上海交通大学学报(英文版) ›› 2012, Vol. 17 ›› Issue (5): 635-642.doi: 10.1007/s12204-012-1336-3
• 论文 • 上一篇
YAN Yu1 (阎昱), WANG Hai-bo1* (王海波), WAN Min2 (万敏)
出版日期:
2012-10-30
发布日期:
2012-11-16
通讯作者:
WANG Hai-bo1* (王海波)
E-mail: rock_haibo@126.com
YAN Yu1 (阎昱), WANG Hai-bo1* (王海波), WAN Min2 (万敏)
Online:
2012-10-30
Published:
2012-11-16
Contact:
WANG Hai-bo1* (王海波)
E-mail: rock_haibo@126.com
摘要: Because of the light weight, high stiffness and high structural efficiency, aluminium alloy integral panels are widely used on modern aircrafts. Press bend forming has many advantages, and it becomes a significant technique in aircraft manufacturing field. In order to design the press bend forming path for aircraft integral panels, we propose a novel optimization method which integrates the finite element method (FEM) equivalent model based on our previous study, the artificial neural network response surface, and the genetic algorithm. First, a multi-step press bend forming FEM equivalent model is established, with which the FEM experiments designed with Taguchi method are performed. Then, the backpropagation (BP) neural network response surface is developed with the sample data from the FEM experiments. Further more, genetic algorithm (GA) is applied with the neural network response surface as the objective function. Finally, experimental and simulation verifications are carried out on a single stiffener specimen. The forming error of the panel formed with the optimal path is only 5.37% and the calculating efficiency has been improved by 90.64%. Therefore, this novel optimization method is quite efficient and indispensable for the press bend forming path designing.
中图分类号:
YAN Yu1 (阎昱), WANG Hai-bo1* (王海波), WAN Min2 (万敏). Forming Path Optimization for Press Bending of Aluminum Alloy Aircraft Integral Panel[J]. 上海交通大学学报(英文版), 2012, 17(5): 635-642.
YAN Yu1 (阎昱), WANG Hai-bo1* (王海波), WAN Min2 (万敏). Forming Path Optimization for Press Bending of Aluminum Alloy Aircraft Integral Panel[J]. Journal of shanghai Jiaotong University (Science), 2012, 17(5): 635-642.
[1] Munroe J, Wilkins K, Gruber M. Integral airframe structures (IAS): Validated feasibility study of integrally stiffened metallic fuselage panels for reducing manufacturing costs [R]. Seattle, Washington: Boeing Commercial Airplane Group, 2000. [2] Sheng Z Q, Jirathearanat S, Altan T. Adaptive FEM simulation for prediction of variable blank holder force in conical cup drawing [J]. International Journal of Machine Tools and Manufacture, 2004, 44(5): 487-494. [3] Sun G Y, Li G Y, Gong Z H, et al. Multiobjective robust optimization method for drawbead design in sheet metal forming [J]. Materials and Design, 2010,31(4): 1917-1929. [4] Lorenzo R D, Ingarao G, Chinesta F. Integration of gradient based and response surface methods to develop a cascade optimisation strategy for Y-shaped tube hydroforming process design [J]. Advances in Engineering Software, 2010, 41(2): 336-348. [5] Mirzaali M, Seyedkashi S M H, Liaghat G H,et al. Application of simulated annealing method to pressure and force loading optimization in tube hydroforming process [J]. International Journal of Mechanical Sciences, 2012, 55(1): 78-84. [6] Zeng G, Li S H , Yu Z Q, et al. Optimization design of roll profiles for cold roll forming based on response surface method [J]. Materials and Design, 2009, 30(6):1930-1938. [7] Ou H, Wang P, Lu B, et al. Finite element modelling and optimisation of net-shape metal forming processes with uncertainties [J]. Computers and Structures,2012, 90-91: 13-27. [8] Zhao G Q, Ma X W, Zhao X H, et al. Studies on optimization of metal forming processes using sensitivity analysis methods [J]. Journal of Materials Processing Technology, 2004, 147(2): 217-228. [9] Ant′onio C C, Catarina C, Sousa L C. Optimization of metal forming processes [J]. Computers and Structures, 2004, 82(17-19): 1425-1433. [10] Castro C F, Ant′onio C A C, Sousa L C. Optimization of shape and process parameters in metal forging using genetic algorithms [J]. Journal of Materials Processing Technology, 2004, 146(3): 356-364. [11] Palaniswamy H, Ngaile G, Altan T. Optimization of blank dimensions to reduce springback in the flexforming process [J]. Journal of Materials Processing Technology, 2004, 146: 28-34. [12] Ohata T, Nakamura Y, Katayama T, et al. Development of optimum process design system for sheet fabrication using response surface method [J]. Journal of Materials Processing Technology, 2003, 143-144:667-672. [13] Lee H W, Arunasalam P, Laratta W P. Neurogenetic optimization of temperature control for a continuous flow polymerase chain reaction microdevice [J]. Journal of Biomechanical Engineering, 2007, 129(4):540-547. [14] Jansson T, Nilsson L. Optimizing sheet metal forming processes: Using a design hierarchy and response surface methodology [J]. Journal of Materials Processing Technology, 2006, 178(1-3): 218-233. [15] Takayama K, Fujikawa M, Obata Y, et al. Neural network based optimization of drug formulations [J].Advanced Drug Delivery Reviews, 2003, 55(9): 1217-1231. [16] Mandal S, Sivaprasad P V, Venugopal S. Artificial neural network modeling of composition-processproperty correlations in austenitic stainless steels [J]. Materials Science and Engineering A, 2008, 485(1-2):571-580. [17] Pal S, Pal S K, Samantaray A K. Artificial neural network modeling of weld joint strength prediction of a pulsed metal insert gas welding process using arc signals [J]. Journal of Materials Processing Technology,2008, 202(1-3): 464-474. [18] Kurtaran H. A novel approach for the prediction of bend allowance in air bending and comparison with other methods [J]. International Journal of Advanced Manufacturing Technology, 2008, 37(5-6): 486-495. [19] Cheng J, Li Q S, Xiao R C. A new artificial neural network-based response surface method for structural reliability analysis [J]. Probabilistic Engineering Mechanics,2008, 23(1): 51-63. [20] Yan Y, Wan M, Wang H B. FEM equivalent model for press bend forming of aircraft integral panel [J].Transactions of Nonferrous Metals Society of China,2009, 19(2): 414-424. [21] Fowlkes W Y, Creveling C M. Engineering methods for robust product design [M]. Massachusetts, MA:Addison Wesley Longman, Inc., 1995. |
[1] | LI Jie (李杰), LIU Yongzhi (刘勇智), SHAN Chenglong (鄯成龙), DAI Cong (戴聪). Implementation of Simplified Fractional-Order PID Controller Based on Modified Oustaloup's Recursive Filter[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(1): 44-50. |
[2] | WANG Menghan* (王梦寒), XIAO Guiqian (肖贵乾), WANG Jinqiang (王晋强), LI Zhi (李志). Optimization of Clinching Tools by Integrated Finite Element Model and Genetic Algorithm Approach[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(2): 262-272. |
[3] | MENG Yu *(孟宇), GAN Xin (甘鑫), WANG Yu (汪钰), GU Qing (顾青). LQR-GA Controller for Articulated Dump Truck Path Tracking System[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(1): 78-85. |
[4] | JIAO Qinglong (焦庆龙), XU Da (徐达). A Discrete Bat Algorithm for Disassembly Sequence Planning[J]. sa, 2018, 23(2): 276-285. |
[5] | PAN Qian1*(潘谦), HE Xing1 (何星), CAI Yun-ze1 (蔡云泽),WANG Zhi-hua2 (王治华), SU Fan2 (苏. Improved Real-Coded Genetic Algorithm Solution for Unit Commitment Problem Considering Energy Saving and Emission Reduction Demands[J]. 上海交通大学学报(英文版), 2015, 20(2): 218-223. |
[6] | HUANG Qiang1,2 (黄 强), LOU Xin-yuan3 (楼新远), WANG Wei4* (王 薇), NI Shao-quan1 (倪少权). Research of Order Allocation Model Based on Cloud and Hybrid Genetic Algorithm Under Ecommerce Environment[J]. 上海交通大学学报(英文版), 2013, 18(3): 334-342. |
[7] | XU Ji-xiang* (许继祥), ZHAO Jin-cheng (赵金城), DUAN Hai-juan (段海娟). Risk-Identification-Based Hybrid Method for Estimating the System Reliability of Existing Jacket Platforms Under Fire[J]. 上海交通大学学报(英文版), 2013, 18(1): 70-75. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||