Residual life estimation based on bivariate Wiener degradation process with measurement errors
来源期刊：中南大学学报(英文版)2013年第7期
论文作者：王小林 GUO Bo(郭波) CHENG Zhi-jun(程志君) JIANG Ping(蒋平)
文章页码：1844 - 1851
Key words：residual life; performance characteristics; bivariate Wiener process; Frank copula; MCMC method
Abstract: An adaptive method of residual life estimation for deteriorated products with two performance characteristics (PCs) was proposed, which was sharply different from existing work that only utilized one-dimensional degradation data. Once new degradation information was available, the residual life of the product being monitored could be estimated in an adaptive manner. Here, it was assumed that the degradation of each PC over time was governed by a Wiener degradation process and the dependency between them was characterized by the Frank copula function. A bivariate Wiener process model with measurement errors was used to model the degradation measurements. A two-stage method and the Markov chain Monte Carlo (MCMC) method were combined to estimate the unknown parameters in sequence. Results from a numerical example about fatigue cracks show that the proposed method is valid as the relative error is small.
WANG Xiao-lin(王小林), GUO Bo(郭波), CHENG Zhi-jun(程志君), JIANG Ping(蒋平)
(College of Information Systems and Management, National University of Defense Technology,
Changsha 410073, China)
Abstract:An adaptive method of residual life estimation for deteriorated products with two performance characteristics (PCs) was proposed, which was sharply different from existing work that only utilized one-dimensional degradation data. Once new degradation information was available, the residual life of the product being monitored could be estimated in an adaptive manner. Here, it was assumed that the degradation of each PC over time was governed by a Wiener degradation process and the dependency between them was characterized by the Frank copula function. A bivariate Wiener process model with measurement errors was used to model the degradation measurements. A two-stage method and the Markov chain Monte Carlo (MCMC) method were combined to estimate the unknown parameters in sequence. Results from a numerical example about fatigue cracks show that the proposed method is valid as the relative error is small.
Key words:residual life; performance characteristics; bivariate Wiener process; Frank copula; MCMC method
