Remaining useful life prediction of rolling bearings based on the three-parameter Weibull distribution proportional hazards model
Ye Wang, Zhixiong Chen, Yang Zhang, Xin Li, Zhixiong Li
Abstract
In order to accurately predict the remaining useful life (RUL) of rolling bearings, a novel method based on the threeparameter Weibull distribution proportional hazards model (WPHM) is proposed in this paper. In this new method, degradation features of the bearing vibration signals were calculated in the time, frequency and time-frequency domains and treated as the input covariates of the predictive WPHM. Essential knowledge of the bearing degradation dynamics was learnt from the input features to build an effective three-parameter WPHM for bearing RUL prediction. Experimental data acquired from the run-to-failure bearing tests of the intelligent maintenance system (IMS) was used to evaluate the proposed method. The analysis results demonstrate that the proposed model is able to produce accurate RUL prediction for the tested bearings and outperforms the popular two-parameter WPHM.