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Dynamic modeling of the gear vibration is a useful tool to study the vibration response of a geared system under various gear parameters and operating conditions. An improved understanding of vibration signal is required for early detection of incipient gear failure to achieve high reliability. However, the aim of this work is to make use of a 6-degree-of-freedom gear dynamic model including localized tooth defect for early detection of gear failure. The model consists of a gear pair, two shafts, two inertias representing load and prime mover and bearings. The model incorporates the effects of time-varying mesh stiffness and damping, backlash, excitation due to gear errors and modifications. The results indicate that the simulated signal shows that as the defect size increases the amplitude of the acceleration signal increases. The crest factor and kurtosis values of the simulated signal increase as the fault increases.

The early detection of incipient failure in a mechanical system is of great practical importance as it permits scheduled inspections without costly shutdowns and indicates the urgency and locations for repair before a system incurs catastrophic failure. However, in this work a new technique for processing vibration data to quantify the level of damage, cracks only, in a gear system. The technique consists of a nonlinear numerical optimization. The optimization uses a dynamic model of the gear mesh used in vehicle gearbox and forms an estimate of both time-varying and frequency-varying mesh stiffness that best corresponds to the given set of vibration data. The procedure developed in this study can be applied as a part of either an onboard machine health monitoring system or a health diagnostic system used in the regular maintenance.