K000314/1)
Engineering and Physical Sciences Research Council (EP/L010917/1)
Engineering and Physical Sciences Research Council (EP/P013848/1)
This work is being funded by the Lloyd’s Register Foundation, EPSRC and Innovate UK through the Data-Centric Engineering programme of the Alan Turing Institute and through the Cambridge Centre for Smart Infrastructure and Construction. Funding for the monitoring installation was provided by EPSRC under the Ref. EP/N021614/1 grant and by Innovate UK under the Ref. 920035 grant.