基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化 -- 西北工业大学学报,2019,37(1):160-166
论文:2019,Vol:37,Issue(1):160-166
引用本文:
张楠, 史耀耀, 杨臣, 陈振, 刘江. 基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化[J]. 西北工业大学学报
ZHANG Nan, SHI Yaoyao, YANG Chen, CHEN Zhen, LIU Jiang. Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method[J]. Northwestern polytechnical university

基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化
张楠1,2, 史耀耀1, 杨臣1, 陈振1, 刘江2
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
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。
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   
Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method
ZHANG Nan1,2, SHI Yaoyao1, YANG Chen1, CHEN Zhen1, LIU Jiang2
1. The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
Abstract:
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.
Key words:    disc-mill cutter    blisk-tunnel    processing parameters    multi-objective optimization    GRA-RBF-FA    GRG   
收稿日期: 2018-03-05     修回日期:
DOI: 10.1051/jnwpu/20193710160
基金项目: "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
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作者简介: 张楠(1981-),女,西北工业大学博士研究生,主要从事金属切削机理研究。
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参考文献:
[1] 史耀耀, 段继豪, 张军锋,等. 整体叶盘制造工艺技术综述[J]. 航空制造技术,2012, 399(3):26-31 SHI Yaoyao, DUAN Jihao, ZHANG Junfeng, et al. Blisk Disc Manufacturing Process Technology[J]. Aeronautical Manufacturing Technology, 2012, 399(3):26-31 (in Chinese)
[2] 王增强. 航空发动机整体叶盘加工技术[J]. 航空制造技术,2013, 429(9):40-43 WANG Zengqiang. Machining Technology of Aeroengine Blisk[J]. Aeronautical Manufacturing Technology, 2013, 429(9):40-43 (in Chinese)
[3] 史耀耀, 左安邦, 董婷,等. 开式整体叶盘通道高效粗加工方法研究[J]. 航空制造技术,2013, 424(4):34-37 SHI Yaoyao, ZUO Anbang, DONG Ting, et al. Research on Rough-Cutting Machining Method for Blisk[J]. Aeronautical Manufacturing Technology, 2013, 424(4):34-37 (in Chinese)
[4] 冯新敏, 毛杜邦, 程耀楠,等. 整体叶盘铣削参数的优化[J]. 工具技术,2018(1):70-73 FENG Xinmin, MAO Dubang, CHENG Yaonan, et al. Optimization System of Milling Parameters for Whole Blade Disk[J]. Tool Engineering, 2018(1):70-73 (in Chinese)
[5] REN J, ZHOU J, ZENG J. Analysis and Optimization of Cutter Geometric Parameters for Surface Integrity in Milling Titanium Alloy Using a Modified Grey-Taguchi Method[J]. Proceedings of the Institution of Mechanical Engineers, Part B:Journal of Engineering Manufacture, 2016, 230(11):2114-2128
[6] TAKESEN A, KVTVKDE K. Experimental Investigation and Multi-Objective Analysis on Drilling of Boron Carbide Reinforced Metal Matrix Composites Using Grey Relational Analysis[J]. Measurement, 2014, 47:321-330
[7] KUMAR S S, UTHAYAKUMAR M, KUMARAN S T, et al. Parametric Optimization of Wire Electrical Discharge Machining on Aluminium Based Composites through Grey Relational Analysis[J]. Journal of Manufacturing Processes, 2015, 20:33-39
[8] NELABHOTLA D M, JAYARAMAN T V, ASGHAR K, et al. The Optimization of Chemical Mechanical Planarization Process-Parameters of C-Plane Gallium-Nitride Using Taguchi Method and Grey Relational Analysis[J]. Materials & Design, 2016, 104:392-403
[9] DATTA S, MAHAPATRA S. Modeling, Simulation and Parametric Optimization of Wire Edm Process Using Response Surface Methodology Coupled with Grey-Taguchi Technique[J]. International Journal of Engineering Science & Technology, 2010, 2(5):162-183
[10] ADALARASAN R, SANTHANAKUMAR M, RAJMOHAN M. Application of Grey Taguchi-Based Response Surface Methodology(GT-RSM) for Optimizing the Plasma Arc Cutting Parameters of 304L Stainless Steel[J]. International Journal of Advanced Manufacturing Technology, 2015, 78(5/6/7/8):1161-1170
[11] ZHOU J, REN J, YAO C. Multi-Objective Optimization of Multi-Axis Ball-End Milling Lnconel 718 via Grey Relational Analysis Coupled with RBF Neural Network and PSO Algorithm[J]. Measurement, 2017, 102:271-285
[12] ZHOU J, REN J, TIAN W. Grey-RBF-FA Method to Optimize Surface Integrity for Inclined End Milling Inconel 718[J]. The International Journal of Advanced Manufacturing Technology, 2017, 91(9):1-19
[13] JULONG D. Introduction to Grey System Theory[J]. The Journal of Grey System, 1989, 1(1):1-24
[14] MAO K Z, HUANG G B. Neuron selection for RBF Neural Network Classifier Based on Data Structure Preserving Criterion[J]. IEEE Trans on Neural Networks, 2005, 16(6):1531-1540
[15] YANG Xinshe. Multiobjective Firefly Algorithm for Continuous Optimization[J]. Engineering with Computers, 2013, 29(2):175-184