Multi-adversarial domain transfer network with adaptive threshold generation pseudolabels for fault diagnosis under strong interference
Journal of Vibration and Control
Published online on January 19, 2026
Abstract
Journal of Vibration and Control, Ahead of Print.
In practical industrial scenarios, the fault diagnosis for rolling bearings faces the challenges of scarce fault data and strong interference. The adversarial transfer learning can address those issues, but it often relies on global feature alignment, ...
In practical industrial scenarios, the fault diagnosis for rolling bearings faces the challenges of scarce fault data and strong interference. The adversarial transfer learning can address those issues, but it often relies on global feature alignment, ...