GB Railfreight Successfully Trials Brake Monitoring IoT System

GB Railfreight Successfully Trials Innovative Brake Monitoring IoT System

Collaborating with Icomera, DG8 and SENSEi Networks, GB Railfreight (GBRf) has tested a first-of-its-kind solution for monitoring wheel and brake issues.

The environmental and economic benefits of transporting goods by rail are well understood. Research from Rail Partners[1] shows that rail freight has a considerable environmental advantage over road freight in the UK, where a single freight train can perform the work of 129 heavy goods vehicles (HGVs) while producing 76% less CO2 per tonne. The report found that with the right support, rail freight has the potential to boost the UK economy by £5.2bn annually by 2050, while reducing road decongestion and improving air quality.

Given the importance of rail freight in supporting the pursuit of universal goals, any improvements to the safety and efficiency of its operation deliver real value.

The Challenge

One prominent issue in the operation of rail freight occurs when the wheels of the wagon are not freely turning. This can be caused by axle or brake issues due to mechanical failure, or human error – failing to release the handbrake for instance. This can cause wheel flats, damage to the infrastructure, and, in the worst case, derailments; in fact, of the 500 freight rail derailments that occur on average in Europe each year, approximately 10% are caused by issues relating to wheel and brake failure[2]. The cost of the associated network disruption, not to mention the cost of wagon and infrastructure repairs, is significant.

GB Railfreight (GBRf), in partnership with Icomera, its design and engineering team DG8, and IoT platform developer SENSEi Networks, looked to address this issue through a combination of new, emerging technologies, and technologies used in other industries refactored for rail freight.

GBRf’s main requirement was the ability to immediately inform the driver of an issue with a wagon within the train consist before it left the depot.​

The solution needed to i) monitor the brakes​, ii) identify out of tolerance events​, and iii) communicate an alert to the driver​.

The freight wagons offered no power source for onboard equipment, and there was no electrical connection between each wagon or locomotive. This meant the solution needed to operate independently from a power and communication perspective.

The Solution Concept

Icomera, DG8 and SENSEi proposed a concept solution for GB Railfreight whereby each wagon is instrumented with battery-powered sensors. DG8 advised the project on sensor types and placement, and offered insights into how the data generated could be interpreted.

These sensors monitor:​

  • Handbrake on/off​
  • Brake pipe pressure
  • ​Brake cylinder pressure 

The sensors on each wagon communicate via a long distance, secure, low power wireless network with a bespoke implementation of SENSEi’s IoT Platform-as-a-Service, which is hosted as a virtual machine on Icomera’s mobile Internet connectivity and applications router.

SENSEi’s platform filters and processes the received wagon data for each train consist locally. Status and out of tolerance alerts are then sent over the vehicle’s Icomera Wi-Fi hotspot to the drivers app running on a tablet in the locomotive’s cabin. This allows the driver to take action and receive feedback on the results of that action in real-time.

The status and out of tolerance alerts are also sent to a cloud hosted server, via the Icomera router which aggregates the connectivity of the available cellular networks along the route, feeding into reports for teams back at the operational control centre. The technology does not replace the teams performing vehicle pre-checks, rather it works hand-in-hand with them to improve the running of the rail network and create safer working conditions by reducing the number of avoidable incidents and the associated risky recovery work on the tracks further down the line.

From Concept to Live Train Trial

Icomera, DG8 and SENSEi conducted a bench test at GB Railfreight’s offices in Peterborough, to demonstrate the feasibility of the concept. A static train test of the low power wireless network was successfully completed in October 2022, proving that it would cover the full length of the freight train consist.

The solution was then installed on one GBRf Class 66 Locomotive at GBRf’s depot in Doncaster, and on two wagons at GBRf’s depot in March, Cambridgeshire, ahead of being deployed on an in-service consist for live trials between East Midlands Gateway rail freight terminal and Seaforth over a four-week period in June 2023.

The trial successfully demonstrated a world-first – No known method previously existed for delivering freight wagon brake sensor data to the driver in the locomotive wirelessly via a closed system.

All parties involved are now considering the next phase of solution development and further collaborative trials in rail freight environments.

David Golding, Asset Director, GB Railfreight , said:

“Working with our trusted industry partners, we have proven the concept of a first-of-its-kind application in the rail sector. GBRf is really proud to be leading the freight industry by developing these innovative solutions to reduce incidents relating to wheel and brake issues.”

Peter Kingsland, SVP, Icomera UK, said:

“Rail freight operators are rightly paving the way for digitally driven solutions to mitigate risks as the freight industry grows. Connecting drivers and the engineering teams that support them to real-time trainborne sensor data is a natural step towards a safer and more efficient rail network for all users.”

Damon Thomas, Chief Executive Officer, SENSEi Networks Limited, said:

“The utilisation of low-power sensors, long range, wireless networking and edge intelligence is enabling long sought ambitions for autonomous monitoring and real-time alerting to be realised in the freight rail sector, fulfilling the potential for significant improvements to operational efficiency, cost and safety.”

This article was originally published by Icomera.

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