Jing-Hong Tian

T-UIL: an incremental few-shot fault diagnosis framework based on uncertainty-guided trustworthy sample screening

FDCA-GRU: A dual-branch fusion network with frequency dynamic convolution attention for bearing fault diagnosis

Rolling bearing fault diagnosis is confronted with significant technical challenges, including the difficult extraction of weak fault features and the insufficient fusion of one-dimensional (1D) temporal dynamics with two-dimensional time-frequency patterns. To address this issue, this article proposes a novel dual-bra...

KAP-Former: a knowledge-aware physics-informed transformer for cross-domain few-shot bearing fault diagnosis

Recent advances in deep metric learning and meta-learning have shown promise for few-shot bearing fault diagnosis, yet their cross-domain generalization remains limited under cross-sampling-rate conditions, cross-test-rig transfer, and strong background interference, mainly due to frequency-coordinate misalignment and...