Rolling element bearing fault detection: Combining energy operator demodulation and wavelet packet transform

Rolling element bearing vibration signal is a modulated signal, and the existence of modulation increases the difficulty in bearing fault detection. Hilbert transform has been widely used in signal demodulation. However, the endpoint effect often makes the result unsatisfactory. Further, bearing vibration signals are usually polluted by various noises at low frequency, and the analysis of high frequency can be more effective for bearing fault feature extraction. This paper proposes an improved method that combines the energy operator demodulation and the dual reconstruction scheme in wavelet packet transform. A fan bearing test rig is established and the vibration signals collected from this test rig are used to validate the proposed method. The analysis results show that the proposed method has a good frequency resolution.