A surface slicing planning method based on the K-means clustering algorithm and improved fruit fly optimization algorithm (FOA) is proposed to address the efficiency problem in the surface processing of special shaped workpieces. The NURBS surface reconstruction is performed on the complex surface of the selected workpiece, and the K-means clustering algorithm with the curvature-distance factor is used to subdivide the surface, and the FOA with the hopping strategy is used to plan the optimal connection path for each subdivision with different starting points. This improves the local search capability of the FOA by improving the mixing of different classes that occurs when the surface is subdivided. Finally, the proposed method is demonstrated to be effective for surface slicing by simulating the slicing plan on the constructed heterogeneous workpiece surface, and the shortest connectivity paths are obtained for different starting points.

中文翻译：

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异形工件自由曲面智能切片规划方法研究

针对异形工件表面加工中的效率问题，提出一种基于K均值聚类算法和改进果蝇优化算法（FOA）的表面切片规划方法。对所选工件的复杂曲面进行NURBS曲面重构，采用曲率-距离因子的K-means聚类算法对曲面进行细分，采用跳跃策略的FOA规划最优连接路径对于具有不同起点的每个细分。这通过改进细分表面时发生的不同类别的混合来提高 FOA 的局部搜索能力。最后，