Bearing Remaining Useful Life Prediction Based on a Nonlinear Wiener Process Model

Hindawi Shock and Vibration Volume 2018, Article ID 4068431, 13 pages https://doi.org/10.1155/2018/4068431 Research Article Bearing Remaining Useful Life Prediction Based on a Nonlinear Wiener Process Model Juan Wen , Hongli Gao , and Jiangquan Zhang School of Mechanical Engineering, Southwest Jiaotong University, 610031 Chengdu, China Correspondence should be addressed to Hongli Gao; hongli [email protected] Received 1 August 2017; Revised 12 February 2018; Accepted 20 May 2018; Published 26 June 2018 Academic Editor:NunoM.Maia Copyright © 2018 Juan Wen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Prognostic is an essential part of condition-based maintenance, which can be employed to enhance the reliability and availability and reduce the maintenance cost of mechanical systems. This paper develops an improved remaining useful life (RUL) prediction method for bearings based on a nonlinear Wiener process model. First, the service life of bearings is divided into two stages in terms of the working condition. en Th a new prognostic model is con structed to reflect the relationship between time and bearing health status. Besides, a variety of factors that cause uncertainties toward the degradation path are considered and appropriately managed to obtain reliable RUL prediction results. eTh particle filtering is utilized to estimate the degradation state, qualify the uncertainties, and predict the RUL. The experimental studies show that the proposed method has a better performance in RUL prediction and uncertainty management than the exponential model and the linear model. 1. Introduction no prior knowledge about systems is needed, and the relationship between the RUL and the historical failure data The condition-based maintenance (CBM) is a widely used is constructed with machine...