Funder
The National Natural Science Foundation of China Key Support Project
The National Natural Science Foundation of China
the Fellowship of China Postdoctoral Science Foundation
the Fellowship of Heilongjiang Province Postdoctoral Science Foundation
Outstanding Doctoral Dissertation Funding Project of Heilongjiang Province
Publisher
Springer Science and Business Media LLC
Reference33 articles.
1. AlShorman, O., Alkahatni, F., Masadeh, M., et al. (2021). Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study. Advances in Mechanical Engineering, 13(2), 1687814021996915.
2. AlShorman, O., Irfan, M., Saad, N., et al. (2020). A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor. Shock and vibration, 2020, 1.
3. Chen, T., Kornblith, S., & Norouzi, M. (2020). A simple framework for contrastive learning of visual representations. International conference on machine learning (pp. 1597–1607). PMLR.
4. Chen, J., Yang, B., & Liu, R. (2022). Self-supervised Contrastive Learning Approach for Bearing Fault Diagnosis with Rare Labeled Data. 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) (pp. 1190–1194). IEEE.
5. Dong, H., Xun, L., & Ma, W. (2022). Fault diagnosis of aeroengine fan based on generative adversarial network and acoustic features. Aerospace Systems, 5, 1–9.
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