基于动力学仿真的螺旋铣孔切削参数优化研究

发布时间：2018-03-20 11:47

本文选题：螺旋铣孔　切入点：遗传算法　出处：《湖南工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：螺旋铣孔作为一种先进的制孔技术已被广泛应用于航空航天、汽车制造、轨道交通等领域。螺旋铣孔过程中,刀具几何参数、工件材料的切削性能及铣孔参数等对切削力、待加工孔表面质量和切削稳定性等会产生重大影响。本论文将重点探讨螺旋铣孔动力学建模、孔群加工路径优化及单个孔切削参数优化等问题,目的是为了实现高效、高质量螺旋铣孔,主要研究内容如下:首先,通过对螺旋铣孔切削机理研究发现,螺旋铣孔中存在侧刃周铣和底刃插铣两种切削形式。在此基础上,通过对螺旋切削刃离散化处理,实现了螺旋铣孔动态切削力预测。与此同时,通过采用数值方法计算平均方向力系数,推导出了一种由轴向每齿进给量/切向每齿进给量、主轴转速表示的新稳定性叶瓣图。切削力与颤振稳定性验证试验结果显示,本文所构建的切削力及颤振稳定性预测模型的正确性。基于开发的仿真程序,系统地分析了螺旋铣孔切削参数对切削力和切削稳定性的影响,得到了可用于指导实际工程应用的有益的结论。其次,通过研究发现,螺旋铣孔优化问题可分解为孔群路径优化与单孔切削参数优化两个子问题,而孔群加工路径优化本质上就是一个典型的TSP问题。在深入分析现有求解TSP问题的诸多方法后,基于经典的遗传算法,本文提出了一种新的混合改进型遗传算法,该算法通过采用具有变化惩罚项的适应度函数,用来指导遗传搜索,并从蚁群算法早期产生的蚂蚁序列中选择优良个体组成初始解,构建质量更高、多样性更好的初始种群,提高了算法的效率和精度。通过对比三种算法的优化仿真结果及进行相关实验,证实了该算法的正确性与高效性。最后,针对单孔切削参数优化问题,建立了以加工效率为目标函数、以切削参数为设计变量,综合考虑切削力、切削功率、表面形貌及切削稳定性等为约束条件的非线性优化模型,提出了一种变搜索域的优化求解算法,该算法可以通过改变求解过程中搜索域的范围,快速得到符合要求的切削参数。优化试验结果证实了该优化模型及其求解算法的正确性和有效性,可为高效螺旋铣孔提供一种可行的技术解决方案。
[Abstract]:Helical milling is an advanced drilling technology has been widely used in aerospace, automobile manufacturing, rail transportation and other fields. The helical milling process, tool geometry, workpiece materials, cutting performance and milling parameters on cutting force, the hole to be machined surface quality and cutting stability will produce significant effect. This paper focuses on Dynamic Modeling of helical milling, holes machining path optimization and single hole cutting parameter optimization problem, the purpose is to realize high efficiency, high quality of helical milling, the main research contents are as follows: firstly, based on the helical milling cutting mechanism research, the side edge and the bottom edge milling insert two kinds of cutting milling form helical milling. On this basis, through the spiral cutting edge discretization, the cutting force of the helical milling dynamic prediction. At the same time, calculate the average direction of force by using numerical method The coefficient, and derives a by axial feed per tooth / tangential feed per tooth, said the new spindle speed stability lobes. The test results of the cutting force and the flutter stability shows that the correctness of the model to predict the cutting force and the flutter stability of the simulation program. Based on the development of the parameters of helical milling cutting on cutting force and stability of the system analysis, the conclusions can be used to guide the practical engineering application. Secondly, through the study found that the helical milling optimization problem can be decomposed into two sub problems: Kong Qun path optimization and optimization of cutting parameters of single hole, and the holes machining path optimization essence is a typical TSP problem. In many ways the in-depth analysis of the existing TSP problems, based on the classical genetic algorithm, this paper proposes a new improved hybrid genetic algorithm, the algorithm. The fitness function with the change of the penalty term, used to guide the genetic search, and select excellent individuals from the initial solution sequence of ant ant colony algorithm produced in the early stage, the construction quality is higher, the initial population diversity better, improve the efficiency and precision of the algorithm. Through the simulation optimization and comparison of three algorithms the related experiments confirmed the correctness and effectiveness of this algorithm. Finally, to solve the optimization problem of single hole cutting parameters is established based on the machining efficiency as the objective function, the cutting parameters as design variables, considering cutting force, cutting power, nonlinear optimization model of surface morphology and cutting stability as constraint conditions, put forward a variable domain search optimization algorithm, the algorithm can change the search range in the solving process, can meet the requirements of fast cutting parameters. The optimization results confirmed The correctness and effectiveness of the optimization model and its solution algorithm can provide a feasible technical solution for high efficiency spiral milling holes.

【学位授予单位】：湖南工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG54

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