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JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)
    
Remaining useful life prediction method based on Gamma processes with random parameters
WANG Hao-wei1, XU Ting-xue1, LIU Yong2
1. Department of Ordnance Science and Technology, Naval Aeronautical and Astronautical University, YanTai 264000, China; 2. New Equipment Training Center, Naval Aeronautical and Astronautical University, YanTai 264000, China
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Abstract  

A method based on Bayesian inference with non-conjugate prior distributions of parameters of Gamma processes was proposed for the products which had gone through accelerated aging tests in order to improve the reliability of remaining useful life prediction. The accelerated aging data was considered as prior information and Gamma processes were utilized to model the aging data. After the transformed values of parameters at the normal working stress were obtained by acceleration factors, the Anderson-Darling statistic was applied to determine the prior distributions of two parameters. Few testing data at working was considered as field information, and the posterior means of parameters were obtained by Markov Chain Monte Carlo simulation based on Gibbs sampling. The research significance and engineering value were demonstrated through a missile electrical connector.



Published: 01 April 2015
CLC:  TB 114  
Cite this article:

WANG Hao-wei, XU Ting-xue, LIU Yong. Remaining useful life prediction method based on Gamma processes with random parameters. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2015, 49(4): 699-704.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2015.04.013     OR     http://www.zjujournals.com/eng/Y2015/V49/I4/699


基于随机参数Gamma过程的剩余寿命预测方法

为了提高剩余寿命预测的可信度,针对进行过加速老化试验的产品,提出利用Gamma过程参数的非共轭先验分布进行Bayesian统计推断的剩余寿命预测方法.将加速老化数据作为先验信息,利用Gamma过程进行老化建模,通过加速因子获得形状参数在工作应力下的折算值,使用Anderson-Darling 统计量确定随机参数的先验分布.将产品工作中的少量实测数据作为现场信息,利用基于Gibbs抽样的Markov Chain Monte Carlo(MCMC)仿真得到参数的后验均值.以某型导弹电连接器为例说明了该方法的研究意义和工程应用价值.

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