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Nearly arc-length tool path generation and tool radius compensation algorithm research in FTS turning

机译:FTS车削中近弧长刀具路径生成及刀具半径补偿算法研究

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In the non-rotational symmetrical microstrcture surfaces generation using turning method with Fast Tool Servo(FTS), non-uniform distribution of the interpolation data points will lead to long processing cycle and poor surface quality. To improve this situation, nearly arc-length tool path generation algorithm is proposed, which generates tool tip trajectory points in nearly arc-length instead of the traditional interpolation rule of equal angle and adds tool radius compensation. All the interpolation points are equidistant in radial distribution because of the constant feeding speed in X slider, the high frequency tool radius compensation components are in both X direction and Z direction, which makes X slider difficult to follow the input orders due to its large mass. Newton iterative method is used to calculate the neighboring contour tangent point coordinate value with the interpolation point X position as initial value, in this way, the new Z coordinate value is gotten, and the high frequency motion components in X direction is decomposed into Z direction. Taking a typical microstructure with 4μm PV value for test, which is mixed with two 70μm wave length sine-waves, the max profile error at the angle of fifteen is less than 0.01μm turning by a diamond tool with big radius of 80μm. The sinusoidal grid is machined on a ultra-precision lathe succesfully, the wavelength is 70.2278μm the Ra value is 22.81nm evaluated by data points generated by filtering out the first five harmonics.
机译:在使用快速工具伺服(FTS)车削方法生成的非旋转对称微结构表面中,插值数据点的不均匀分布将导致较长的加工周期和较差的表面质量。为了改善这种情况,提出了一种近似弧长的刀具路径生成算法,该算法生成近似弧长的刀尖轨迹点,代替了传统的等角插补规则,并增加了刀具半径补偿。由于X滑块的进给速度恒定,所有插补点的径向分布都等距,高频刀具半径补偿分量同时位于X方向和Z方向,这使得X滑块由于质量大而难以遵循输入顺序。采用牛顿迭代法,以插值点X位置为初始值,计算相邻轮廓切点坐标值,得到新的Z坐标值,将X方向的高频运动分量分解为Z方向。以一个典型的具有4μmPV值的微观结构进行测试,并与两个70μm波长的正弦波混合,用半径为80μm的金刚石工具车削时,在15度角处的最大轮廓误差小于0.01μm。成功地在超精密车床上加工了正弦网格,其波长为70.2278μm,Ra值为22.81nm(通过滤除前五个谐波产生的数据点来评估)。

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