Residual life estimation based on bivariate Wiener degradation process with measurement errors  被引量:12

Residual life estimation based on bivariate Wiener degradation process with measurement errors

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作  者:王小林 郭波 程志君 蒋平 

机构地区:[1]College of Information Systems and Management, National University of Defense Technology

出  处:《Journal of Central South University》2013年第7期1844-1851,共8页中南大学学报(英文版)

基  金:Project(60904002)supported by the National Natural Science Foundation of China

摘  要: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.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.

关 键 词:residual life performance characteristics bivariate Wiener process Frank copula MCMC method 

分 类 号:TB115[理学—数学]

 

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