Estimating fatigue curves with the random fatigue-limit model

被引：215

作者：

Pascual, FG ^{[1
]}

Meeker, WQ

机构：

[1] Washington State Univ, Dept Math, Pullman, WA 99164 USA

[2] Washington State Univ, Program Stat, Pullman, WA 99164 USA

[3] Iowa State Univ, Dept Stat, Ames, IA 50011 USA

[4] Iowa State Univ, Ctr Nondestruct Evaluat, Ames, IA 50011 USA

来源：

TECHNOMETRICS | 1999年 / 41卷 / 04期

关键词：

akaike information criterion; fatigue data; maximum likelihood methods; probability (P-P) plots; random fatigue limit; right censoring;

D O I：

10.2307/1271342

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In a fatigue-limit model, units tested below the fatigue limit (also known as the threshold stress) theoretically will never fail. This article uses a random fatigue-limit model to describe (a) the dependence of fatigue life on the stress level, (b) the variation in fatigue life, and (c) the unit-to-unit variation in the fatigue limit. We fit the model to actual fatigue datasets by maximum likelihood methods and study the fits under different distributional assumptions. Small quantiles of the life distribution are often of interest to designers. Lower confidence bounds based on likelihood ratio methods are obtained for such quantiles. To assess the fits of the model, we construct diagnostic plots and perform goodness-of-fit tests and residual analyses.

引用

页码：277 / 290

页数：14