Bo-Wen Hu

Physics-data coupled transfer learning for rolling bearing fault diagnosis under variable conditions

A novel cross-domain diagnosis method that deeply integrates dynamic mechanism modeling with conditional generative adversarial networks and synergizes physical interpretability with data adaptability is proposed, offering a robust solution for scenarios with limited samples and significant domain shifts.