计入RBFNN重构油膜力的发动机连杆变形分析
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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)


Deformation analysis of engines’ connecting-rods including oil film forces reconstructed by RBFNN
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    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。

    Abstract:

    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.

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孟凡明.计入RBFNN重构油膜力的发动机连杆变形分析[J].重庆大学学报,2011,34(7):8-13.

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  • 收稿日期:2010-02-16
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