Monitoring tooth profile faults in epicyclic gearboxes using synchronously averaged motor currents: Mathematical modeling and experimental validation. (1st February 2017) - Ottewill, J.R.; Ruszczyk, A.; Broda, D.
Abstract: Time-varying transmission paths and inaccessibility can increase the difficulty in both acquiring and processing vibration signals for the purpose of monitoring epicyclic gearboxes. Recent work has shown that the synchronous signal averaging approach may be applied to measured motor currents in order to diagnose tooth faults in parallel shaft gearboxes. In this paper we further develop the approach, so that it may also be applied to monitor tooth faults in epicyclic gearboxes. A low-degree-of-freedom model of an epicyclic gearbox which incorporates the possibility of simulating tooth faults, as well as any subsequent tooth contact loss due to these faults, is introduced. By combining this model with a simple space-phasor model of an induction motor it is possible to show that, in theory, tooth faults in epicyclic gearboxes may be identified from motor currents. Applying the synchronous averaging approach to experimentally recorded motor currents and angular displacements recorded from a shaft mounted encoder, validate this finding. Comparison between experiments and theory highlight the influence of operating conditions, backlash and shaft couplings on the transient response excited in the currents by the tooth fault. The results obtained suggest that the method may be a viable alternative or complement to more traditional methods for monitoring gearboxes. However, general observations also indicate that further investigations into the sensitivity and robustness of the method would be beneficial. Highlights: Experiments are conducted on an epicyclic gearbox with a seeded planet tooth fault. A low DOF model of an epicyclic gearbox with tooth profile faults is introduced. Simulation shows that fault signatures appear in the currents of a connected motor. The synchronous average of currents method is updated for epicyclic gearboxes. Experiments and simulations show that the method can extract planet fault signatures.