Chinese Journal of Ship Research, Volume. 20, Issue 2, 20(2025)

Marine motor fault diagnosis based on CEEMDAN and BRECAN under strong noise conditions

Renjie ZHU1, Enzhe SONG2, Chong YAO2, and Yun KE2
Author Affiliations
  • 1College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China
  • 2Yantai Research Institute, Harbin Engineering University, Harbin 264000, China
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    References(20)

    [6] [6] TOLIYAT H A, NI S, CHOI S, et al. Electric machines: modeling, condition moniting, fault diagnosis[M]. Boca Raton: CRC Press, 2017.

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    [24] [24] HU J, SHEN L, SUN G. Squeezeexcitation wks[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. Las Vegas: IEEE, 2018: 7132−7141.

    [25] [25] HU J, SHEN L, SUN G. Squeezeexcitation wks[C]2018 IEEECVF Conference on Computer Vision Pattern Recognition. Salt Lake City, UT, USA:IEEE, 2018.

    [26] [26] WANG Q L, WU B G, ZHU P F et al. ECA: efficient channel attention f deep convolutional neural wks[C]2020 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR). Seattle, WA, USA: IEEE, 2020: 11531−11539.

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    Renjie ZHU, Enzhe SONG, Chong YAO, Yun KE. Marine motor fault diagnosis based on CEEMDAN and BRECAN under strong noise conditions[J]. Chinese Journal of Ship Research, 2025, 20(2): 20

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    Paper Information

    Category: Ship Intelligent O&M, and Fault Diagnosis

    Received: Jul. 15, 2024

    Accepted: --

    Published Online: May. 15, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.04059

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