Reliable condition indicators are necessary to perform effective diagnosis and prognosis. However, the vibration signals are often corrupted with non-Gaussian noise and rotating machines may operate under time-varying operating conditions. This impedes the application of conventional condition indicators. The synchronous average of the squared envelope is a relatively simple yet effective method to perform fault detection, fault identification and fault trending under constant and time-varying operating conditions. However, its performance is impeded by the presence of impulsive signal components attributed to impulsive noise or the presence of other damage modes in the machine. In this work, it is proposed that the synchronous median of the squared envelope should be used instead of the synchronous average of the squared envelope for gearbox fault diagnosis. It is shown on numerical and experimental datasets that the synchronous median is more robust to the presence of impulsive signal components and is therefore more reliable for estimating the condition of specific machine components.

Modal analysis of back-to-back planetary gear: experiments and correlation against lumped-parameter model

The operating cycle of planetary gear transmissions is composed by the run up regime, steady state regime with fixed speed and the run down regime. Run up and run down are one of the main non stationary excitations for planetary gearboxes. This paper investigates, in these two regimes, the dynamic behaviour of a special configuration of two stages planetary gear which are mounted back-to-back. A dynamic model is developed. The variability of speed in the run up and run down regimes is included in the model. The computation of the dynamic response shows that additional sidebands instability zones are generated. Using the Short Time Fourier Transform, an amplitude-frequency modulation is observed in the non stationary condition. An experimental study done on a back-to-back planetary gear test rig is conducted for validation of the mathematic model.