Optimization of machining path for integral impeller side milling based on SA-PSO fusion algorithm in CNC machine tools

IF 2 Q2 ENGINEERING, MECHANICAL
Yu Zhao
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引用次数: 0

Abstract

The five axis linkage Computer Numerical Control machine tool for integral impeller can achieve blade machining through side milling, which is of great significance for improving the machining accuracy, production efficiency, and long-term stability of integral impeller blades. This study is based on non-uniform rational B-spline curves and aims to reduce the surface over cutting or under cutting of integral turbine blades. The path planning of non deployable ruled surfaces was analyzed in depth through side milling, and the path planning model of the side milling cutter axis was solved through a fusion algorithm of simulated annealing algorithm and particle swarm optimization algorithm, in order to find the optimal path through iterative process. As the number of iterations increased, the error values of particle swarm optimization algorithm and simulated annealing particle swarm optimization fusion algorithm gradually decreased, with convergence times of about 7 and 6, respectively. The stable error value of the fusion algorithm was 0.253, which is 30.45% lower than that of the particle swarm optimization algorithm. The optimal number of iterations for solving the model using particle swarm optimization algorithm and fusion algorithm was the 7th, with range values of 0.0213 and 0.0165 mm, respectively. The tool axis trajectory surface optimized by the fusion algorithm was closer to the tool axis motion state compared to the initial tool axis trajectory surface. The range of the sum of mean squared deviations for single and global cutting was 0.0011–0.0198 and 0.046–0.0341, but the overall error value was relatively small. This study effectively reduces the envelope error of machining tools and improves machining accuracy, thereby solving the principle error of non expandable ruled surfaces in the motion trajectory of the blade axis of the integral turbine. This provides new research ideas for the intelligent development of Computer Numerical Control machining technology.
基于 SA-PSO 融合算法的数控机床整体叶轮侧铣加工路径优化
整体叶轮五轴联动计算机数控机床可通过侧铣实现叶片加工,对提高整体叶轮叶片的加工精度、生产效率和长期稳定性具有重要意义。本研究基于非均匀有理 B-样条曲线,旨在减少整体式叶轮叶片的表面过切或欠切。通过侧铣深入分析了非展开规则曲面的路径规划,并通过模拟退火算法和粒子群优化算法的融合算法求解侧铣刀轴的路径规划模型,从而通过迭代过程找到最优路径。随着迭代次数的增加,粒子群优化算法和模拟退火粒子群优化融合算法的误差值逐渐减小,收敛时间分别约为 7 和 6。融合算法的稳定误差值为 0.253,比粒子群优化算法低 30.45%。使用粒子群优化算法和融合算法求解模型的最佳迭代次数为第 7 次,范围值分别为 0.0213 毫米和 0.0165 毫米。与初始刀轴轨迹面相比,融合算法优化后的刀轴轨迹面更接近刀轴运动状态。单次切削和全局切削的均方差之和范围分别为 0.0011-0.0198 和 0.046-0.0341 ,但总体误差值相对较小。该研究有效降低了加工刀具的包络误差,提高了加工精度,从而解决了整体式水轮机叶片轴运动轨迹中不可扩展尺面的原理误差问题。这为计算机数控加工技术的智能化发展提供了新的研究思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Mechanical Engineering
Frontiers in Mechanical Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
4.40
自引率
0.00%
发文量
115
审稿时长
14 weeks
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