RailPower technology monitors the vibrations created when a train travels along the tracks
We have combined breakthrough materials engineering with the latest machine learning to produce a low power sensor for rail analytics. Our system takes the vibration from the rail and analyses it to forecast failure. Importantly we can recognise failure much earlier than current systems and can uniquely identify the failure mechanism at play. Our approach not only warns of degradation in track health but simultaneously determines the cause of the change of health. The system uses a passive monitoring approach coupled with machine learning to provide unprecedented insights into the health of the track.
Analyzing these vibrations allows for the deterioration of track components to be detected and reported to infrastructure managers
