Comparison of Parameter Estimation Methods for Reliability Model

doi:10.3969/j.issn.1000-565X.2011.06.009

Journal of South China University of Technology (Natural Science Edition) ›› 2011, Vol. 39 ›› Issue (6): 47-52.doi: 10.3969/j.issn.1000-565X.2011.06.009

• Mechanical Engineering • Previous Articles Next Articles

Comparison of Parameter Estimation Methods for Reliability Model

Wang Xiao-feng¹Shen Gui-xiang¹Zhang Ying-zhi¹Chen Bing-kun¹Zheng Shan¹Liu Wei²

1. College of Mechanical Science and Engineering,Jilin University,Changchun 130022,Jilin,China; 2. School of Life Sciences,Changchun University of Science and Technology,Changchun 130022,Jilin,China

Received:2010-12-29 Revised:2011-02-13 Online:2011-06-25 Published:2011-05-06
Contact: 王晓峰(1984-) ，男，博士生，主要从事数控机床可信性技术研究． E-mail:289799164@163.com
About author:王晓峰(1984-) ，男，博士生，主要从事数控机床可信性技术研究．
Supported by:
国家自然科学基金资助项目( 50875110) ; 国家科技重大专项项目( 2010ZX04014-011)

Abstract

Abstract:

In order to solve the problems existing in the parameter estimation of the Weibull distribution for the reliability determination of complex systems,both the x-direction and y-direction parameter estimation methods are introduced,and the statistical characteristics of the two methods are analyzed. Then,a comparison between the two methods is carried out via the Monte Carlo simulation. Finally,by reasonably selecting a parameter estimation
method,a Weibull distribution model of complex products is established. The results show that,for the reliability model of complex systems,when the sample size n is more than 14,the x-direction parameter estimation method is applicable. However,when n is not more than 14,a suitable parameter estimation method should be selected according to the mean square deviation of the sample.

Key words: reliability, parameter estimation, small sample, Weibull distribution, Monte Carlo simulation

Wang Xiao-feng Shen Gui-xiang Zhang Ying-zhi Chen Bing-kun Zheng Shan Liu Wei. Comparison of Parameter Estimation Methods for Reliability Model[J]. Journal of South China University of Technology (Natural Science Edition), 2011, 39(6): 47-52.

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Comparison of Parameter Estimation Methods for Reliability Model

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