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Progressive segmentation for MRR-based feed-rate optimization in CNC machining

机译:CNC加工中MRR基饲料速率优化的逐步分割

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Keeping a constant cutting force in CNC machining is very important for obtaining better stability of cutting operation and improving topography, texture and geometry of the machined surface. This paper presents a feed-rate optimization approach based on Material Removal Rate (MRR). Given a tool-path with predefined feed-rates, the geometry of raw material, and the shape of cutter, the histogram of MRR in very fine resolution can be efficiently computed by using a GPU-based geometric modeling kernel. Starting from the evaluation given on the finest histogram of MRR, error-controlled subdivision algorithms are developed to progressively segment the tool-path into user-specified number of sub-regions. Different feed-rates are assigned to different sub-regions so that nearly constant MRR can be achieved while keeping the shape of the given tool-path unchanged. Experimental tests taken on real examples verify the effectiveness of this method.
机译:保持CNC加工中的恒定切割力对于获得更好的切割操作稳定性和改善加工表面的地形,纹理和几何形状非常重要。本文介绍了基于材料去除率(MRR)的进料速率优化方法。给定具有预定义饲料速率的工具路径,通过使用基于GPU的几何建模内核,可以有效地计算原料的几何形状和切割器的形状,MRR的直方图非常精细分辨率。从MRR的最佳直方图给出的评估开始,开发错误控制的细分算法以逐步将工具路径逐行分割为用户指定的子区域。不同的饲料速率被分配给不同的子区域,使得可以在保持给定工具路径的形状不变的同时实现几乎恒定的MRR。实际示例采用的实验试验验证了该方法的有效性。

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