Modified iterative approach for predicting machined surface topography in ball-end milling operation
Modified iterative approach for predicting machined surface topography in ball-end milling operation
复制标题
DOI：
10.1007/s00170-021-07245-6
复制
发表时间：
2021-05
期刊：
影响因子：
--
通讯作者：
Ren-quan Wang;Song Zhang;R. Ge;Xiaona Luan;Qing Zhang;Jiachang Wang;Shaolei Lu
中科院分区：
文献类型：
--
作者：
Ren-quan Wang;Song Zhang;R. Ge;Xiaona Luan;Qing Zhang;Jiachang Wang;Shaolei Lu
加工表面形貌预测是优化切削参数的重要且有用的工具。然而，由于切削刃的余摆线运动和计算负担引起的刀具与工件相互作用的复杂性，准确预测球头铣削操作中的加工表面形貌一直极具挑战性。在本研究中，提出了一种改进的迭代方法来解决切削刃扫掠表面与工件离散Z矢量模型之间的交点，该方法用于预测球头铣削操作中的加工表面形貌。首先，利用齐次坐标变换建立了考虑刀具跳动的切削刃扫掠面精确模型。其次，将切削刃扫掠面按照等参数间隔分散成一系列斑块，利用切削刃的最小和最大轴向浸入角提取切入斑块。第三，使用牛顿法求解每个切入面片与离散Z向量之间的交集，用于更新相应离散Z向量的端点。最后，对 AISI P20 钢进行了球头铣削实验，以验证所提出的方法，并研究切削参数对加工表面形貌和粗糙度的影响。预测的加工表面形貌和粗糙度与测量结果非常吻合。此外，在相同的预测精度下，所提出的方法比传统的迭代方法需要更少的计算时间。这项研究还为优化切削参数以控制球头铣削操作中的表面质量提供了指导。
Machined surface topography prediction is an important and useful tool for optimizing cutting parameters. However, accurate prediction of machined surface topography in ball-end milling operation has been extremely challenging, due to the complexity in tool-workpiece interaction induced by the trochoidal motion of cutting edge and computing burden. In this present research, a modified iterative approach was proposed to solve the intersections between the cutting-edge sweeping surface and the discrete Z-vector model of workpiece, which were used to predict the machined surface topography in ball-end milling operation. Firstly, the accurate model of cutting-edge sweeping surface was established utilizing homogeneous coordinate transformation, in which the tool runout was considered. Secondly, the cutting-edge sweeping surface was dispersed into a series of patches in accordance with equal parameter interval, and the in-cut patch was extracted by using the minimum and maximum axial immersion angle of the cutting edge. Thirdly, the intersection between each in-cut patch and discrete Z-vector was solved using the Newton’s method, which was used to update the endpoint of the corresponding discrete Z-vector. Finally, ball-end milling experiments of AISI P20 steel were carried out to validate the proposed approach as well as investigate the effect of cutting parameters on the machined surface topography and roughness. The predicted machined surface topography and roughness were in good agreement with the measured results. Moreover, the proposed approach needs less computing time than the traditional iterative approaches at the same predicting accuracy. This research also provides guidance for optimizing cutting parameters to control surface quality in ball-end milling operation.