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.

KEYWORDS:

• Condition monitoring
• IoT
• Railways fault detection
• Sensors
• Vibration analysis

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Shridhar Padhi

Sridhar H Padhi completed BE in mechanical engineering from Pillai HOC College of Engineering and Technology and is working in the automotive industry as an inventory control officer. Email: [email protected]

Mansi Subhedar

Mansi Subhedar completed BE (E & TC), ME (Electronics Engineering), and PhD in electronics engineering from RTMN University, Nagpur. She is working as an associate professor at Pillai HOC College of Engineering and Technology, Rasayani, Maharashtra, India. She has more than 17 years of teaching experience. She has published more than 43 papers in peer-reviewed international journals and conferences. She is also a reviewer for reputed international journals and was a technical program committee member for reputed conferences. She is a life member of ISTE, IETE, IE, and CSI. Her research interests include cyber security, next-generation networks, and artificial intelligence.

Saikiran Behra

Saikiran P Behera completed BE in electronics and telecommunication engineering from Pillai HOC College of Engineering and Technology. Currently, he is working as a hardware design engineer at Saraca Solutions. Email: [email protected]

Tejesh Patil

Tejesh Patil completed BE in mechanical engineering from Pillai HOC College of Engineering and Technology and is working in the automotive industry as an inventory control officer. Email: [email protected]