高斯分布
高斯过程
正态性
分布(数学)
累积分布函数
转化(遗传学)
数学
联合概率分布
统计物理学
概率密度函数
应用数学
计算机科学
统计
数学分析
物理
基因
化学
量子力学
生物化学
作者
Denis Benasciutti,R. Tovo
标识
DOI:10.1016/j.probengmech.2004.11.001
摘要
The aim of the paper is to propose a method to assess the cycle distribution and the fatigue damage in stationary broad-band non-Gaussian processes; the method is a further development of an existing procedure proposed for Gaussian processes [Int J Fatigue 2002; 24(11)]. By introducing a suitable transformation, we link a non-Gaussian process to an underlying Gaussian one, for which we can estimate the cumulative distribution of counted cycles; the corresponding joint density for the non-Gaussian process is then derived. The analysis of time histories measured on Mountain-bikes in off-road tracks shows that the new method is able to correctly assess the distribution of 'rainflow' counted cycles taking into account the non-normality of the load.
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