Train tracking and train condition monitoring by Distributed Acoustic Sensing

In this technical contribution we present the potential of Distributed Acoustic Sensing (DAS) for monitoring railway tracks and rolling stock. DAS is a measuring technique that allows to sense pressure changes in an optical fiber through sensing the Rayleigh backscatter of injected light pulses. The optical fibers used for sensing are an integral part of modern railway infrastructure, therefore installing a DAS system does not require investment in new infrastructure. We present algorithms for train tracking as well as for train condition monitoring. Both of these applications are at the core of railway safety and therefore immediately relevant for infrastructure management. The presented algorithms are evaluated on more than 5 hours of data recorded along two different railway tracks in Austria. The goal of this contribution is to show the currently unused potential of existing optical fibers along railway infrastructure.