首页 | 本学科首页   官方微博 | 高级检索  
     检索      

TC4钛合金铣削性能分析及多目标参数优化
引用本文:鲍骏,白海清,任礼,安熠蔚,秦望.TC4钛合金铣削性能分析及多目标参数优化[J].科学技术与工程,2021,21(36):15400-15410.
作者姓名:鲍骏  白海清  任礼  安熠蔚  秦望
作者单位:陕西理工大学机械工程学院;陕西省工业自动化重点实验室;陕西理工大学机械工程学院
摘    要:如何更好对钛合金材料进行切削加工,以及在保证高切削加工效率,高精度与低切削力的基础上,如何对加工参数进行合理选取一直是钛合金切削加工领域中的一大研究热点。为了探究TC4钛合金的铣削性能与铣削参数优化问题,设计了正交铣削试验方案,分析了铣削参数即背吃刀量,侧吃刀量,主轴转速,进给速度对其铣削力与铣削后表面粗糙度的影响规律。将铣削力,表面粗糙度与材料去除率作为优化目标,建立了多目标优化模型,在Pareto算法的基础上,采用了一种简捷的方法对模型进行求解,并通过试验验证了该方法的可行性。结果显示,对铣削力的影响程度中,背吃刀量影响最大,随后是侧吃刀量与主轴转速,进给速度影响程度最小;对表面粗糙度的影响程度中,进给速度影响最大,其次是侧吃刀量与背吃刀量,主轴转速影响程度最小;Pareto算法所得的参数组通过试验验证,与正交试验组相比,各项指标数值均在较优位置。

关 键 词:TC4钛合金、铣削、铣削力、表面粗糙度、材料去除率、参数优化。
收稿时间:2021/3/2 0:00:00
修稿时间:2021/10/12 0:00:00

Analysis of milling performance of TC4 titanium alloy and Optimization of multi-objective parameters
Bao Jun,Bai Haiqing,Ren Li,An Yiwei,Qin Wang.Analysis of milling performance of TC4 titanium alloy and Optimization of multi-objective parameters[J].Science Technology and Engineering,2021,21(36):15400-15410.
Authors:Bao Jun  Bai Haiqing  Ren Li  An Yiwei  Qin Wang
Institution:College of Mechanical Engineering,Shaanxi University of Technology,HanZhong Shaanxi
Abstract:How to better machining titanium alloy materials, and on the basis of ensuring high machining efficiency, high precision and low cutting force, how to reasonably select machining parameters has been a major research focus in the field of titanium alloy machining. In order to explore the milling performance and milling parameter optimization of TC4 titanium alloy, an orthogonal milling experiment scheme was designed. The effects of milling parameters such as milling depth, milling width, spindle speed and feed speed on milling force and surface roughness were analyzed. Taking milling force, surface roughness and material removal rate as optimization objectives, a multi-objective optimization model is established. Based on Pareto algorithm, a simple method is adopted to solve the model, and the feasibility of the method is verified by experiments. The results show that the milling depth has the greatest influence on the milling force, followed by the milling width and spindle speed, and the feeding speed has the least influence.Among the influences on surface roughness, feed speed has the greatest influence, followed by milling width and milling depth, and spindle speed has the least influence.The parameter group obtained by Pareto algorithm has been verified by experiments. Compared with the orthogonal experimental group, all the index values are in an optimal position.
Keywords:TC4 titanium alloy  milling  milling force  surface roughness  material removal rate  parameter optimization  
点击此处可从《科学技术与工程》浏览原始摘要信息
点击此处可从《科学技术与工程》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号