A hybrid prognosis scheme for rolling bearings based on a novel health indicator and nonlinear Wiener process

This paper proposes a novel hybrid method aiming at the fault prognosis of bearings. A nonlinear health indicator is first constructed using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Kernel Principal Component Analysis to reflect the health state of a bearing accurately and convincingly. Subsequently, multi-domain features are extracted from vibration signals and the Dual-Channel Transformer Network with the Convolutional Block Attention Module is applied for constructing HIs of the rest bearings. Moreover, the 3σ criterion is employed to establish the condition monitoring interval of health state and detect the First Prediction Time, with which degradation modeling and…