Flexible iterative generalized demodulation filtering for the fault diagnosis of rotating machinery under nonstationary conditions

The health monitoring and diagnosis of rotating machinery under nonstationary conditions are still challenging due to the complex modulation characteristics and the interfering noises. In this paper, a novel flexible iterative generalized demodulation filtering method is proposed for the machinery fault diagnosis. First, the Hilbert transform is applied to the vibration signals to highlight the characteristic frequencies as well as their harmonics. Second, the phase functions used for mapping the interest frequencies are designed, and no matter how the speed varies, the time-varying frequencies of different signal segments with the same physical meaning are transformed into the same constant frequencies. Then, the filters are designed based on the introduced base frequency and the characteristic coefficients, and then the modulation rotating frequency, fault characteristic frequencies, and their harmonics are filtered. Finally, the demodulated signals are reconstructed and the health conditions are determined by the demodulated spectrums. The method is evaluated by the vibration signals of faulty rolling bearings and planetary gearboxes. The results demonstrate that the method can well reveal the fault-related frequencies and that the demodulated frequency values are not subject to the speed fluctuation profiles.