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Chinese Journal of Ship Research, Volume. 17, Issue 6, 88(2022)

Ship propulsion shafting bearing fault diagnosis based on holographic SDP similarity visual recognition

Zhiqiang LIAO and Baozhu JIA
Author Affiliations
  • Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China
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    [3] LIAO Z Q, SONG X W, JIA B Z et al. Bearing fault feature enhancement and diagnosis based on statistical filtering and 1.5-dimensional symmetric difference analytic energy spectrum[J]. IEEE Sensors Journal, 21, 9959-9968(2021).

    [10] XU L, CHATTERTON S, PENNACCHI P et al. A tacholess order tracking method based on inverse short time fourier transform and singular value decomposition for bearing fault diagnosis[J]. Sensors, 20, 6924(2020).

    [11] FAN H W, SHAO S J, ZHANG X H et al. Intelligent fault diagnosis of rolling bearing using FCM clustering of EMD-PWVD vibration images[J]. IEEE Access, 8, 145194-145206(2020).

    [12] WANG H, XU J W, YAN R Q et al. A new intelligent bearing fault diagnosis method using SDP representation and SE-CNN[J]. IEEE Transactions on Instrumentation and Measurement, 69, 2377-2389(2020).

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    Zhiqiang LIAO, Baozhu JIA. Ship propulsion shafting bearing fault diagnosis based on holographic SDP similarity visual recognition[J]. Chinese Journal of Ship Research, 2022, 17(6): 88

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    Paper Information

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    Received: Sep. 3, 2021

    Accepted: --

    Published Online: Mar. 26, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02513

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology