Schmidt, StephanHeyns, P.S. (Philippus Stephanus)Gryllias, Konstantinos C.2018-07-272019-02Schmidt, S., Heyns, P.S. & Gryllias, K.C. 2019, 'A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions', Mechanical Systems and Signal Processing, vol. 116, pp. 40-61.0888-3270 (print)1096-1216 (online)10.1016/j.ymssp.2018.06.026http://hdl.handle.net/2263/66003Performing condition monitoring on critical machines such as gearboxes is essential to ensure that the machines operate reliably. However, many gearboxes are exposed to variable operating conditions which impede the condition inference task. Rolling element bearing component failures are important causes of gearbox failures and therefore robust bearing diagnostic techniques are required. In this paper, a rolling element bearing diagnostic methodology based on novelty detection is proposed for machines operating under variable speed conditions. The methodology uses the wavelet packet transform, order tracking and a feature modelling approach to generate a diagnostic metric in the form of a discrepancy measure. The probability distribution of the diagnostic metric, statistically conditioned on the corresponding operating conditions is estimated, whereafter the condition of the rolling bearing element is inferred. The rolling element bearing diagnostic methodology is validated on data from a phenomenological gearbox model and two experimental datasets.en© 2018 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Mechanical Systems and Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Mechanical Systems and Signal Processing, vol. 116, pp. 40-61. 2019. doi : 10.1016/j.ymssp.2018.06.026.Bearing diagnosticsTime variable speed conditionsNovelty detectionDiscrepancy analysisProbabilistic approachRoller bearingsProbability distributionsGearsCondition monitoringEngineering, built environment and information technology articles SDG-08SDG-08: Decent work and economic growthEngineering, built environment and information technology articles SDG-09SDG-09: Industry, innovation and infrastructureEngineering, built environment and information technology articles SDG-12SDG-12: Responsible consumption and productionEngineering, built environment and information technology articles SDG-13SDG-13: Climate actionPostprint Article