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Towards Efficient Milling of Multi-Cavity Aeronautical Structural Parts Considering ACO-Based Optimal Tool Feed Position and Path

机译:考虑基于ACO的最优工具进料位置和路径朝多腔航空结构部件的高效研磨

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摘要

Cavities are typical features in aeronautical structural parts and molds. For high-speed milling of multi-cavity parts, a reasonable processing sequence planning can significantly affect the machining accuracy and efficiency. This paper proposes an improved continuous peripheral milling method for multi-cavity based on ant colony optimization algorithm (ACO). Firstly, by analyzing the mathematical model of cavity corner milling process, the geometric center of the corner is selected as the initial tool feed position. Subsequently, the tool path is globally optimized through ant colony dissemination and pheromone perception for path solution of multi-cavity milling. With the advantages of ant colony parallel search and pheromone positive feedback, the searching efficiency of the global shortest processing path is effectively improved. Finally, the milling programming of an aeronautical structural part is taken as a sample to verify the effectiveness of the proposed methodology. Compared with zigzag milling and genetic algorithm (GA)-based peripheral milling modes in the computer aided manufacturing (CAM) software, the results show that the ACO-based methodology can shorten the milling time of a sample part by more than 13%.
机译:空腔是航空结构部件和模具中的典型特征。对于高速铣削多腔部件,合理的加工序列规划可以显着影响加工精度和效率。本文提出了一种基于蚁群优化算法(ACO)的多腔连续外围铣削方法。首先,通过分析腔角铣削过程的数学模型,拐角的几何中心被选为初始工具进料位置。随后,通过蚁群传播和信息素对多腔铣削路径溶液进行全局优化工具路径。随着蚁群并行搜索和信息素正反馈的优点,有效地提高了全局最短处理路径的搜索效率。最后,将航空结构部件的铣削编程作为样品,以验证所提出的方法的有效性。与计算机辅助制造(CAM)软件中的Zigzag铣削和基于遗传算法(GA)基于外围铣削模式相比,结果表明,基于ACO的方法可以将样品部分的铣削时间缩短超过13%。

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