工程科学与技术2024，Vol.56Issue(4)：238-249,12.DOI:10.12454/j.jsuese.202201000
多因素影响下基于Bagging-NSGAⅡ的数控铣削稳定性预测与优化研究
Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging-NSGA Ⅱ Under the Influence of Multiple Factors
摘要
Abstract
The occurrence of chatter in the milling process is a key factor limiting the efficiency and quality of machining.The stability of milling depends mainly on the process parameters and the dynamic characteristics of the tool-workpiece system;however,the system dynamics vary with the machining position and tool properties.Considering these multiple influencing factors,herein,a method is proposed to predict the milling sta-bility and determine optimal machining parameters based on a bootstrap aggregating(bagging)procedure and the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ).First,an orthogonal experimental design is used to divide the working space of the machine tool into different machin-ing positions.Under each position,impact testing is then carried out at the tool tip for different tool-overhang lengths to obtain the corresponding frequency response functions(FRFs).Then,limiting axial cutting depth aplim values are theoretically predicted using the tool-tip FRFs and ma-chining parameters.Using sample information,the bagging algorithm is applied to establish a model for predicting aplim,in which the inputs are the displacements of the moving parts(x,y,z),tool diameter(d),tool-overhang length(h),spindle speed(n),cutting width(ae),and feed rate per tooth(fz).Taking these process parameters(x,y,z,d,h,n,ap,ae,fz)as design variables,a multi-objective optimization model is constructed to bal-ance machining efficiency and tool life.Additionally,the pre-established aplim prediction model is used to express the milling-stability constraint.The multi-objective optimization model is then solved using NSGA-Ⅱ,and the Pareto-optimal set is obtained.Finally,the entropy weight meth-od and the technique for order preference by similarity to an ideal solution(TOPSIS)are combined to select a unique optimal solution from the Pareto-optimal set.A three-axis vertical machining center was used to carry out a case study.The prediction accuracy of the established bagging model for aplim was 2.99％,and no chatter was observed when performing a milling test with the determined optimal process parameters.These experimental results validate the feasibility of the proposed method for predicting milling stability and selecting optimal process parameters under multiple influencing factors.关键词
铣削稳定性/工艺参数优化/多目标优化模型/刀具悬伸量/引导聚集算法/NSGA-Ⅱ遗传算法Key words
milling stability/process parameter optimization/multi-objective optimization model/tool overhang/bootstrap aggregating al-gorithm/NSGA-Ⅱ genetic algorithm分类
金属材料引用本文复制引用
邓聪颖,游倩,赵洋,林丽君,殷国富..多因素影响下基于Bagging-NSGAⅡ的数控铣削稳定性预测与优化研究[J].工程科学与技术,2024,56(4):238-249,12.基金项目
国家自然科学基金项目(51705058) （51705058）
四川省科技计划资助项目(2023YFQ0035) （2023YFQ0035）
重庆市教委科学技术研究项目(KJQN202300640 （）
KJZD-K202300611) （）
