A Morphological Hilbert-Huang Transform Technique for Bearing Fault Detection

作者：Osman Shazali; Wang Wilson

来源：IEEE Transactions on Instrumentation and Measurement, 2016, 65(11): 2646-2656.

DOI：10.1109/TIM.2016.2598019

• Bearing fault detection
• Hilbert-Huang transform
• morphology filtering

Most rotary machinery imperfections are related to defects in rolling element bearings. Unfortunately, reliable bearing fault detection still remains a challenging task, especially when bearing defect-related features are nonstationary. A new morphological Hilbert-Huang (MH) technique is proposed in this paper for incipient bearing fault detection. In the proposed MH technique, a new linearity measure method is suggested to demodulate characteristic feature functions, and a mathematical morphological filter is proposed to reduce impedance effect of the measured vibration signal to improve fault detection accuracy. The effectiveness of the proposed MH technique is verified by a series of experimental tests corresponding to different bearing conditions.

• 出版日期2016-11