具有不确定输入的振动结构的可靠性

Y. Ben-Haim
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引用次数: 19

摘要

摘要在动态载荷信息严重缺乏的情况下,我们对振动系统的可靠性进行了评估。我们强调不确定性的非概率信息缺口模型,它适用于严重缺乏信息。当某些概率信息可用时,我们展示了如何将其纳入混合概率/信息差距分析。我们概述了鲁棒可靠性理论,在先验信息不足以验证概率密度选择的情况下,鲁棒可靠性取代了概率可靠性。我们还举例说明了混合概率/信息缺口可靠性分析。最后,我们使用“赌徒定理”和规避风险的思想来提供系统在不确定环境中的性能的全面定量评估。尼尔斯·玻尔说:“预测总是困难的,尤其是对未来的预测。”但我们总是根据从不完整信息中推断出来的假设来行动。从抛硬币到国际冲突,我们都是基于部分信息来预测结果。当我们有丰富的经验时,比如在已知和受控条件下的环境振动,我们可以做出可靠的判断。但在独特和不熟悉的环境中,我们的先验知识严重有限,因此我们必须更加谨慎。在分析与我们所知甚少的罕见和特殊事件相关的关键部件和系统的可靠性时,我们必须尽可能避免无法验证的假设。特别是,我们必须尽可能可靠地表示不确定性,而不需要额外的假设。本文讨论了为此目的而开发的一种可靠度分析方法。从信息上讲,天下没有免费的午餐,因此基于有限先验信息的分析只能做出适度的预测。然而,关键的一点是分析本身是可靠的,而不是虚幻的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliability of vibrating structures with uncertain inputs
10 6 Summary 12 Abstract We evaluate the reliability of vibrating systems subject to severely deficient information about the dynamic loads. We stress non-probabilistic information-gap models of uncertainty, which are adapted to severe lack of information. When some probabilistic information is avail- able, we show how it can be incorporated in a hybrid probabilistic/info-gap analysis. We outline the theory of robust reliability, which replaces probabilistic reliability in those situations where prior information is insufficient to verify the choice of a probability density. We also illustrate a hybrid probabilistic/info-gap reliability analysis. Finally, we use the "gambler's theorem" and the idea of aversion to risk to provide an overall quantitative assessment of the performance of a system in an uncertain environment. 1 Modelling the Unknown "Prediction", said Niels Bohr, "is always difficult, especially of the future." But we act all the time on suppositions extrapolated from incomplete information. From coin-flips to international conflicts, we predict outcomes based on partial information. When we have extensive experience, like in ambient vibrations under known and controlled conditions, we can make reliable asser- tions. But in unique and unfamiliar circumstances we have severely limited prior knowledge, so we must be much more circumspect. In analyzing the reliability of critical components and systems with respect to rare and extraordinary events, about which we know very little, we must avoid unverifiable assumptions as much as possible. In particular, we must represent the uncertainties as reliably as possible, without extraneous assumptions. In this paper we discuss a method of reliability analysis which is developed for this purpose. There is no free lunch, informationally speaking, so an analysis based on limited prior information will be able to make only modest predictions. However, the crucial point is that the analysis itself be reliable and not illusory.
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