Remaining Useful Life Estimation for Rolling Bearing With SIOS-Based Indicator and Particle Filtering

Rolling bearing is a key component of rotating machinery, and its remaining useful life (RUL) estimation is also a critical technique in prognostics health management activities. In this paper, we propose a two-stage strategy for bearing health monitoring, where the bearing health process is divided into two stages: normal stage and degeneration stage, and a new method is proposed to estimate the bearing RUL by combining a new health indicator (HI) and particle filtering (PF). First, the structural information of the spectrum (SIOS) algorithm is employed to construct the HI called SIOS-based indicator (SIOSI) for bearing degeneration monitoring. Second, the initial degenerate point (IDP) is evaluated by a novel index calculated with self-zero space observer in order to conduct the two-stage division of normal and degeneration stages. Third, after detecting the IDP, the bearing RUL is estimated using the SIOSI and the PF-based algorithm with the help of a degeneration model. The effectiveness of the proposed methodology is validated using vibration data collected from bearing run-to-failure tests. Experimental results have shown that the bearing RUL could be estimated acceptably with the proposed method, and its performance is greatly superior to that presented by L10 life formula.