At present there are no existing bearing health monitoring systems capable of continuous monitoring and tracking of railroad bearings on freight cars. Current wayside equipment is used to garner intermittent bearing cup temperatures, which at times could be every 65 km (∼40 mi) or more. Such devices are not designed to provide continuous condition monitoring which would enable users to assess the rate of bearing health degradation and predict when a bearing will require service. To this end, IONX, LLC, a subsidiary of Amsted Rail, Inc., has developed low power Wireless Sensor Nodes (WSNs) which can be retrofitted to existing bearing adapters. The WSNs provide continuous monitoring of bearing temperatures as well as the current ambient temperature. Since the nodes are affixed to the bearing adapter surface, a correlation is necessary to estimate the bearing cup temperature using the measured adapter surface temperature. This paper describes research conducted at The University of Texas-Pan American (UTPA) to devise a reliable mathematical model to correlate both temperatures. Additionally, these wireless nodes are currently in use on ten railroad cars that are part of an Australian fleet. The nodes have been collecting data since March 2010. The acquired data was used to devise and test a series of metrics that can automatically detect distressed bearings and predict time to maintenance. The development of bearing health monitoring metrics and their use to assess bearings in the Australian fleet is also discussed in this paper.

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