Whilst vibration analysis of planetary gearbox faults is relatively well established, the application of Acoustic Emissions (AE) to this field is still in its infancy. For planetary-type gearboxes it is more challenging to diagnose bearing faults due to the dynamically changing transmission paths which contribute to masking the vibration signature of interest. The present study is aimed at developing a series of signal processing procedures to reduce the effect of background noise whilst extracting the fault feature from AE and vibration signatures. Three signal processing techniques including an adaptive filter, spectral kurtosis and envelope analysis, were applied to AE and vibration data acquired from a simplified planetary gearbox test rig with a seeded bearing defect. The results show that AE identified the defect earlier than vibration analysis irrespective of the tortuous transmission path.
|Title of host publication||Advances in Condition Monitoring of Machinery in Non-Stationary Operations|
|Number of pages||14|
|Publication status||E-pub ahead of print - 17 Jul 2015|
|Name||Applied Condition Monitoring|