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Generalized numerical pressure distribution model for smoothing polishing of irregular midspatial frequency errors

机译:平滑中频不规则频率误差的广义数值分布模型

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摘要

The smoothing effect of the rigid lap plays an important role in controlling midspatial frequency errors (MSFRs). At present, the pressure distribution between the polishing pad and processed surface is mainly calculated by Mehta's bridging model. However, this classic model does not work for the irregular MSFR. In this paper, a generalized numerical model based on the finite element method (FEM) is proposed to solve this problem. First, the smoothing polishing (SP) process is transformed to a 3D elastic structural FEM model, and the governing matrix equation is gained. By virtue of the boundary conditions applied to the governing matrix equation, the nodal displacement vector and nodal force vector of the pad can be attained, from which the pressure distribution can be extracted. In the partial contact condition, the iterative method is needed. The algorithmic routine is shown, and the applicability of the generalized numerical model is discussed. The detailed simulation is given when the lap is in contact with the irregular surface of different morphologies. A well-designed SP experiment is conducted in our lab to verify the model. A small difference between the experimental data and simulated result shows that the model is totally practicable. The generalized numerical model is applied on a Φ500 mm parabolic surface. The calculated result and measured data after the SP process have been compared, which indicates that the model established in this paper is an effective method to predict the SP process.
机译:刚性搭接的平滑效果在控制中空频率误差(MSFR)中起着重要作用。目前,抛光垫和加工表面之间的压力分布主要是通过Mehta的桥接模型来计算的。但是,此经典模型不适用于不规则的MSFR。本文提出了一种基于有限元方法(FEM)的广义数值模型来解决这一问题。首先,将平滑抛光(SP)过程转换为3D弹性结构FEM模型,并获得控制矩阵方程。借助于应用于控制矩阵方程的边界条件,可以获得垫的节点位移矢量和节点力矢量,从中可以提取压力分布。在部分接触条件下,需要迭代方法。给出了算法程序,并讨论了广义数值模型的适用性。当棉卷与不同形态的不规则表面接触时,将给出详细的模拟。在我们的实验室中进行了精心设计的SP实验以验证模型。实验数据与模拟结果之间的微小差异表明该模型是完全可行的。将广义数值模型应用于Φ500mm抛物面。对SP过程的计算结果和实测数据进行了比较,表明本文建立的模型是预测SP过程的有效方法。

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