Fault feature extraction from the vibration signals in rotor start-up or slowdown processes based on order tracking and holospectrum

The vibration signal in start-up or slowdown processes can be regarded as a dynamic response to a wide frequency range excitation, which contains more information than steady state vibration signals. So it deserves more attention to extract fault feature from the signals collected in the start-up or slowdown processes of a rotor system. Aiming at the defect that a conventional start-up or slowdown process analysis applying STFT to get vibration amplitude and phase will usually lose transient information, a method based on Vold-Kalman filtering order tracking (VKF-OT) and holospectrum was proposed. By the method, the vibration amplitude and phase can be obtained directly from the complex envelop of each order component, so they can preserve the transient information well and get rid of the average effect of STFT. The amplitudes and phases of the vibrations in two perpendicular directions at a rotor section were measured and a holo-watefall curve was plotted according to the holospectrum theory. On this basis, the fault feature extraction and transient balancing can be fulfilled. The experiment results show that the method can extract the typical fault features of the rotor and the transient balancing can also be well achieved.