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Transfer Learning for Prognostics and Health Management:Advances,Challenges,and Opportunities
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作者 Ruqiang Yan Weihua Li +5 位作者 Siliang lu Min Xia Zhuyun Chen Zheng Zhou Yasong Li jingfeng lu 《Journal of Dynamics, Monitoring and Diagnostics》 2024年第2期60-82,共23页
As failure data is usually scarce in practice upon preventive maintenance strategy in prognostics and health management(PHM)domain,transfer learning provides a fundamental solution to enhance generalization of datadri... As failure data is usually scarce in practice upon preventive maintenance strategy in prognostics and health management(PHM)domain,transfer learning provides a fundamental solution to enhance generalization of datadriven methods.In this paper,we briefly discuss general idea and advances of various transfer learning techniques in PHM domain,including domain adaptation,domain generalization,federated learning,and knowledge-driven transfer learning.Based on the observations from state of the art,we provide extensive discussions on possible challenges and opportunities of transfer learning in PHM domain to direct future development. 展开更多
关键词 domain adaptation domain generalization federated learning knowledge-driven PHM transfer learning
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