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

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Predictive Maintenance in Dynamic Systems

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.

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Acknowledgments

This research was financially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), Bare Point Water Treatment Plant, and eMech Systems Inc., in Thunder Bay, ON, Canada.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Lakehead University, Thunder Bay, ON, Canada

    Shazali Osman

  2. Department of Mechanical Engineering, Lakehead University, Thunder Bay, ON, Canada

    Wilson Wang

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  1. Shazali Osman
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  2. Wilson Wang
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Correspondence to Wilson Wang .

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Editors and Affiliations

  1. Fuzzy Logic Laboratorium Linz-Hagenberg, Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz, Linz, Austria

    Edwin Lughofer

  2. Institute Mines-Telecom Lille Douai, Douai, France

    Moamar Sayed-Mouchaweh

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Osman, S., Wang, W. (2019). A New Hilbert-Huang Transform Technique for Fault Detection in Rolling Element Bearings. In: Lughofer, E., Sayed-Mouchaweh, M. (eds) Predictive Maintenance in Dynamic Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-05645-2_7

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  • DOI: https://doi.org/10.1007/978-3-030-05645-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05644-5

  • Online ISBN: 978-3-030-05645-2

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