Automated Surface Inspection

Automated rail track inspection

Tuesday 26th November, 2019

automated rail track inspection

Omnicom Balfour Beatty and the University of York have joined forces to create a rail track inspection system, which could save £10 million per year in maintenance costs for the rail industry. The project has been worked on for over two years, with the objective of digitalising line inspection, by using machine vision inspection systems.

Research into the new system was supported by the government’s Knowledge Partnership Trust. Knowledge Transfer Partnerships is a UK-wide programme that has been helping businesses for the past 40 years to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base.

The machine vision system uses a camera attached to the front of a train to inspect the tracks. The cameras collect high definition images of the track which is then analysed by an inspection system, from which any defects or faults in the line can be highlighted.

The automated system can also identify potential faults before they arise, allowing preventative fixes to be made before urgent repairs are required.

The automated technology is now being progressed from proof of concept into commercial-grade software. The end goal for Balfour Beatty is to make the process quicker, safer and more efficient than the current manual inspection process.

Professor Richard Wilson, lead researcher on the project from the Department of Computer Science at the University of York, said: “These machine-vision technologies for high-speed rail inspection will improve the reliability of the railway network, reduce costs and increase the safety of manual inspection. The computer vision and machine learning technologies provide automated inspection of complex assets such as junctions and crossings”.

Interested in automated inspection?

Shelton Visions’ tailor-made vision inspection system means a variety of fault types are well within the range of our machine vision system. If you would like to get in touch to discuss how we could help improve your bottom line, then please call 0116 279 0920 or complete our contact form.

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