【摘要】 为了使机械结合面切向接触阻尼实验数据便于在机械结构 CAD中应用 ,本文基于人工神经网络的非线性映射能力 ,提出了机械结合面切向接触阻尼基础数据的神经网络结构化建模方法 ,并进行了实例建模。结果表明 ,该方法实用、有效 ,建模精度和建模效率较高 ,而且集传统建模与建库思想于一体 ,实现了多种结合条件下的机械结合面切向接触阻尼基础数据的统一建模更多还原

【Abstract】 The damping at joint surfaces plays an important part in a machine structure. It is influenced by many factors, for example, the pressure at joint interfaces, joint materials, the machining method and the roughness, as well as vibrating frequency. The relationship between them is nonlinear and complicated. The characteristics of above influencing factors were described and the neural network modelling method for the basic data of the tangential contact damping of joint surfaces acquired in experiments was presented in this paper. The obtained model by this method can be effectively and conveniently used in the design of a machine structure. This method has been proved feasible by a modelling example, and the modelling has a high efficiency and precision.更多还原