中国机械工程2017，Vol.28Issue(7)：842-845,851,5.DOI:10.3969/j.issn.1004-132X.2017.08.014
基于混合算法的薄壁件铣削加工工艺参数优化
Optimization of Milling Process Parameters Based on Hybrid Algorithm for Thin-walled Workpieces
摘要
Abstract
Combining with advantages of neural network method and genetic algorithm,a method to optimize machining process parameters was proposed for thin-walled workpieces based on back propagation neural network(BPNN).The data gained from Taguchi experiments were applied to train in BPNN so as to generate the S/N ratio predictor and quality predictor.By maximizing the S/N ratio,variation of milling processes was minimized,and the optimal process parameter combinations were found.Through numerical simulation and machining experiments,effectiveness of the proposed method in optimization of milling process parameters of thin-walled workpieces was validated.关键词
薄壁件/田口法/遗传算法/工艺参数优化Key words
thin-walled workpiece/taguchi method/genetic algorithm/processing parameter optimization分类
机械制造引用本文复制引用
曾莎莎,彭卫平,雷金..基于混合算法的薄壁件铣削加工工艺参数优化[J].中国机械工程,2017,28(7):842-845,851,5.基金项目
国家自然科学基金资助项目(51505343) （51505343）
中国博士后科学基金资助项目(2015M572192) （2015M572192）
中央高校基本科研业务费专项资金资助项目(2042015kf0048) （2042015kf0048）
