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针对考虑几何分散性的涡轮盘低循环疲劳(LCF)寿命概率分析中几何参数多、几何随机变量难确定、分布特征获取困难、模型需自动更新及计算成本高的问题,提出几何分散性的概率处理方法:采用试验设计方法对涡轮盘结构所有几何参数进行灵敏度分析,筛选出对应力影响较大的关键几何参数作为随机变量,使用K-S(Kolmogorov-Smirnov)方法确定其分布类型和特征参数,最后建立代理模型进行Monte Carlo概率分析.基于此方法,开发出了涡轮盘概率分析系统,在该系统中筛选得到某发动机GH720Li涡轮盘内径、外径、盘缘厚度3个结构参数作为几何随机变量,完成对LCF寿命的概率分析工作得到寿命-可靠度分布曲线.分析结果表明涡轮盘外径对LCF寿命有较大影响.
Aiming at the problem of geometrical parameters, geometric random variables difficult to determine, difficulty in obtaining distribution features, the model to be automatically updated and high computational cost in the probability analysis of low discard fatigue life (LCF) for turbine disc considering geometrical dispersion, the probability of geometrical dispersion Processing method: The sensitivity of all geometric parameters of turbine disk structure was tested by experimental design method, key geometric parameters with large influence on stress were screened out as random variables, KS (Kolmogorov-Smirnov) method was used to determine the distribution type and characteristic parameters, finally This paper established a probabilistic Monte Carlo analysis of the agent model.Based on this method, a turbine disk probability analysis system was developed, in which three structural parameters of GH720Li turbine disk inner diameter, outer diameter and rim thickness were selected as geometric random variables, The life-reliability curve of the lifetime of LCF was completed, and the results showed that the outer diameter of turbine disk had a significant effect on the life of LCF.