A Digital-Twin-Enhanced Adversarial Transfer Learning Framework for Fault Diagnosis of Train Axle Box Bearings
Intelligent fault diagnosis methods have become essential for ensuring the secure and dependable functioning of modern railway systems. In particular, digital twin technology offers a highly promising approach to overcome the challenge of limited fault data availability. However, current digital-twin-based fault diagno...