A novel deep convolution multi-adversarial domain adaptation model for rolling bearing fault diagnosis

Lanjun Wan; Yuanyuan Li; Keyu Chen; Kun Gong; Changyun Li

doi:10.1016/j.measurement.2022.110752

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A novel deep convolution multi-adversarial domain adaptation model for rolling bearing fault diagnosis

Lanjun Wan Yuanyuan Li Keyu Chen Kun Gong Changyun Li

Year: 2022 Journal: Measurement Vol: 191 Pages: 110752-110752 Publisher: Elsevier BV

DOI: 10.1016/j.measurement.2022.110752

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Keywords:

Computer science Fault (geology) Feature extraction Artificial intelligence Pattern recognition (psychology) Classifier (UML) Domain adaptation Deep learning

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Topics

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Mechanical Failure Analysis and Simulation

Physical Sciences → Engineering → Mechanical Engineering

Gear and Bearing Dynamics Analysis

Physical Sciences → Engineering → Mechanical Engineering

A novel deep convolution multi-adversarial domain adaptation model for rolling bearing fault diagnosis

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Citation History

Topics

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