An-Qi Xu

A Hybrid LSTM–Transformer Framework for Rolling Bearing Fault Diagnosis with Time-Frequency Feature Learning

Rolling bearing fault diagnosis is essential for ensuring the reliability and safety of rotating machinery in nuclear industry applications. To improve diagnostic accuracy and robustness in noisy diagnostic environments, this paper proposes a hybrid deep learning model combining Long Short-Term Memory (LSTM) and Transf...