Postdoctoral researcher Muhammad Arslan Khan presents a research poster on ‘Automated and Rapid Fault Diagnosis of Railway Tracks using In-Service Train Measurements’.
Di-Rail is a research project funded by Science Foundation Ireland under “Frontiers for the Future 2020” call. Di-Rail is based in Structural Dynamics and Assessment Laboratory (SDA-Lab) in the School of Civil Engineering at University College Dublin. The project started in Dec 2021 and will be carried out over three years.
This project will bring the latest advances in machine learning from computer science into structural health monitoring and railway engineering to develop an innovative solution for railway infrastructure assessment and maintenance. Instead of conventional railway track monitoring approaches such as inefficient method of ‘walking the track’ and expensive approach of using ‘track recording vehicles’, this project proposes using inexpensive, frequent and widely available data measured on in-service trains to monitor railway track condition. The proposed approach does not disturb service provision and can provide real time data on track condition which has a substantial potential to revolutionize railway maintenance sector.
In this study monitoring of the natural frequencies of Malahide viaduct bridge isn’t carried out. The bridge includes a series of simply supported spans, two of which collapsed in 2009 and were replaced. In this work, the accuracy and robustness of the indirect approach for monitoring of multi span bridges is discussed.