Reliability Growth Evaluation for Highly Reliable Products Based on Bayesian Dynamic Forecasting

摘要：

For highly reliable products, the last stages of reliability growth tests usually have small sample size,which hampers the corresponding reliability evaluation.A generalized linear model(GLM) is established by the historical multistage samples, and then by Bayes-Monte Carlo method, the estimation of the hyper parameter is obtained to serve as the start point of the growth trend forecasting.In the following test stage, the expectation and variance estimations of the hyper parameter are converted to the prior distribution, and then the hierarchical Bayesian forecasting is carried out to obtain the prior distribution of the failure intensity of the current stage.The finite sample of the current stage is used to perform the Bayesian estimation to obtain the posterior of the hyper parameter, and the evaluation results are calculated recursively.The above Bayesian dynamic forecasting method can effectively make the historical information a supplement of the current stage sample, which is of concise computation form,is applicable to the multistage reliability growth test evaluation of highly reliable products.

关键词： Reliability Growth Generalized Linear Model Hierarchical Bayesian Model Bayesian Dynamic Forecasting

作者: Zhi-qiang Yan Ying-jie Jiang Hong-wei Xie

作者单位: College of Mechatronic Engineering and Automation National University of Defense Technology Changsha 410073,China

会议类型: 国际会议

会议名称: 2009 8th International Conference on Reliability,Maintainability and Safety(第八届中国国际可靠性、维修性、安全性会议)

会议地点: 成都

会议语种:英文

页码: 386-390

在线出版日期: 2009-08-24（万方平台首次上网日期，不代表论文的发表时间）