Early Warnings for failing Train Axle Bearings based on Temperature



Published Oct 2, 2017
M.F.E. Peters


By studying the temperature behavior of axle bearings both statistically and physically, the research and development (R&D) department of Netherlands Railways (NS) has successfully developed and implemented a health monitoring system for bearings. In an early stage of degradation, temperature deviations are detected and the level of severity of the degradation is identified through a decision tree. This method enables us to detect bearing failures one to three months earlier than any other method in use, in more than half of the cases. Different handling scenarios per type of temperature behavior have been designed in a way that minimizes impact on train service.

How to Cite

Peters, M. (2017). Early Warnings for failing Train Axle Bearings based on Temperature. Annual Conference of the PHM Society, 9(1). https://doi.org/10.36001/phmconf.2017.v9i1.2451
Abstract 170 | PDF Downloads 404



implementation, decision tree, bearing fault detection, temperature, PHM in Railways, rule-based classifier

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