A Bayesian analysis of fatigue data
A Bayesian analysis of fatigue data
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DOI：
10.1016/j.strusafe.2009.08.001
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发表时间：
2010-01-01
影响因子：
5.8
通讯作者：
Penta, Francesco
中科院分区：
文献类型：
--
作者：
Guida, Maurizio;Penta, Francesco
本文的目的是在疲劳试验的背景下，有利于贝叶斯推理的参数。事实上，寿命测试在机械系统的设计中起着核心作用，因为它们的结构可靠性部分取决于材料的疲劳强度，这需要通过实验来确定。然而，经典的统计分析，可以导致有限的实际用途的结果时，测试的样本数是小的。相反，尽管在这种情况下很少有人关注它，但贝叶斯方法可以通过将测试数据与理论研究和/或以前的实验结果中提供的技术知识相结合，从而提供更准确的估计，从而有助于节省时间和金钱。因此，对于钢合金的情况下，通常可用的技术知识的讨论，并提出了方法，以适当的形式将其形式化的先验可信度密度函数。此外，所提出的贝叶斯程序的性能进行了分析的基础上的模拟研究，表明它们可以大大优于传统的代价是适度增加的计算工作量。(C)2009爱思唯尔有限公司保留所有权利。
The aim of the present paper is to bring arguments in favour of Bayesian inference in the context of fatigue testing. In fact, life tests play a central role in the design of mechanical systems, as their structural reliability depends in part on the fatigue strength of material, which need to be determined by experiments. The classical statistical analysis, however, can lead to results of limited practical usefulness when the number of specimens on test is small. Instead, despite the little attention paid to it in this context, Bayes approach can potentially give more accurate estimates by combining test data with technological knowledge available from theoretical studies and/or previous experimental results, thus contributing to save time and money. Hence, for the case of steel alloys, a discussion about the usually available technological knowledge is presented and methods to properly formalize it in the form of prior credibility density functions are proposed. Further, the performances of the proposed Bayesian procedures are analysed on the basis of simulation studies, showing that they can largely outperform the conventional ones at the expense of a moderate increase of the computational effort. (C) 2009 Elsevier Ltd. All rights reserved.