Affiliation:
1. Science College, Inner Mongolia University of Technology, Hohhot, China
Abstract
The paper aims at predicting the remaining useful life of highly reliable and
long-life products with multiple and multi-stage characteristics in the
degradation process. Considering the unit-to-unit variability among the
product units, a new bivariate and two-phase Wiener process model with
random effects is established. Schwarz Information Criterion is used to
identify the change points of the degradation model, and the analytical
expressions of life and remaining useful life are given by the concept of
first hitting time. Furthermore, the appropriate Copula function is selected
to describe the correlation between the two quality characteristics based on
Akaike Information Criterion. A bivariate degradation model is established
and the unknown parameters of the model are estimated by Markov Chain Monte
Carlo method. Finally, the applicability and effectiveness of the proposed
method are verified by the comparative analysis of turbine engine.
Publisher
National Library of Serbia