利用变环境数据的Weibull分布可靠性综合评估

洪东跑; 马小兵; 赵宇

利用变环境数据的Weibull分布可靠性综合评估

1.
中国运载火箭技术研究院, 北京 100076
2. 北京航空航天大学可靠性与系统工程学院, 北京 100191

详细信息

中图分类号: TB114.3
计量
- 文章访问数: 1870
- HTML全文浏览量: 127
- PDF下载量: 558
- 被引次数: 0
出版历程
- 收稿日期: 2011-07-21
- 网络出版日期: 2012-11-30

Integrated reliability assessment for Weibull distribution using varied environment data

1.
China Academy of Launch Vehicle Technology, Beijing 100076, China
2. School of Reliability and Systems Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 为了提高可靠性评估精度,研究了环境因素对产品可靠性的影响,提出了一种适用于Weibull分布的变环境数据可靠性综合评估方法.首先通过利用径向基函数法来度量不同环境因素及其交互作用对可靠性的影响,建立了关于环境因素的位置参数模型.并针对刻度参数依赖于环境因素的情形,利用线性模型来建立刻度参数模型.然后利用广义线性模型,给出了位置和刻度参数模型系数的极大似然估计,并给出了可靠度近似置信下限.实例表明该方法能较好地度量环境因素对可靠性的影响,而且合理可行便于工程应用.
- 可靠性评估 /
- Weibull分布 /
- 环境因素 /
- 径向基函数法 /
- 广义线性模型
Abstract: To improve the stability and accuracy of the reliability assessment, a method of integrated reliability assessment for Weibull distribution was proposed using the varied environment test data. In this method, the location parameter and scale parameter were assumed respectively as a function of relevant environment variables. Then the location parameter function was constructed by the method of radial basis function while the scale parameter function was constructed by the linear model. Thus the influences of environment factors on the reliability of the product were measured quantificationally. With the generalized linear model, the maximum likelihood estimations of the coefficients were obtained, and corresponding arithmetic was put forward. With the estimations, the approximated confidence interval for the reliability function was obtained according to the normal law. The instance analysis shows that this integrated reliability assessment method improves the precision of reliability assessment and is straightforward for engineering application.
- reliability assessment /
- Weibull distribution /
- environment factor /
- radial basis function /
- generalized linear model

HTML全文

参考文献(14)

[1]	Wendai W,Dimitri B K.Fitting the Weibull log-linear model to accelerated life-test data [J].IEEE Transactions on Reliability,2000,49(2):217-223
[2]	李凤,师义民,荆源.两参数Weibull分布环境因子的Bayes估计[J].系统工程与电子技术,2008,30(1):186-189 Li Feng,Shi Yimin,Jing Yuan.Bayesian estimation for environmental factor of two parameter of Weibull distribution[J].Systems Engineering and Electronics,2008,30(1):186-189(in Chinese)
[3]	洪东跑,马小兵,赵宇,等.基于比例风险模型的环境折合系数确定方法[J].北京航空航天大学学报,2010,36(4):443-446 Hong Dongpao,Ma Xiaobing,Zhao Yu,et al.Environment referring factor based on proportional hazards model[J] Journal of Beijing University of Aeronautics and Astronautics,2010,36(4):443-446(in Chinese)
[4]	Nelson W.Accelerated testing:statistical models,test plans,and data analyzes [M].New York:John Wiley & Sons,1990
[5]	洪东跑,赵宇,马小兵.利用变环境试验数据的可靠性综合评估[J].北京航空航天大学学报,2009,35(9):1152-1155 Hong Dongpao,Zhao Yu,Ma Xiaobing.Integrated reliability assessment using varied environment test data [J].Journal of Beijing University of Aeronautics and Astronautics,2009,35(9):1152-1155(in Chinese)
[6]	Elsayed E A,Wang H Z.Bayes & classical estimation of environmental factors for the binomial distribution [J].IEEE Transactions on Reliability,1996,45(4):661-665
[7]	Mettas A.Modeling & analysis for multiple stress-type accelerated life data [C]//Proceedings Annual Reliability and Maintainability Symposium.Los Angeles:IEEE,2000:138-143
[8]	Chen C K.Temperature-dependent standard deviation of log (failure time) distributions [J].IEEE Transaction on Reliability,1991,40(2):157-160
[9]	Schwarz J A.Effect of temperature on the variance of the lognormal distribution of failure times due to electro migration damage [J].Journal of Applied Physics,1987,61:801-803
[10]	Meeter C A.Meeker W Q.Optimum accelerated life tests with a nonconstant scale parameter [J].Technometrics,1994,36(1):71-83
[11]	Buhmann M D.Radial basis functions [M].London:Cambridge University Press,2004
[12]	McLinn J A.New analysis methods of multilevel accelerated life tests [C]// IEEE Proceedings of Annual Reliability and Maintainability Symposium.Washington DC:IEEE,1999:38-42
[13]	Uusipaikka E.Confidence intervals in generalized regression models [M].Boca Raton:CRC Press,2009
[14]	Bagdonavicius V,Nikulin M.Accelerated life models modeling and statistical analysis [M].Boca Raton:Chapman & Hall/CRC,2002