Detecting a Cracked Rotor with HHT-based Time-Frequency Representation

During the Hilbert-Huang Transformation (HHT), time-series data are firstly decomposed into several components with different time scale (i.e. intrinsic mode function, IMF), using the empirical mode decomposition (EMD). Then, the Hilbert transformation is applied to every IMF. As a result, the HHT spectrum of the data is constructed. In this paper, the HHT-based time-frequency representation was used for fault detection of rotor crack. On the basis of explaining the HHT-based representation in details, a simulated deep crack in a rotor was researched using this method. Experimental results showed that the HHT-based method can correctly represent the phase-modulation phenomenon excitated by the torsional vibration from the deep crack, and effectively detect the crack fault, which implies great potential of the HHT-based time-frequency method in fault diagnosis of rotor system.