View Project

Norwegian AI Directory

Real-time condition and collision risk monitoring for railway infrastructure using fibre optic networks


Description:

The Rail-DAS project aims to exploit the free capacity of fibre optic communication cables currently being installed in the ground alongside the Bane NOR network, to listen for characteristic acoustic signatures of condition risk (generated as a train passes) and collision risk (generated by objects moving nearby the rails). At the heart of the concept lies Distributed Acoustic Sensing (DAS). DAS consists of a passive optical fibre, that can be 10s of km in length, and an “interrogator” box at one end. The interrogator sends laser pulses along the fibre, and a small amount of the light is scattered from each location along the fibre back to the interrogator. The optical path experienced by the backscatter is modulated by acoustic fields, allowing for disturbances to be spatially resolved to within a few meters along the entire length of the fibre. A profound advantage of distributed fibre optic technology is that the low-cost passive fibre itself functions as the sensor. Furthermore, in contrast to a large numbers of individual point sensors requiring individual power sources, a distributed fibre optic sensor requires power only at the interrogator end of the fibre. Unlike their electrical counterparts, fibre optic sensors are immune to electromagnetic interference, a valuable property for electrically powered railroads like in Norway. By the development and application of machine learning algorithms alongside DAS, Rail-DAS will allow for near-continuous condition and collision risk monitoring over the entire rail network, and allow for preventative maintenance and other interventions to be carried out before problems become critical. The main elements of Rail-DAS are: 1) Real-time, network wide detection and location of rail infrastructure damage using DAS 2) Real-time, network wide detection and location of rolling stock with wheel damage using DAS 3) Real-time, network wide detection and location of objects on the rail line using DAS


Project leader: Peter Thomas

Started: 2021

Ends: 2024

Category: Øvrige offentlige

Sector: Øvrige

Budget: 6550000

Institution: BANE NOR SF

Address: Hamar