新型二段式高效粗加工刀具路径生成

doi:10.11996/JG.j.2095-302X.2025061183

图学学报 ›› 2025, Vol. 46 ›› Issue (6): 1183-1190.DOI: 10.11996/JG.j.2095-302X.2025061183

• 制造产品核心工业软件 • 上一篇下一篇

新型二段式高效粗加工刀具路径生成

刘畅¹(), 马鸿宇¹, 申立勇¹(), 袁春明¹^,², 张博文¹^,², 李世初¹

¹ 中国科学院大学数学科学学院，北京 100049
² 中国科学院数学与系统科学研究院，北京 100190

收稿日期:2025-08-22 接受日期:2025-10-30 出版日期:2025-12-30 发布日期:2025-12-27
通讯作者:申立勇(1977-)，男，教授，博士。主要研究方向为计算机辅助设计、智能技术等。E-mail：lyshen@ucas.ac.cn
第一作者:刘畅(2001-)，男，硕士研究生。主要研究方向为碰撞检测与路径规划。E-mail：liuchang232@mails.ucas.ac.cn
基金资助:
中国科学院战略先导科技专项(XDB0640200);国家自然科学基金(12201606);国家自然科学基金(12371384);国家自然科学基金(12271516)

A novel approach of two-stage high-efficiency rough machining toolpath generation

LIU Chang¹(), MA Hongyu¹, SHEN Liyong¹(), YUAN Chunming¹^,², ZHANG Bowen¹^,², LI Shichu¹

¹ School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
² Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing 100190, China

Received:2025-08-22 Accepted:2025-10-30 Published:2025-12-30 Online:2025-12-27
First author：LIU Chang (2001-), master student. His main research interests cover collision detection, toolpath planning. E-mail：liuchang232@mails.ucas.ac.cn
Supported by:
Strategic Priority Research Program of Chinese Academy of Sciences(XDB0640200);National Natural Science Foundation of China(12201606);National Natural Science Foundation of China(12371384);National Natural Science Foundation of China(12271516)

摘要/Abstract

摘要：

整体开粗是减材制造中的首阶段，通过高效切除毛坯上大部分余量(行业实践通常达70%~90%)，使工件形状和尺寸初步接近成品。其核心在于快速材料去除，直接决定加工效率。此前粗加工中的刀路生成算法主要使用环切方式，虽能得到较好的加工质量，但无法保证加工效率。考虑到这个问题，以及目前数控机床配备自动换刀功能已成主流，提出了一种基于碰撞检测的新型二段式粗加工优化算法。首先利用GPU并行计算进行碰撞检测快速确定可行加工域，并采用大直径刀具实施首段行切(DP)路径实现大范围去料切除；继而通过精准更新残留域边界，切换小直径刀具生成二阶段环切(CP)刀路进行精密环切。实验与加工仿真表明：相较于传统CP模式，该策略在保证加工表面质量的同时显著提升加工效率(增幅>17%)，提供了缓解粗加工阶段质量与效率难以兼顾的核心矛盾的新思路。

关键词: 3轴减材制造, GPU并行加速, 轮廓偏置, 碰撞检测, 路径规划

Abstract:

Rough machining, the initial stage of subtractive manufacturing, rapidly removes the majority of workpiece stock (typically 70%-90% in industry practice) to approximate the final part geometry. Its core objective is high-efficiency material removal, which directly determines overall machining productivity. Conventional roughing toolpath generation algorithms predominantly employ contour-parallel strategies, which ensure satisfactory surface quality but often sacrifice efficiency. To address this given and leveraging the widespread adoption of automatic tool-changing systems in modern CNC (computer numerical control) machines, a novel two-stage roughing optimization algorithm based on collision detection was proposed. The method first utilized GPU-accelerated parallel computing for rapid collision detection to identify feasible machining zones. A large-diameter tool was then deployed to generate direction-parallel (DP) toolpaths in the first stage, enabling aggressive stock removal. Subsequently, the residual stock boundary was precisely updated, and a smaller-diameter tool was engaged to generate contour-parallel (CP) toolpaths for localized precision machining in the second stage. Experimental and simulation results demonstrated that, compared to traditional CP methods, this strategy achieved a 17% improvement in machining efficiency while maintaining surface quality. This work provided new perspectives on resolving the fundamental trade-off between machining quality and processing efficiency during rough machining.

Key words: 3-axis subtractive manufacturing, GPU parallel acceleration, contour-offset, collision detection, toolpath planning

中图分类号:

TG659

刘畅, 马鸿宇, 申立勇, 袁春明, 张博文, 李世初. 新型二段式高效粗加工刀具路径生成[J]. 图学学报, 2025, 46(6): 1183-1190.

LIU Chang, MA Hongyu, SHEN Liyong, YUAN Chunming, ZHANG Bowen, LI Shichu. A novel approach of two-stage high-efficiency rough machining toolpath generation[J]. Journal of Graphics, 2025, 46(6): 1183-1190.

图/表 10

图1 2种加工路径形式((a) 行切路径；(b) 环切路径)

Fig. 1 Two types of machining paths ((a) Direction-parallel toolpath; (b) Contour-parallel toolpath)

图2 方法流程((a) 快速去料；(b) 环切去料)

Fig. 2 Processing methods ((a) Rough machining; (b) Contour-parallel engraving)

图3 加工区域提取((a) 平面可加工深度图；(b) 3D加工区域(蓝色区域为加工可行域)；(c) GPU结构图；(d) GPU上一个计算单元进行的计算：三角面片和刀具几何体碰撞检测)

Fig. 3 Machining region extraction ((a) Planar machinable depth map; (b) 3D machining region (blue area: machining zone); (c) GPU architecture diagram; (d) Computation of collision detection performed by one computing unit on the GPU)

图4 切削刀具类型((a) 平底刀；(b) 圆环刀；(c) 球头刀)

Fig. 4 Cutting tool types ((a) Flat-end mill; (b) Toroidal cutter; (c) Ball-nose end mill)

图5 连通域边界提取((a) 连通区域；(b) 像素边界；(c) 光滑边界)

Fig. 5 Connected domain boundary extraction ((a) Connected region; (b) Pixel boundary; (c) Smoothed boundary)

图6 模拟加工结果((a) 路径1；(b) 路径2；(c) 路径3)

Fig. 6 Machining simulation result ((a) Path 1; (b) Path 2; (c) Path 3)

表1 粗加工参数/mm

Table 1 Rough machining parameters/mm

路径	切削深度		路径间距
路径	快速去料	环切去料	快速去料	环切去料
1	2	1	3	2
2	2	2	3	3
3	2		3

图7 加工路径展示(路径1) ((a) 加工模型；(b) 加工路径；(c) 一层路径)

Fig. 7 Toolpath visualization (Path 1) ((a) Machining model; (b) Toolpath; (c) Single-layer path)

表2 碰撞检测运行时间对比

Table 2 Comparison of collision detection running time

模型	三角面片数量	CPU/s	GPU/s	加速比
1	5501	2513.87	3.61	696.36
2	36431	4007.14	13.33	300.60
3	8361	4753.74	4.56	1042.48
4	4218	3808.53	3.09	1232.53

表3 模拟加工时间对比

Table 3 Comparison of machining simulation time

模型	路径1/s	路径2/s	路径3/s	加工效率增幅/%
模型	路径1/s	路径2/s	路径3/s	路径1	路径2
1	1878.19	1528.57	1934.16	2.89	20.96
2	1261.55	1136.49	1774.28	28.89	35.94
3	944.49	801.68	974.50	3.07	17.73
4	5523.32	4839.06	6308.63	12.44	23.29

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新型二段式高效粗加工刀具路径生成

A novel approach of two-stage high-efficiency rough machining toolpath generation

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