Typical railway wheelsets consist of wheels, axle and axle bearings. Faults can develop on any of the aforementioned\ncomponents, but the most common are related to wheel and axle bearing defects. The continuous increase in train\noperating speeds means that failure of an axle bearing can lead to serious derailments, causing loss of life and severe disruption\nin the operation of the network, damage to the track and loss of confidence in rail transport by the general public.\nThe rail industry has focused on the improvement of maintenance and remote condition monitoring of rolling stock\nto reduce the probability of failure as much as realistically possible. Current wayside systems such as hot axle box detectors\nand acoustic arrays may fail to detect defective bearings. This article discusses the results of wayside high-frequency\nacoustic emission measurements performed on freight rolling stock with artificially induced damage in axle bearings in\nLong Marston, UK. Time spectral kurtosis is applied for the analysis of the acoustic emission data. From the results\nobtained, it is evident that time spectral kurtosis is capable of distinguishing the axle bearing defects from the random\nnoises produced by different sources such as the wheelââ?¬â??rail interaction, braking and changes in train speed.
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