article Open AccessTop 1% cited
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Mechanical Systems and Signal Processing · 2021 · Vol. 167 · pp. 108487–108487
Weihua Li✉(South China University of Technology)Ruyi Huang✉(South China University of Technology)Jipu Li(South China University of Technology)Yixiao Liao(South China University of Technology)Zhuyun Chen(South China University of Technology)Guolin He(Guangzhou Experimental Station)Ruqiang Yan(Xi'an Jiaotong University)Konstantinos Gryllias(KU Leuven)
Machine Fault Diagnosis TechniquesNon-Destructive Testing TechniquesFault Detection and Control SystemsLeverage (statistics)Computer scienceTransfer of learningArtificial intelligencePerspective (graphical)Field (mathematics)Deep learningMachine learningData scienceRepresentation (politics)
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Artificial intelligence for fault diagnosis of rotating machinery: A review
Mechanical Systems and Signal Processing · 2018 · 2,047 citations
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Mechanical Systems and Signal Processing · 2018 · 1,079 citations
Deep learning and its applications to machine health monitoring
Mechanical Systems and Signal Processing · 2018 · 2,497 citations
Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning
IEEE Transactions on Industrial Informatics · 2018 · 1,500 citations
Machine learning methods for wind turbine condition monitoring: A review
Renewable Energy · 2018 · 779 citations
Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data
IEEE Transactions on Industrial Electronics · 2018 · 1,188 citations
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