摘要
针对截尾寿命试验数据缺少随机变量尾部分布和常规截尾数据分析对长寿命区高可靠度估计不准确的情况 ,根据极值统计学原理 ,给出一个结构元件疲劳寿命分布的极值模型。文中利用全样本试验数据构造截尾试验 ,采用传统的极大似然估计法给出寿命总体的分布形式 ,分析结构元件疲劳寿命的极值分布情况 ,建立一个新的寿命分布的极值模型 ,对长寿命区的寿命分布形式和高可靠度的估算有明显优势。三个算例表明 。
In censored life tests for structural components, the cumulative density functions (CDF) of fatigue life obtained by conventional methods are not accurate and reasonable in their tail distributions, which are critical for the failure estimation of high-reliability components. Considering the stochastic nature of environmental influence and the randomicity of geometrical and mechanical properties of structural materials, fatigue life is a random variable and usually assumed to follow logarithmic normal distribution approximately. The distributions of extreme life are analyzed according to statistics of extremes that deduces the extreme values ofthe exponential type of initial distributions asymptotically follow the first (Gumbel) extreme distribution. Consequently, an extreme-based life distribution model is presented which has a more precise distribution especially in the long life region. Three examples are used to demonstrate the new life distribution model and the numerical results show that it has a better agreement with the experimental data than the conventional maximum likelihood method.
出处
《机械强度》
CAS
CSCD
北大核心
2004年第z1期237-240,共4页
Journal of Mechanical Strength
基金
国家自然科学基金 (1 0 3770 0 7)
航空科学基金 (0 3A52 0 0 5)资助项目~~
关键词
截尾试验
极值统计
疲劳寿命
寿命分布
Censored test
Statistics of extreme
Fatigue life
Life distribution
