1982
DOI: 10.1109/tr.1982.5221421
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Fatigue Failure Models ߝ Birnbaum-Saunders vs. Inverse Gaussian

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Cited by 95 publications
(46 citation statements)
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“…The last term in the right-hand side of the equality accounts for the fact that in the Wiener process the events [X(t) ≤ ω and X * (t) > ω] have a probability strictly greater than zero [43], where X * (t) = sup s∈[0,t] X(s). In fact, in the case of the Wiener process the events T > t and X(t) ≤ ω are not equivalent.…”
Section: ) P-quantile Lifetime At the Use Conditionmentioning
confidence: 99%
“…The last term in the right-hand side of the equality accounts for the fact that in the Wiener process the events [X(t) ≤ ω and X * (t) > ω] have a probability strictly greater than zero [43], where X * (t) = sup s∈[0,t] X(s). In fact, in the case of the Wiener process the events T > t and X(t) ≤ ω are not equivalent.…”
Section: ) P-quantile Lifetime At the Use Conditionmentioning
confidence: 99%
“…На цей час в стандартах та нормативних матеріалах рекомендуються плани та методики експериментальної оцінки ймовірності безвідмовної роботи об'єктив (си-стем) на основі використання різних теоретичних мо-делей відмов, що приводить до істотної розбіжності оцінок і різним об'ємам випробувань [6][7][8][9].…”
Section: аналіз досліджень і публікацій та постановка проблемиunclassified
“…In Bhattacharyya and Fries (1982), the identical approach in Birnbaum and Saunders (1969a) was viewed as a Wiener process of accumulated fatigue in time (with positive drift parameter μ and diffusion constant τ 2 ), and this leads directly to an I-G distribution. From this derivation, it is shown that a B-S random variable or "event" is actually contained within the I-G model since only positive increments in the growth of the dominant crack are allowed in Birnbaum and Saunders (1969a) (a "negative growth" can be viewed as a repair in the dominant crack, but this event is rare whenever μ τ ).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Another model, the inverse Gaussian distribution (abbreviated by I-G hereafter), was originally used to describe the first passage time in a Brownian motion. However, the inverse Gaussian distribution has been used quite frequently to model reliability data, and the relationship between the B-S and the I-G distributions was first established by Bhattacharyya and Fries (1982). Starting in Section 2, these two distributions will be presented, and the main results, extensions, and summaries from an extensive literature review will be provided.…”
Section: Introductionmentioning
confidence: 99%