摘要
提出一种人工智能方法进行航空轴承疲劳可靠性分析.通过二次多项式近似拟合温度场效应,建立热弹流润滑效应下航空轴承接触应力分析模型,同时考虑热弹流润滑效应、材料属性以及疲劳强度修正系数的随机性,结合应力-强度干涉理论,运用人工神经网络法完成疲劳可靠性分析,基于改进的一次二阶矩法完成可靠性灵敏度分析.数值算例表明,建立的可靠性分析模型能正确反映热弹流润滑效应对航空轴承接触疲劳的影响.与传统蒙特卡罗方法相比,提出的智能方法具有良好的全局搜索能力和高效的计算性能,并通过无交互方差分析滚动轴承疲劳试验对可靠性灵敏度分析结果进行了验证.
An intelligent method is proposed to complete the contact fatigue reliability analysis of aviation bearings. The temperature field is approximated using quadratic polynomial with intercrossing term,and the stress model under thermal elastohydrodynamic lubrication （ EHL） is set up. Considering the randomness of the thermal EHL,material properties and fatigue strength correction factors,the probabilistic reliability analysis model is established using artificial neural network （ ANN）,and the reliability sensitivity analysis is completed based on the advanced first order second moment （ AFOSM） . The numerical example shows that the established probabilistic reliability analysis model could correctly reflect the effect of the thermal EHL on contact fatigue of aviation bearings,and the proposed intelligent method has an excellent global search capability as well as a highly efficient computing performance compared with the traditional Monte Carlo method,and then the results are verified with the fatigue life test of rolling bearings considering the non-interacting variance analysis.
作者
金燕
刘少军
JIN Fare;LIU Shao-jun(State Key Laboratory for High Performance Complex Manufacturing/School of Mechanical and Electrical Engineering,Central South University,Changsha 410083,China;Institute of Mechanical and Auto Engineering,Changzhou Vocational Institute of Engineering,Changzhou 213164,China)
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2018年第6期850-855,共6页
Journal of Northeastern University(Natural Science)
基金
国防预研项目(8130208)
关键词
接触疲劳
热弹流润滑
航空轴承
可靠性
人工神经网络
遗传算法
contact fatigue
thermal elastohydrodynamic lubrication （ EHL）
aviation bearing
reliability
artificial neural network （ANN）
genetic algorithm （ GA）
