A Dual-Channel Deep Learning Framework with ECA-TCN for Bearing RUL Estimation
Predicting the Remaining Useful Life (RUL) of rolling bearings is a central problem in predictive maintenance, but most existing data-driven solutions still rely on a single vibration channel and a CNN–LSTM architecture. This combination ignores cross-axis degradation information, depends on noise-sensitive Fourier fea...