The effects of the operating conditions and tooth fault on gear vibration signature. (1st June 2021) - Bachar, Lior; Dadon, Ido; Klein, Renata; Bortman, Jacob
Highlights: Using validated realistic dynamic model of spur gear. The effects of the operating conditions on the vibration signature. The behavior of tooth faults in the vibration signature. Improving the detection capability based on the understanding of the physical phenomena. Abstract: The dynamic response of gear transmissions holds essential information for the recognition of faults in the system. A realistic nonlinear dynamic model is used to predict the vibration regime of spur gear transmissions. This model was validated experimentally for both healthy and damaged conditions. The model allows to simulate each combination of rotational speed, load and surface roughness, and to isolate its influence on the dynamic response. An experimental study would be limited due to the large amount of cases to consider. The simulated surface roughness enables a more realistic evaluation of the condition indicators robustness. The first part of the study examines the effects of the operating conditions, e.g. speed, load and surface roughness, on the vibration signature of a healthy gearbox. It was found that the levels at the gear mesh frequencies (GMF) have a strong dependency on speed and load. The energy of the frequency modulation (FM) sidebands depends mainly on speed but hardly affected by load. The second part of the study examines the manifestation of a single tooth face fault in the vibration signature. Based on the conclusions of the first part, the analysis was focused on the synchronous average spectrum and the difference signal. The investigation using hundreds of simulations shed a new light on the physical phenomena in the dynamic response - the fault's expression is amplified around the natural frequencies of the gears. Based on this insight, it was found that the analysis of the spectrum around the natural frequencies allows the detection of incipient faults that cannot be detected using the analysis of the difference signal. The understanding of the physical phenomena, based on the dynamic model, enabled the generalization of this new finding.