Public Funding for Balfour Beatty Rail Limited

This project will demonstrate a solution which takes time based data in close to real time and broadcasts off measurment trains ito a cloud and (in parallel) the facility for a measurement train to be managed remotely (whilst being hauled by a manned traction unit), i.e. the operator can be in any remote centre. One operator team can then manage many measurement vehicles around the world. Data quality from unmanned vehicles will improve, crew costs reduced and data access improved. Analysis will be carried out in the cloud; more than one analysis can be used, and the results distributioned. Fault reports, statistics and alerts are taken from the cloud by users with mobile Apps or office systems. More than one display tool can use the data and the users can be anywhere in the world; in an office or on the line side. This combination of features, as well as improving the efficiency of the national railways has the potential to change the way in which this technology is delivered and will allow access to thie type of technology for smaller organisations such as tram and light rail infrastructure operators. It is envisaged that the creation of this rich dataset, and controlled access to it, will act as a stimulus for future system and product development from both within and outside the consortium.

Precise train positioning is key to the vision for an innovative railway presented by the Rail Capability Delivery Plan 2017\. GPS is problematic for rail and currently the industry relies heavily on signs, transponders and balises in the track to locate a train at a specific point on its path. These are expensive to install and maintain. Each new application that needs them increases the complexity and management burden of the infrastructure. This project takes a completely new, lower cost, approach. Adapting recent developments in technology for autonomous cars, a train will be able to locate itself without needing any infrastructure equipment. Instead of a physical transponder or balise in the track, the system creates a virtual 'Video Balise' - Valise, which is stored in a forward facing camera mounted in the windscreen. The Valise is 'read' as the camera recognises that the train is passing the stored location. The Valise will unlock the potential for many high value applications which cannot economically be delivered with today's expensive physical positioning infrastructure. The project is being delivered by RDS in collaboration with Nottingham Scientific Ltd, Omnicom Balfour Beatty, First Group and Network Rail. RDS will develop the Valise technology and integrate it with its Video Train Positioning System (VTPS) to provide an autonomous low cost system suitable for deployment in service trains. The technology will be trialled in a real-time demonstrator on a First Group train, integrated with the RDS Driver Support System (DSS). The demonstator will show how the technology would be deployed for platform stopping and 'virtual' temporary speed restrictions. Balfour Beatty and Network Rail will validate the performance of the Valise against existing positioning systems and demonstate its use for remote monitoring and survey applications. NSL will bring its R&D experience in 'virtual balise' technology using satellite postioning (GNSS). With this, the project team will develop a safety approach for integerating GNSS and video virtual balises in order to realise a dependable virtual balise capable of use in safety related applications.

RailSAFT aims to develop an affordable and reliable Non-Destructive Testing (NDT), automated ultrasonic inspection technique for high manganese, wear-resistant steel rail crossover points (Frogs). These are commonly used on the UK and global rail networks and are susceptible to in-service cracking due to high impact loads from rolling stock. The early detection of cracks at safety critical locations in rail is vital because they can propagate in service and may ultimately lead to failure with potentially catastrophic consequences. Flaws detected at an early stage in their growth cycle can be monitored/ assessed and repaired before risk of failure. Modelling & simulation methods will be used to develop algorithms for the precise control of the ultrasonic beam generated by phased array probes that are to be developed. Synthetic Aperture Focusing (SAFT) together with advanced signal processing will enhance Signal Noise Ratios thus improving defect detection in cast Frog rail sections.