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- W2513528654 abstract "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." @default.
- W2513528654 created "2016-09-16" @default.
- W2513528654 creator A5001648352 @default.
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- W2513528654 date "2016-11-01" @default.
- W2513528654 modified "2023-10-17" @default.
- W2513528654 title "A Morphological Hilbert-Huang Transform Technique for Bearing Fault Detection" @default.
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- W2513528654 doi "https://doi.org/10.1109/tim.2016.2598019" @default.
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