摘要
提出了一种发动机连杆瞬态变形分析的耦合分析法。设计了一个3层径向基神经网络(RBFNN),来重构活塞组件的二维油膜力,通过连杆的耦合方程,得到了连杆两端的耦合力,进而借助商用有限元软件ANSYS分析了发动机连杆的瞬态变形,同时该耦合方法的有效性被证实。仿真结果表明:在计入二维活塞组件油膜力作用下,连杆最大变形可提前或落后于压缩行程的下止点。
A coupling analysis method is proposed for the transient deformation of engines＇ connecting-rods.A radial base function neural network（RBFNN） with three layers is designed to reconstruct the two-dimensional oil film forces.Forces acting on the two ends of the connecting-rod are achieved through coupling equations for it.Further,finite element analyses of transient deformation for the connecting-rod are made through software ANSYS.Meanwhile,the validity of the proposed method is demonstrated.Numerical results show the maximum deformation of a rotary connecting rod occurs before or behind the bottom dead center at compression stroke when the two-dimensional oil film forces are considered.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第7期8-13,共6页
Journal of Chongqing University
基金
国家自然科学基金资助项目(50975297)
教育部博士点新教师基金项目(200806111020)
重庆市教委基金资助项目(KJ08A11)
关键词
变形
连杆
耦合
二维油膜力
径向基神经网络
有限元
deformation
connecting-rod
coupling
two-dimensional oil film forces
radial base function neural network
finite element
