基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化
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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.
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.
引文
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[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):40-43WANG 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):34-37SHI 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):70-73FENG 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,KTKDE 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 ProcessParameters 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