Abstract

Abstract Bearing temperature serves as an important metric used in identifying defective bearings in the rail industry. Current defect detection systems, such as the Hot Box Detectors (HBDs), are used to measure the temperature of freight car roller bearings. The HBD is a wayside device that utilizes a non-contact infrared sensor to determine the operating temperature of a railroad bearing as it passes over the HBD. Railroads analyze the data collected by HBDs to detect and flag defective bearings. If the operating temperature of a bearing surpasses a predetermined threshold, an emergency stop is initiated, and the bearing is removed from service and sent for inspection. One major drawback of HBDs is that they have been associated with many “false positives,” which has resulted in costly train stoppages and delays. To combat that, researchers have opted to use wireless onboard sensor devices mounted directly on the bearing adapter. One such device is the wireless onboard health monitoring system developed by the University Transportation Center for Railway Safety (UTCRS) that utilizes temperature and vibration sensors to detect the condition of rolling stock. However, because the device is affixed to the bearing adapter and not the bearing itself, the strategic placement of the temperature sensor on the adapter is crucial in minimizing the thermal lag associated with the heat transfer from the bearing to the location where the temperature is measured, as this will directly affect the accuracy of the readings. By conducting a transient heat transfer finite element analysis (FEA), the estimated time-lag and the temperature distribution within the bearing adapter can be determined. To validate the accuracy of the transient FEA model, the results were compared to data acquired from laboratory testing performed on the UTCRS dynamic bearing test rigs. The results obtained in this study can be used to identify optimal anchor points for the temperature sensors on the bearing adapter, and in turn, increase the proficiency of wireless onboard sensor devices in detecting defective components.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.