A fault feature extraction method for rotor start-up or slowdown process based on fractional Fourier transform and holospectrum

The vibration signal of the rotor start-up or slowdown process can be regarded as a dynamic response to a wide frequency range excitation, which contains more information than steady state vibration. As such, it deserves more attention to extracting fault features by the analysis of rotor start-up or slowdown process. In light of the defect that the analysis of conventional start-up or slowdown process applying STFT to obtain the amplitude and phase will lose transient information, a method based on fractional Fourier transform and holospectrum is proposed. In this method, amplitude and phase can be directly obtained from the complex envelop of each order component, so it can preserve the transient information and eliminate the average effect of STFT. In this paper, amplitudes and phases of the vibration from two perpendicular directions of a rotor section were obtained. A holo-watefall curve was plotted according to the holospectrum theory, then fault feature extraction was fulfilled. The experimental results show that the method can effectively extract the typical fault feature of the rotor and has strong ability to distinguish typical faults.