Salford University researchers are working on a project to mitigate the impact of leaves on the line during train journeys.According to Salford, leaves — plus snow and rain — cause problems for trains because they reduce traction and cause wheels to spin on acceleration, or to lock when slowing down.Wheel slip/slide protection (WSP) measures in traction and braking systems are currently used to overcome the problems, but do not give instant data about the conditions of the track to the drivers and train operators.Consequently, drivers rely on rough estimates based on weather reports or track-side sensors that tell them to drive more carefully.Salford scientists are working on a solution using sensors on the train that will show contact characteristics and conditions of the track, including the maximum adhesion available in real time.The information obtained can not only be used by drivers to determine the maximum acceleration or braking forces they can...
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apply, but also to enhance the advanced control and condition monitoring for trains of the future that are also being researched by the scientists at Salford.TX Mei, a professor of control and mechatronics at Salford, said: ‘The contact mechanics at the wheel-rail interface are extremely complex and difficult problems demand sophisticated solutions in order to deliver reliable and accurate results.’The technology being developed by the Salford team is said to involve the use of a number of mathematical models of a rail vehicle to mimic train-dynamic behaviours in response to different track conditions.Those models are compared with the real vehicle — through the measurement output of vehicle-mounted inertial sensors — and the best-matched outputs are then processed using an artificial-intelligence decision-making method to give live information about the track conditions.According to Salford, the result is that wheels don’t spin on the tracks, preventing damage and increased costs. It also saves time because drivers can be optimally efficient in the speeds they travel at rather than using the current guidelines.Furthermore, the system will reportedly make better use of energy. Trains will also be able to stop more precisely at stations and won’t overshoot platforms.The Salford team is currently at the final stage of the study and looking for an industry partner to help develop the system further.

Research at the University of Salford is on track to solve the age-old problem of leaves on the line delaying trains.Leaves, as well as snow and rain, cause problems for trains because they reduce traction and cause wheels to spin on acceleration or to lock when slowing down.Wheel slip/slide protection (WSP) measures in traction and braking systems are currently used to overcome the problems, but do not give instant data about the conditions of the track to the drivers and train operators. This means that drivers rely on rough estimates based on weather reports or track-side sensors which tell them to drive more carefully.Salford scientists are working on a solution using sensors on the train that will show contact characteristics and conditions of the track – including the maximum adhesion available in real time.The information obtained can not only be used by drivers to determine the maximum acceleration or braking forces...
more...

they can apply, but also to enhance the advanced control and condition monitoring for trains of the future that are also being researched by the scientists at Salford.Professor of Control and Mechatronics at Salford, TX Mei said: “Train driving isn’t like driving a car. Loss of traction is much more difficult to feel and more difficult to compensate for.“The contact mechanics at the wheel-rail interface are extremely complex and difficult problems demand sophisticated solutions in order to deliver reliable and accurate results.”The technology being developed by the Salford team involves the use of a number of carefully selected mathematical models of a rail vehicle to mimic train dynamic behaviours in response to different track conditions.Those models are compared with the real vehicle (through the measurement output of vehicle mounted inertial sensors) and the best matched outputs are then processed using an artificial intelligence decision making method to give live information about the track conditions.The result is that wheels don’t spin on the tracks, preventing damage and increased costs. It also saves time because drivers can be optimally efficient in the speeds they travel at rather than using the current guidelines.Furthermore, the system will make better use of energy – which will save on carbon emissions and fuel consumption. Trains will also be able to stop more precisely at stations and won’t overshoot platforms.The Salford team is currently at the final stage of completing its study and is looking for an industry partner to help develop the system further.