Paper Info
Title
Remaining Useful Life Prediction for Nonlinear Degraded Equipment with Bivariate Time Scales
Abstract
As the fundamental and prerequisite work of remaining useful life (RUL) prediction, degradation modeling directly affects the accuracy of RUL prediction. Existing degradation models are all developed under a single time scale, and less research has been carried out to consider the impact of multiple time scales on the degradation model. Toward this end, we mainly study a nonlinear degradation modeling and RUL prediction method for nonlinear stochastic degraded equipment with bivariate time scales in this paper. Firstly, a nonlinear degradation model considering the influence of two time scales is constructed based on the diffusion process. At the same time, the relationship between the two scales is quantitatively characterized by random proportional coefficient. Then, the analytical expressions of the life and RUL for nonlinear degraded equipment are derived under the concept of first passage time (FPT). In order to realize the adaptive estimation of parameters, the model parameters estimation method based on maximum likelihood estimation (MLE) and Kalman filtering algorithm is developed in this paper. Finally, numerical simulation and the monitoring data of gyroscope verify the effectiveness and superiority of the proposed method. The experimental results show that the method proposed in this paper can effectively improve the accuracy of RUL prediction, and has a broad engineering application space.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2951804
IEEE ACCESS
Keywords
DocType
Volume
Bivariate time scales,diffusion process,nonlinear degradation,Kalman filtering,remaining useful life (RUL) prediction
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Hong Pei100.34
C. H. Chang242836.69
Xiao-Sheng Si362346.17
Jian-Fei Zheng493.18
Qi Zhang500.34
Zheng-Xin Zhang61199.12
Zhenan Pang773.50