关键词: CAE, 神经网络, 压边力, 优化, 波箔型径向气体轴承, 波纹箔片非线性刚度模型, 有限差分法, 轴承静特性

Abstract: The optimum methods of binder force based on CAE are provided in the analysis. By CAE, the sheet’s stabilities in forming process are described each time. Some stability values of key spots (the easiest instable parts) can be input parameters, and Neural net method is applied to optimize binder force. By this method, it is easy to obtain optimum binder force without special equipment to educate style, and the results are in good agreement with experiments.

Key words: Binder force, CAE, Neural net, Optimization, bearing static performance, bump foil nonlinear stiffness model, bump-type gas foil bearing, finite difference method