ETR – Eisenbahntechnische Rundschau | Ausgabe International/2017

Predictive analytics for railway – monitoring and maintaining point health with smart sensors and AI

September 2017 | Thomas Böhm, Natalie Weiß

Points (switches and crossings) are amongst the essential components for efficient and flexible railway operations. Point failures are closely associated with delays in train schedules, which is why infrastructure managers are relying more and more on continuous monitoring using sensors. Innovative IIoT sensors in combination with smart analytical systems facilitate holistic insights into point condition. KONUX GmbH uses this system solution to monitor, analyse and predict the health status of railway points. It combines IIoT hardware with artificial intelligence and enables infrastructure providers such as Deutsche Bahn to make predictive maintenance a reality. Point failures are known to disrupt railway operations and are among the principal causes of train delays and high maintenance costs. For that reason, infrastructure managers are trusting more and more in sensors to perform continuous monitoring in the field. By combining these measuring devices with analytical systems based on artificial intel-ligence, it is possible to arrive at a holistic view of the condition of points and to make predictive maintenance a reality.