A New Hilbert-Huang Transform Technique for Fault Detection in Rolling Element Bearings

Abstract

Rotary machinery is commonly used in various industries. Most rotating machinery imperfections are related to defects in rolling element bearings. Unfortunately, reliable bearing fault detection still remains a challenging task, especially when bearing defect is at its initial stages, and the defect-related features are nonstationary. A new enhanced Hilbert–Huang transform (HHT) technique, eHT, is proposed in this chapter for incipient bearing fault detection. In the proposed eHT technique, the vibration signal is firstly denoised to reduce impedance effect of the measured vibration signal and enhance signal-to-noise ratio. Then, a morphological filter is proposed using a linearity measure method to demodulate characteristic features from the HHT, and to improve fault detection accuracy. The effectiveness of the proposed eHT technique is verified analytically and experimentally by a series of tests corresponding to different bearing conditions.