Gear Fault Detection Using Angle Domain Average and Hilbert-Huang Transform Phase Map

Varying speed machinery fault diagnosis is more difficult due to non-stationary machine dynamics and vibration. A new approach to fault diagnosis of bearing under running up based on angle domain average and Hilbert-Huang transform (HHT) phase map is presented. The non-stationary vibration signals are transformed from the time domain transient signal to angle domain stationary one using order tracking. Empirical mode decomposition (EMD) can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs). Hilbert transform can track the instantaneous amplitude and instantaneous frequency of the intrinsic mode functions at any instant. The experimental results show that average domain average and Hilbert-Huang transform phase map can effectively diagnosis the faults of the gear crack.