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

Zhiqiang LIAO; Baozhu JIA

doi:10.19693/j.issn.1673-3185.02513

Journals >Chinese Journal of Ship Research >Volume 17 >Issue 6 >Page 88 > Article

Chinese Journal of Ship Research
Vol. 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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DOI: 10.19693/j.issn.1673-3185.02513 Cite this Article

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 Copy Citation Text

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References

[3] Z Q LIAO, X W SONG, B Z JIA et al. Bearing fault feature enhancement and diagnosis based on statistical filtering and 1.5-dimensional symmetric difference analytic energy spectrum. IEEE Sensors Journal, 21, 9959-9968(2021).

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

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

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

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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