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Robust fibre optic sensor arrays for monitoring early-age performance of mass-produced concrete sleepers

Accepted version
Peer-reviewed

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Type

Article

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Authors

Butler, LJ 
Xu, J 
He, P 
Dirar, S 

Abstract

This study investigates integrating fibre optic sensing technology into the production process of concrete railway sleepers. Robust fibre Bragg grating strain and temperature sensor arrays were developed specifically for this application and were designed for long-term monitoring of sleeper performance. The sensors were used to monitor sleeper production and to help gain a deeper understanding of their early-age behaviour which can highly influence long-term performance. In total, 12 sleepers were instrumented and strain data were collected during the entire manufacturing process including concrete casting and curing, prestressing strand detensioning and qualification testing. Following the production process, sleepers were stored temporarily and monitored for 4 months until being placed in service. The monitoring results highlight the intrinsic variability in strain development among identical sleepers, despite high levels of production quality control. Using prestress loss as a quality control indicator, the integrated sensing system demonstrated that sleepers were performing within Eurocode-based design limits prior to being placed in service. A three-dimensional nonlinear finite element model was developed to provide additional insight into the sleepers’ early-age behaviour. Based on the fibre Bragg grating–calibrated finite element model, more realistic estimates for the creep coefficient were provided and found to be 48% of the Eurocode-predicted values.

Description

Keywords

fibre optic sensors, early-age concrete behaviour, prestress losses, finite element analysis, concrete sleepers

Journal Title

Structural Health Monitoring

Conference Name

Journal ISSN

1475-9217
1741-3168

Volume Title

Publisher

SAGE Publications
Sponsorship
Engineering and Physical Sciences Research Council (EP/L010917/1)
Engineering and Physical Sciences Research Council (EP/N021614/1)
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors thank the EPSRC and Innovate UK for funding this research through the Cambridge Centre for Smart Infrastructure and Construction (CSIC) Innovation and Knowledge Centre (EPSRC grant reference number EP/L010917/1).