An attention residual network with triple feature as input is proposed to predict the remaining useful life (RUL) of bearings. First, channel and spatial are connected in series into connection neural obtain a new module, so that newly constructed deep learning can better pay weak changes bearing state. Secondly, “triple feature” used network, grasp change trend running state, realize predictio...

This work is focused on developing an effective method for bearing remaining useful life predictions. The in accurately predicting the of bearings so that machine damage, production outage, and human accidents caused by unexpected failure can be prevented. study uses dataset provided FEMTO-ST Institute, Besançon, France. starts with exploration neural networks, based which biaxial vibration sig...