Advanced diagnostics and anomaly detection for railroad safety applications: Using a wireless, IoT-enabled measurement system

Accidents involving trains have been attributed to degraded track and rolling stock. Detection of anomalies that indicate degraded condition is critical. In this paper we present results of an experiment using a sensor system mounted on one of the 110 boxcars on a train on a high-tonnage loop test track. The sensor was a microelectromechanical systems (MEMS) triaxial accelerometer module mounted on the hubs of the wheels of the boxcar. Sensor data were wirelessly transmitted to a collection gateway hub mounted inside the boxcar. The purpose of the experiment was to evaluate the feasibility of using a rotating triaxial accelerometer-based system designed to be mounted inside of a helicopter gearbox, and to use the system to detect anomalies in railroad tracks and rolling stock as well as anomalies of bearings, rotating shafts and gears. The results confirm it is feasible to identify, locate, and characterize such anomalies.