Research on fault feature enhancement and diagnosis of marine water pump bearing based on BM-MTF

Zhiqiang LIAO; Zhende HUANG; Xuewei SONG; Guanlong LIANG; Baozhu JIA

doi:10.19693/j.issn.1673-3185.04014

Chinese Journal of Ship Research, Volume. 20, Issue 2, 56(2025)

Research on fault feature enhancement and diagnosis of marine water pump bearing based on BM-MTF

Zhiqiang LIAO^1,2,3, Zhende HUANG¹, Xuewei SONG^1,2,3, Guanlong LIANG¹, and Baozhu JIA^1,2,3

Author Affiliations

¹Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China

²Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province, Zhanjiang 524088, China

³Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang 524088, China

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References(5)

[10] LI Q F, ZHOU Y X, TANG G et al. Early weak fault diagnosis of rolling bearing based on multilayer reconstruction filter[J]. Shock and Vibration, 2021, 6690966(2021).

[11] KHODJA A Y, GUERSI N, SAADI M et al. Rolling element bearing fault diagnosis for rotating machinery using vibration spectrum imaging and convolutional neural networks[J]. The International Journal of Advanced Manufacturing Technology, 106, 1737-1751(2020).

[13] WANG M J, WANG W J, ZHANG X N et al. A new fault diagnosis of rolling bearing based on Markov transition field and CNN[J]. Entropy, 24, 751(2022).

[16] [16] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning f image recognition[C]Proceedings of the 2016 IEEE Conference on Computer Vision Pattern Recognition. Las Vegas: IEEE, 2016: 770−778. doi: 10.1109CVPR.2016.90.

[17] RAJ K K, KUMAR S, KUMAR R R et al. Enhanced fault detection in bearings using machine learning and raw accelerometer data: a case study using the case western reserve university dataset[J]. Information, 15, 259(2024).

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Zhiqiang LIAO, Zhende HUANG, Xuewei SONG, Guanlong LIANG, Baozhu JIA. Research on fault feature enhancement and diagnosis of marine water pump bearing based on BM-MTF[J]. Chinese Journal of Ship Research, 2025, 20(2): 56

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Paper Information

Category: Ship Intelligent O&M, and Fault Diagnosis

Received: Jun. 18, 2024

Accepted: --

Published Online: May. 15, 2025

The Author Email:

DOI:10.19693/j.issn.1673-3185.04014

Topics

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