A Study on Multicomponent Failure Interactions Within a Planetary Gearbox of a Wind Turbine

摘要

Condition-based maintenance methods are being used in expensive and crucial equipment thereby provides the maintenance team with the information required without actually dismantling or shutting down the machine. For example, wind turbines and large stationary gearboxes use this method to predict the health of the system, thereby avoiding the possibility of a catastrophic failure. Studies related to fixed axis gearbox are more when compared to studies related to planetary gearbox. Multiple studies related to single component fault diagnosis have been carried out over the past years. However, studies on multicomponent fault detection are comparatively less. Nevertheless, the practical application requires multicomponent fault diagnosis technics to reliably predict failures as the machinery used would have more than one point of failure. This paper reports a study on multi-fault diagnosis conducted in a scaled-down model of a wind turbine planetary gearbox subjected to stationary loading. A uniaxial piezoelectric accelerometer was used to acquire vibration data which was then processed with an algorithm after the features were extracted using statistical feature extraction. The power spectral density was analysed to interpret the results obtained.