基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化  

Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method

作　　者：张楠 史耀耀[1] 杨臣[1] 陈振 刘江 ZHANG Nan;SHI Yaoyao;YANG Chen;CHEN Zhen;CHEN Zhen(The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education,Northwestern Polytechnical University, Xi′an 710072, China;School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051,China)

机构地区：[1]西北工业大学现代设计与集成制造技术教育部重点实验室,陕西西安710072 [2]内蒙古工业大学机械学院,内蒙古呼和浩特010051

出　　处：《西北工业大学学报》2019年第1期160-166,共7页Journal of Northwestern Polytechnical University

基　　金："高档数控机床与机床制造装备"科技重大专项(2013ZX04001081);内蒙古自治区高等学校科学研究项目(NJZY16089)资助

摘　　要：整体叶盘通道盘铣加工是典型的多输入输出系统,改善该加工过程需要多目标优化。应用集灰色关联分析(grey relations analysis,GRA)、径向基神经网络(radial basis function neural network,RBF)和萤火虫智能算法(firefly algorithm,FA)于一体的多目标优化方法。通过优化加工参数:切削速度、每齿进给率和切削高度,同时满足最小切削力和最大材料去除率的目标。验证试验结果表明,灰色关联分析-径向基神经网络-萤火虫算法(GRA-RBF-FA)可用于盘铣TC17整体叶盘通道的加工参数优化;该方法优于灰色关联度分析。The process of disc-mill cutter machining blisk-tunnel is a typical multi-input and multi-output system, therefore multi-objective optimization is applied to improve the process. In this paper, an integrated approach that Grey Relational Analysis(GRA)couples with Radial Basis Function (RBF) neural network and Firefly algorithm (FA) is used to solve the optimization problem. The aim is to satisfy the minimum cutting force and maximum material removal rate simultaneously by optimizing the cutting speed, feed rate per tooth and cutting height. The results for verifying experiment indicated that GRA-RBF-FA method can be applied to optimize the processing parameters of disc-mill cutter machining TC17 blisk-tunnel and the optimization results are superior to the GRA′s.

关 键 词：盘铣刀 整体叶盘通道 加工参数 多目标优化 灰色关联分析-径向基神经网络-萤火虫算法 灰色关联度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]