Heyns, TheoHeyns, P.S. (Philippus Stephanus)De Villiers, Johan Pieter2012-12-062012-12-062012-10T Heyns, PS Heyns & JP de Villiers, Combining synchronous averaging with a Gaussian mixture model novelty detection scheme for vibration based condition monitoring of a gearbox, Mechanical Systems and Signal Processing, vol. 32, pp. 200-215 (2012), doi: 10.1016/j.ymssp.2012.05.008.0888-3270 (print)1096-1216 (online)10.1016/j.ymssp.2012.05.008http://hdl.handle.net/2263/20646This paper investigates how Gaussian mixture models (GMMs) may be used to detect and trend fault induced vibration signal irregularities, such as those which might be indicative of the onset of gear damage. The negative log livelihood (NLL) of signal segments are computed and used as measure of the extent to which a signal segment deviates from a reference density distribution which represents the healthy gearbox. The NLL discrepancy signal is subsequently synchronous averaged so that an intuitive, yet sensitive and robust, representation may be obtained which offers insight into the nature and extent to which a gear is damaged. The methodology is applicable to nonlinear, non-stationary machine response signals.en© 2012 Elsevier. 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. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Mechanical Systems and Signal Processing, vol 32, October 2012, doi: 10.1016/j.ymssp.2012.05.008.Synchronous averagingNegative log likelihood transformGaussian mixture modelGearing -- DynamicsGearing -- VibrationGaussian measuresPostprint Article