Multi-source transfer learning network to complement knowledge for intelligent diagnosis of machines with unseen faults
Mechanical Systems and Signal Processing(2022)
Abstract
•A multi-source transfer learning network is proposed for intelligent diagnosis.•Diagnostic knowledge is complemented to recognize unseen faults of machines.•Multiple subnets are proposed to adapt partial distribution of source-target pairs.•A multi-source knowledge fusion module is constructed to fuse results from subnets.
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Key words
Intelligent fault diagnosis,Rotating machines,Multi-source transfer learning,Deep transfer learning,Partial domain adaptation
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