Jing-Jing Cao

ST-DGAT: A Fault-Characteristic Frequency-Guided Dynamic Graph Attention Transformer for Bearing Remaining Useful Life Prediction

Accurate remaining useful life (RUL) prediction of rolling bearings remains challenging because fault-related spectral components evolve across frequency and time. This article proposes a spatio-temporal dynamic graph attention transformer (ST-DGAT) that embeds bearing kinematics into frequency-graph learning. A logari...