Heyns, T and Heyns, T and Godsill, SJ and De Villiers, JP and De Villiers, JP and Heyns, PS (2012) Statistical gear health analysis which is robust to fluctuating loads and operating speeds. Mechanical Systems and Signal Processing, 27. pp. 651-666. ISSN 0888-3270Full text not available from this repository.
Condition-based maintenance is concerned with the collection and interpretation of data to support maintenance decisions. The non-intrusive nature of vibration data enables the monitoring of enclosed systems such as gearboxes. It remains a significant challenge to analyze vibration data that are generated under fluctuating operating conditions. This is especially true for situations where relatively little prior knowledge regarding the specific gearbox is available. It is therefore investigated how an adaptive time series model, which is based on Bayesian model selection, may be used to remove the non-fault related components in the structural response of a gear assembly to obtain a residual signal which is robust to fluctuating operating conditions. A statistical framework is subsequently proposed which may be used to interpret the structure of the residual signal in order to facilitate an intuitive understanding of the condition of the gear system. The proposed methodology is investigated on both simulated and experimental data from a single stage gearbox. © 2011 Elsevier Ltd. All rights reserved.
|Uncontrolled Keywords:||Bayesian model selection Gear maintenance Residual analysis Statistical gear model|
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Unnamed user with email email@example.com|
|Date Deposited:||16 Jul 2015 13:26|
|Last Modified:||31 Jul 2015 23:59|