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确定可靠性分析Weibull分布参数的概率加权矩法
引用本文:邓建,古德生,李夕兵.确定可靠性分析Weibull分布参数的概率加权矩法[J].计算力学学报,2004,21(5):609-613.
作者姓名:邓建  古德生  李夕兵
作者单位:中南大学,资源与安全工程学院,长沙,410083
基金项目:中国博士后科学基金(2002),湖南省优秀博士论文基金(2002)资助项目.
摘    要:用概率加权矩理论来确定描述可靠性分析中疲劳寿命Weibull分布的参数。推导了Weibull分布参数与样本概率加权矩的关系,给出了计算样本概率加权矩的MATLAB语言程序片段。根据疲劳寿命的样本值,计算各阶样本概率加权矩,然后估计疲劳寿命分布的参数。蒙特卡罗模拟的结果和应用实例表明,概率加权矩法计算结果精度较高,具有理论和实用价值。

关 键 词:三参数Weibull分布  参数估计  概率加权矩  疲劳寿命
文章编号:1007-4708(2004)05-0609-05
修稿时间:2002年12月17

Parameters and quantile estimation for fatigue life distribution using probability weighted moments
Deng Jian,Gu Desheng,Li Xibing.Parameters and quantile estimation for fatigue life distribution using probability weighted moments[J].Chinese Journal of Computational Mechanics,2004,21(5):609-613.
Authors:Deng Jian  Gu Desheng  Li Xibing
Institution:Deng Jian~,Gu Desheng,Li Xibing
Abstract:Weibull distribution is a three-parameter distribution that contains normal, exponential and Rayleigh distribution as special cases. It is one of the most common and widely-used distribution in reliability theory, especially in fatigue life estimation. The goal of this paper is to use the method of probability weighted moments for estimating parameters and quantiles of fatigue life distribution (i.e. Weibull distribution) and to describe our MATLAB implementation of the method of probability weighted moments from field sample data. The relationship between sample probability weighted moments and the parameters of Weibull distribution was investigated. Two examples were presented to illustrate the applicability of the method. The results obtained from probability weighted moments were compared with the actual parameters by the method of Monte-Carlo method and with the results obtained by the method of Mean Rank Fitting and the method of Correlation Coefficient. It was demonstrated that the parameters estimated by the method of probability weighted moments are accurate enough to be used in reliability analysis.
Keywords:three-parameter Weibull distribution  parameter estimation  probability weighted moments  fatigue life
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