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Engineers from Loughborough University, the University of Sheffield and engineering firm Perpetuum have partnered to develop a new product that will detect low adhesion hot spots in real-time and create an up-to-date map of the network.
A minimum level of adhesion is essential for reliable braking and traction performance, especially for maintaining safety and limiting delays. Changes in adhesion can be very localised, unpredictable and transient, and poor adhesion experienced by one train might not affect following trains at the same location.
Loughborough’s Dr Chris Ward, who is leading the initiative, said: “The network is in danger of low adhesion events occurring at all times and the industry takes the impact of these incredibly seriously.
“Network Rail and the wider rail industry invest huge amounts of money in rail head cleaning, controlling flora alongside lines and forecasting where low adhesion events may occur – but it’s not an exact science and affected areas may only be discovered after an incident has taken place. The areas of low adhesion can often be short-lived and various types of train can react differently to the conditions.
“This new technology, by detecting low adhesion in real-time from in-service vehicles, will allow for a much more accurate picture of where hazards lie on the UK’s huge network of track, which will mean a quicker response – such as defensive driving or railhead treatment – and as a result a safer network with fewer delays.”
The detection system will use established sensing methods to collect data that will then be processed using algorithms created by Dr Ward and colleagues at Loughborough. The experimental software should pick up small changes in how the wheels of a carriage respond to different track conditions.
As a train passes over areas of low adhesion, the vehicle moves differently compared to running over tracks with high levels of adhesion. Signals of the movements will be picked up by sensors, which are then processed and turned into an assessment of adhesion level. If required, a warning could be sent to the driver or the wider network users.
“The aim is to develop a ‘first of type’ product addressing the issue of low adhesion on the wheel-rail interface,” said Elaine Cockroft, project manager at Network Rail.
“The medium-term aspiration is to install a device on the Network Rail head treatment train or a multi-purpose vehicle, or any other suitable vehicle to capture intelligent seasonal treatment data at a minimum speed of 60mph and to demonstrate the effectiveness of the rail head treatment.
“The future ambition is to add the technology to passenger trains or freight locomotives, and so the technology would need to be developed to capture continuous data at a travelling speed of 125mph across the network. This would feed into an up-to-date adhesion map of the network.”
The 22-month study will see the research team conduct a major test programme at Network Rail’s Rail Innovation and Development Centre in Tuxford, Nottinghamshire, to test their algorithms. Artificial low adhesion will be created for the testing programme and measured using state-of-the-art friction measurement equipment from University of Sheffield.
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