A Self-Sensing Digital Twin of a Railway Bridge using the Statistical Finite Element Method

by   Eky Febrianto, et al.

The monitoring of infrastructure assets using sensor networks is becoming increasingly prevalent. A digital twin in the form of a finite element model, as used in design and construction, can help in making sense of the copious amount of collected sensor data. This study demonstrates the application of the statistical finite element method (statFEM), which provides a consistent and principled means for synthesising data and physics-based models, in developing a digital twin of an instrumented railway bridge. The considered structure is a steel skewed half-through bridge of 27.34 m length located along the West Coast Mainline near Staffordshire in the UK. Using strain data captured from fibre Bragg grating (FBG) sensors at 108 locations along the bridge superstructure, statFEM can predict the `true' system response while taking into account the uncertainties in sensor readings, applied loading and finite element model misspecification errors. Longitudinal strain distributions along the two main I-beams are both measured and modelled during the passage of a passenger train. The digital twin, because of its physics-based component, is able to generate reasonable strain distribution predictions at locations where no measurement data is available, including at several points along the main I-beams and on structural elements on which sensors are not even installed. The implications for long-term structural health monitoring and assessment include optimization of sensor placement, and performing more reliable what-if analyses at locations and under loading scenarios for which no measurement data is available.



There are no comments yet.


page 1

page 2


The Statistical Finite Element Method

The finite element method (FEM) is one of the great triumphs of modern d...

A Quantile-Based Approach to Modelling Recovery Time in Structural Health Monitoring

Statistical techniques play a large role in the structural health monito...

Error analysis for a statistical finite element method

The recently proposed statistical finite element (statFEM) approach synt...

Analysis of a stabilised finite element method for power-law fluids

A low-order finite element method is constructed and analysed for an inc...

A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware

Technological advancement in Wireless Sensor Networks (WSN) has made it ...

Crowdsourcing Bridge Vital Signs with Smartphone Vehicle Trips

The efficacy of sensor data in modern bridge condition evaluations has b...

Leveraging Gaussian Process and Voting-Empowered Many-Objective Evaluation for Fault Identification

Using piezoelectric impedance/admittance sensing for structural health m...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.