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The estimation with Artificial Neural Networks of some quality parameters for the surfaces processed by superfinishing

机译:用超缺陷处理的表面的一些质量参数的人工神经网络估计

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This paper presents a study on the quality parameters obtained by superfinishing. The quality is characterized by the roughness. They are dependent on the following process parameters: circular feed, the contact pressure between the piece and the tool, frequency of oscillation of the tool, the coverage degree between the tool and the piece and the basic time. Because the dependence between inputs and outputs is a nonlinear one, in this paper we used an artificial feed forward neural network (ANN). The ANN is trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. The ANN is used to estimate some parameters from future experiments of the mechanical process.
机译:本文提出了超缺陷获得的质量参数的研究。质量的特点是粗糙度。它们依赖于以下工艺参数:圆形进料,件之间的接触压力和工具之间的接触压力,工具振荡的频率,工具和件之间的覆盖度和基本时间。因为输入和输出之间的依赖性是非线性的,因为在本文中,我们使用了人工馈送前向神经网络(ANN)。 ANN通过BackPropagation算法培训,使用从机械过程中测量的训练模式数据。 ANN用于估计来自机械过程的未来实验的一些参数。

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