Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis
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DOI: 10.1016/j.ress.2023.109879
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- Zhao, Chao & Shen, Weiming, 2022. "Adaptive open set domain generalization network: Learning to diagnose unknown faults under unknown working conditions," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
- Ding, Ning & Li, Hulin & Xin, Qi & Wu, Bo & Jiang, Dan, 2023. "Multi-source domain generalization for degradation monitoring of journal bearings under unseen conditions," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Wang, Rui & Huang, Weiguo & Lu, Yixiang & Zhang, Xiao & Wang, Jun & Ding, Chuancang & Shen, Changqing, 2023. "A novel domain generalization network with multidomain specific auxiliary classifiers for machinery fault diagnosis under unseen working conditions," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
- Miao, Xingyuan & Zhao, Hong & Gao, Boxuan & Song, Fulin, 2023. "Corrosion leakage risk diagnosis of oil and gas pipelines based on semi-supervised domain generalization model," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
- Dong, Yutong & Jiang, Hongkai & Wu, Zhenghong & Yang, Qiao & Liu, Yunpeng, 2023. "Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Shi, Yaowei & Deng, Aidong & Deng, Minqiang & Xu, Meng & Liu, Yang & Ding, Xue & Bian, Wenbin, 2023. "Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Ren, He & Liu, Wenyi & Shan, Mengchen & Wang, Xin & Wang, Zhengfeng, 2021. "A novel wind turbine health condition monitoring method based on composite variational mode entropy and weighted distribution adaptation," Renewable Energy, Elsevier, vol. 168(C), pages 972-980.
- Li, Qi & Chen, Liang & Kong, Lin & Wang, Dong & Xia, Min & Shen, Changqing, 2023. "Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
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Keywords
Single domain generalization; Fault diagnosis; Domain-invariant representation; Contrastive learning; Style learning; Adversarial training;All these keywords.
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