Researching | Rolling bearing fault diagnosis method based on FSC-MPE and BP neural network

Chinese Journal of Ship Research, Volume. 16, Issue 6, 183(2021)

Rolling bearing fault diagnosis method based on FSC-MPE and BP neural network

Junfeng LIU¹, baoying DONG², Xiang YU³, and Haibo WAN³

Author Affiliations

¹College of Power Engineering, Naval University of Engineering, Wuhan 430033, China

²The 91278 Unit of PLA, Dalian 116041, China

³College of Naval Architecture and Ocean Engineering, Naval University of Engineering, Wuhan 430033, China

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[4] CHEN Y L, ZHANG P L. Bearing fault detection based on SVD and EMD[J]. Applied Mechanics and Materials, 184/185, 70-74(2012).

[12] GARDNER W A, BROWN W, CHEN C K. Spectral correlation of modulated signals: Part II-digital modulation[J]. Communications IEEE Transactions on, 35, 595-601(1987).

[13] ANTONI J, XIN G, HAMZAOUI N. Fast computation of the spectral correlation[J]. Mechanical Systems & Signal Processing, 92, 248-277(2017).

[17] [17] AZIZ W, ARIF M. Multiscale permutation entropy of physiological time series[C]International Multitopic Conference. IEEE, 2005.

[20] URBANEK J, BARSZCZ T, ANTONI J. A two-step procedure for estimation of instantaneous rotational speed with large fluctuations[J]. Mechanical Systems and Signal Processing, 38, 96-102(2013).

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Junfeng LIU, baoying DONG, Xiang YU, Haibo WAN. Rolling bearing fault diagnosis method based on FSC-MPE and BP neural network[J]. Chinese Journal of Ship Research, 2021, 16(6): 183

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Paper Information

Category: Marine Machinery, Electrical Equipment and Automation

Received: Oct. 28, 2020

Accepted: --

Published Online: Mar. 28, 2025

The Author Email:

DOI:10.19693/j.issn.1673-3185.02158

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