期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 32, 期 -, 页码 200-215出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2012.05.008
关键词
Condition based maintenance; Negative log likelihood transform; Gaussian mixture model; Synchronous averaging
This 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 likelihood (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 non-linear, non-stationary machine response signals. (C) 2012 Elsevier Ltd. All rights reserved.
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