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首页> 外文期刊>Life Cycle Reliability and Safety Engineering >Using the best two-observational percentile and maximum likelihood methods in a multicomponent stress-strength system to reliability estimation of inverse Weibull distribution
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Using the best two-observational percentile and maximum likelihood methods in a multicomponent stress-strength system to reliability estimation of inverse Weibull distribution

机译：用最好的中百分位在多组分最大似然方法应力强度系统可靠性估计的逆威布尔分布

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Abstract In this paper, we propose an estimate of reliability in a multicomponent system. The system has kdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$$k$$end{document} components strengths are given by independently and identically distributed random variables X1documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${X}_{1}$$end{document}, X2documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${X}_{2}$$end{document},…, Xkdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${X}_{k}$$end{document} and each component is exposed to random stress Ydocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${rm Y}$$end{document}. The reliability of such a system is obtained when strength and stress variables are given by inverse Weibull (IW) distribution with scale parameters λ1documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${lambda }_{1}$$end{document},  λ2documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$${lambda }_{2}$$end{document} and common shape parameter αdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$$alpha$$end{document}. The system reliability is estimated using maximum likelihood estimation (MLE) and the best two-observational percentile estimation (BTPE) methods in samples drawn from strength and stress distributions. Also, the asymptotic confidence interval for system reliability is obtained. The reliability estimators obtained from both methods are compared using average bias, mean squares error, and confidence interval length via Monte Carlo simulation. In the end, using two real data sets we illustrate the procedure.
机译：文摘中,我们提出一个估计的在多组分系统可靠性。系统具有kdocumentclass [12 pt]{最小}usepackage {upgreek}setlength {oddsidemargin} {-69 pt}优点是由独立的同分布的随机变量usepackage {upgreek}setlength {oddsidemargin} {-69 pt}usepackage {upgreek}setlength {oddsidemargin} {-69 pt}usepackage {upgreek}setlength {oddsidemargin} {-69 pt}组件是随机接触压力Ydocumentclass [12 pt]{最小}usepackage {amsmath}setlength {oddsidemargin} {-69 pt}获得这样一个系统的可靠性强度和应力变量是由逆威布尔(IW)分布与规模usepackage {upgreek}setlength {oddsidemargin} {-69 pt}usepackage {upgreek}setlength {oddsidemargin} {-69 pt}常见的形状参数αdocumentclass [12 pt]{最小}usepackage {amsmath}setlength {oddsidemargin} {-69 pt}开始α{文档}$ $ $ ${文档}结束。可靠性是使用最大似然估计估计(企业)和中最好的百分位数估计(BTPE)方法在样本从强度和应力分布。此外,渐近置信区间系统的可靠性。估计从两种方法获得使用平均偏差相比,平均平方误差,通过蒙特卡罗和置信区间的长度模拟。我们说明这个过程。

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