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Titolo:
Estimating fatigue curves with the random fatigue-limit model
Autore:
Pascual, FG; Meeker, WQ;
Indirizzi:
Washington State Univ, Dept Math, Pullman, WA 99164 USA Washington State Univ Pullman WA USA 99164 pt Math, Pullman, WA 99164 USA Washington State Univ, Program Stat, Pullman, WA 99164 USA Washington State Univ Pullman WA USA 99164 am Stat, Pullman, WA 99164 USA Iowa State Univ, Dept Stat, Ames, IA 50011 USA Iowa State Univ Ames IA USA 50011 ate Univ, Dept Stat, Ames, IA 50011 USA Iowa State Univ, Ctr Nondestruct Evaluat, Ames, IA 50011 USA Iowa State Univ Ames IA USA 50011 Nondestruct Evaluat, Ames, IA 50011 USA
Titolo Testata:
TECHNOMETRICS
fascicolo: 4, volume: 41, anno: 1999,
pagine: 277 - 290
SICI:
0040-1706(199911)41:4<277:EFCWTR>2.0.ZU;2-N
Fonte:
ISI
Lingua:
ENG
Soggetto:
NONCONSTANT STANDARD-DEVIATION; RUNOUTS; STRESS;
Keywords:
akaike information criterion; fatigue data; maximum likelihood methods; probability (P-P) plots; random fatigue limit; right censoring;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
25
Recensione:
Indirizzi per estratti:
Indirizzo: Pascual, FG Washington State Univ, Dept Math, Pullman, WA 99164 USA Washington State Univ Pullman WA USA 99164 lman, WA 99164 USA
Citazione:
F.G. Pascual e W.Q. Meeker, "Estimating fatigue curves with the random fatigue-limit model", TECHNOMET, 41(4), 1999, pp. 277-290

Abstract

In a fatigue-limit model, units tested below the fatigue limit (also knownas the threshold stress) theoretically will never fail. This article uses a random fatigue-limit model to describe (a) the dependence of fatigue lifeon 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.

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Documento generato il 05/07/20 alle ore 10:03:45