The development & optimisation of a Nitrogen Arc Discharge Plasma railway cleaning system, embedding plasma science within the technical development team, and influencing the new product development route map.

The Leaves on the Line Track Sensor RAMAN 4 the Railways UK societal cost of 'Leaves on the Line' delays has been estimated at £355million annually. This includes cost of cleaning and maintenance of the tracks during the Autumnal season, as well as delays & chaotic changes to autumnal timetabling. Leaves fall on and around the track and as the train passes its aerodynamic effect deposits more leaves onto the railtrack. When the train passes over the leaves, the wheels compress them into a paste, with a force of around one gigapascal (30 tonnes a square inch), between the wheel and track. The leaves are transformed into a black teflon-like surface (called a 3rd layer contaminant), that's bonded to the track surface. This super slippery layer reduces grip, meaning trains need to accelerate and brake gently to avoid slipping. This problem can also be created by other contaminants , such as grease, oil, fuel & corrosion. There is currently no system for sensing/ measuring the railtrack condition in real-time. This information would be invaluable for many different aspects of the UK railway running; including Network Rail Seasonal track cleaning teams, timetable schedulers, and train drivers. RAMAN sensing is used in chemical & pharmaceutical industries to analyse material compounds. PlasmaTrack, with support from the National Physical Laboratory, has been using this sophisticated system to analyse and develop simulants of the leaf layer in its laboratory. This has been used to help it in the development of its plasma track cleaning system. Having discovered this innovative technology which can analyse any chemical compound, PlasmaTrack has been able to characterise the key components in the leaf layer. It is proposing to develop the technology specifically tuned to railway leaf layer and other low adhesion contaminant signatures. This project will further optimise it for the railway environment; by limiting the scanning to the specific signatures will enable more rapid analysis which will lead to a product for fast diagnosis track side and on-board sensing to aid with driver feed-back and braking control. With the number of passenger journeys doubling over the last 20 years, the UK rail network is at maximum capacity. This sensing system will lead to the ability to run more trains on the UK network with Closer Running through predictable and optimised braking. This First of A Kind technology is key to unlocking the unrealised capacity of the UK Rail Network.