IoT Based Condition Monitoring for Railway Track Fault Detection in Smart Cities

Abstract

The railways have the busiest and biggest networks in the world and play a key role in driving the economic growth of any country. The railways still follow the traditional method of manual inspection which is very time-consuming and not economical. The proposed work demonstrates maintenance i.e. condition monitoring based fault detection. In this method, the system will measure accelerations at the train bogie and can find railway track longitudinal profile, and rail condition from the response provided by inertial sensors mounted on the in-service train. The vertical and lateral accelerations of railway bogies are used to evaluate faults in railway tracks. A tachometer system and a map-matching algorithm are used to pinpoint the location of faults on tracks. This system will communicate these vibration messages wirelessly to a cloud service, which processes the data, and using knowledge of sensor location and vibration history the determination of the track condition is performed on a regular basis. This data is then conveyed to infrastructure managers in the form of alerts, thereby facilitating a condition-based maintenance approach equipped with IoT. The system can easily indicate the weak locations in the track that can be further analyzed in detail by the diagnostician. Thus, the system aids in tracking maintenance strategies and will reduce downtime. This condition-based maintenance system provides smart detection of faults as compared with traditional methods.