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AuthorButler, L.J.
AuthorLau, D.-H.
AuthorGregory, A.
AuthorGirolami, M.
AuthorElshafie, M.Z.E.B.
Available date2024-08-05T07:19:21Z
Publication Date2019
Publication NameInternational Conference on Smart Infrastructure and Construction 2019, ICSIC 2019: Driving Data-Informed Decision-Making
ResourceScopus
URIhttp://dx.doi.org/10.1680/icsic.64669.343
URIhttp://hdl.handle.net/10576/57450
AbstractA variety of methods exist in the structural health monitoring literature that aim to combine the observed data and predicted outputs from physics-based models (e.g. model updating and calibration). Typically implemented on a case-by-case basis, there is currently no unifying procedure or method for formally synthesising this combination of information. Data-centric engineering (DCE) is an emerging class of analytical approaches that is aimed at studying engineered systems and assets through the synthesis of various data-driven and physicsbased models. DCE may also involve procedures for fusing sensor data from both experimental and operational systems. This paper introduces a DCE-based approach using data collected from experimental and operational railway structures (bridges and sleepers), which have been instrumented with advanced fibre optic sensors (FOS). This study provides a high-level definition of DCE approaches to studying instrumented infrastructure and discusses some of the challenges in implementing these methods in practice. An example of an implementation of a Gaussianprocess based DCE method is provided, with the goal of predicting the response of operational instrumented rail infrastructure (i.e. concrete sleepers) over time. Some practical issues of this implementation relate to the measurement systems, data acquisition rate, efficiently batch processing the data and accounting for uncertainty in the response predictions. In leveraging both the information gained from real-time measurement data and from traditional analytics or physics-based methods, a DCE-based modelling approach can provide unique a set information and insights into the operational performance of infrastructure.
Languageen
PublisherICE Publishing
SubjectData acquisition
Data handling
Decision making
Railroad transportation
Structural health monitoring
Uncertainty analysis
Analytical approach
Instrumented infrastructure
Operational performance
Physics-based methods
Physics-based models
Rail infrastructure
Real time measurements
Response prediction
Batch data processing
TitleIntroducing data-centric engineering to instrumented infrastructure
TypeConference Paper
Pagination343-349
dc.accessType Open Access


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