A Bearing Fault Diagnosis Method Based on VMD-HPE

Author:

Huang WanqingORCID,Chen Yang,Chen Yongqi,Zhang Tao,Yu Feiyu,Mao Xiaoyan

Publisher

Springer Nature Switzerland

Reference31 articles.

1. Duo, M., Ji, G., H, Zhu, H.: Bearing fault diagnosis based on VMD noise reduction and CNN. Noise Vibr. Control 14(05), 155–160(2021)

2. Zhang, Y.P., Zhang, P., Wang, H.: Intelligent identification of early bearing faults based on dual-time domain weak fault feature enhancement. J. Mech. Eng. 52(21), 96–103 (2016)

3. Zheng, J., Pan, H., Qi, X.: Composite hierarchical fuzzy entropy and its applications to rolling bearing fault diagnosis. China Mech. Eng. 27(15), 2048–2055 (2016)

4. Zheng, J., Dai, J., Zhu, S.: Improved multi-scale fuzzy entropy-based rolling bearing fault diagnosis method. Vibr. Testing Diag. 38(5), 929–934 (2018)

5. Chen, D., Zhang, Y., Yao, C.: Fault diagnosis based on FVMD multiscale alignment entropy and GK fuzzy clustering. J. Mech. Eng. 54(14), 16–27 (2018)

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1. Life prediction method of rolling bearing based on CNN-LSTM-AM;Journal of Vibroengineering;2024-05-23

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