Pyramid-type zero-shot learning model with multi-granularity hierarchical attributes for industrial fault diagnosis
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DOI: 10.1016/j.ress.2023.109591
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References listed on IDEAS
- Yiping Gao & Liang Gao & Xinyu Li & Yuwei Zheng, 2020. "A zero-shot learning method for fault diagnosis under unknown working loads," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 899-909, April.
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Cited by:
- Wang, Haoyu & Li, Chuanjiang & Ding, Peng & Li, Shaobo & Li, Tandong & Liu, Chenyu & Zhang, Xiangjie & Hong, Zejian, 2024. "A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
- Ma, Chenyang & Wang, Xianzhi & Li, Yongbo & Cai, Zhiqiang, 2024. "Broad zero-shot diagnosis for rotating machinery with untrained compound faults," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Cai, Li & Deng, Xuanhong & Yin, Hongpeng & Lin, Jingdong & Qin, Yan, 2025. "Generalized zero-sample industrial fault diagnosis with domain bias," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
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- Ma, Chenyang & Wang, Xianzhi & Li, Yongbo & Cai, Zhiqiang, 2024. "Broad zero-shot diagnosis for rotating machinery with untrained compound faults," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
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Keywords
Zero-shot fault diagnosis; Pyramid-type hierarchical attribute; Fault description; Information granularity;All these keywords.
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