The dynamic response of gear transmissions holds essential information for the recognition of an incipient fault and its propagation. A realistic and validated dynamic model is used to predict the vibration regime of gear transmissions. A great virtue of a model is the ability to examine each phenomenon separately and isolate its contribution to the dynamic response. This paper presents the analysis of local tooth faults in spur gear transmissions. The model considers the nonlinear behavior of the gear mesh stiffness, integrating the geometric profile errors of the gears. The scattering in the data, which is generated by the random factor of the simulated surface roughness, simulates the reality better than data of an ideal profile. The ability to determine what is possible to monitor for each surface roughness is not trivial at all. It cannot be achieved experimentally, due to the immense span of cases to consider. The thoughtful insights from the simulated vibration signatures were drawn from a set of features, which made it possible to examine the detection capability in different operating conditions including speed, load and surface roughness. This comprehensive analysis may yield the ability to fit a robust and sensitive monitoring process for different operation conditions and faults. Moreover, investigating by the use of simulations shade a new light on understanding the physical phenomena. A matrix of hundreds of simulations was used to assess the capability to discriminate between health status of the gear and detectability of different fault severities.

 Keywords: Gear Model, Vibration Signature, Condition Monitoring, Local Tooth Fault, Spur Gear, Gear Diagnostics, Statistical Analysis

 

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