Cross-Machine Fault Diagnosis with Semi-Supervised Discriminative Adversarial Domain Adaptation

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 13; p. 3753
• Main Authors: Wang, Xiaodong, Liu, Feng, Zhao, Dongdong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 04.07.2020; MDPI
• Subjects: Annotations; Bearings; cross-machine fault diagnosis; Deep learning; discriminability; Fault diagnosis; Laboratories; Neural networks; semi-supervised domain adaptation; Working conditions; discriminability; cross-machine fault diagnosis; semi-supervised domain adaptation
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20133753

Bearings are ubiquitous in rotating machinery and bearings in good working conditions are essential for the availability and safety of the machine. Various intelligent fault diagnosis models have been widely studied aiming to prevent system failures. These data-driven fault diagnosis models work wel...