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档位齿轮预成形形状与工艺参数的复合型蜂群算法优化
英文标题:Optimization on complex bee colony algorithm of gear preformed shape and process parameters
作者:郑辉1 2 马晓琳1 2 
单位:1.天津科技大学 工业工程系 2.天津科技大学 精益管理研究中心 
关键词:档位齿轮 预成形联合优化 电场法 闭合等势线 复合型蜂群算法 Metropolis选择准则 
分类号:TG315.2
出版年,卷(期):页码:2022,47(4):37-42
摘要:

 为了降低档位齿轮的成形载荷并提高锻件的合格率,提出了基于电场法和复合型蜂群算法的预成形形状与工艺参数联合优化方法。基于电场法,得到了各闭合等势线对应的备选预成形形状,同时选择压机速度、摩擦因数、坯料温度等参数作为共同优化参数,以降低成形载荷和提高填充率为目标,建立了多目标优化模型。在人工蜂群算法中引入Metropolis选择准则和复合型优化方法,提出了复合型蜂群算法的参数优化方法。经验证,复合型蜂群算法的参数优化结果好于传统人工蜂群算法。经过仿真和实际生产验证,锻压过程的最大成形载荷由1960 kN降低为1550 kN,产品合格率由91.7%提高为100%,以上数据验证了预成形形状和工艺参数联合优化方法的有效性。

 

 In order to reduce the forming load of gear and improve the qualification rate of forgings, a union optimization method of preformed shape and process parameters based on electric field method and complex bee colony algorithm was proposed. Based on the electric field method, the candidate preformed shapes corresponding to each closed equipotential line were obtained. At the same time, selecting press speed, friction factor, billet temperature as the common optimization parameters, a multi-objective optimization model was established to reduce the forming load and improve the filling rate. Furthermore, the parameter optimization method of the complex bee colony algorithm was proposed by introducing the Metropolis selection criterion into the artificial bee colony algorithm and using the complex optimization method. It was verified that the parameters optimization result of the complex bee colony algorithm was better than that of the traditional artificial bee colony algorithm. Through simulation and actual production verification, the maximum forming load of the forging process is reduced from 1960 kN to 1550 kN, and the product qualification rate is increased from 91.7% to 100%, which verifies the effectiveness of the union optimization method of preformed shape and process parameters. 

基金项目:
科技部创新方法工作专项(2019IM020300);教育部研究重大课题攻关项目(16JZD014)
作者简介:
作者简介:郑辉(1978-),女,博士,副教授 E-mail:s42smn@163.com
参考文献:

 [1]黄超群, 来飞. 基于傅里叶描述子的预成形设计[J].锻压技术,2020,45(6):16-21.


Huang C Q, Lai F. Preforming design based on Fourier descriptor [J]. Forging & Stamping Technology, 2020, 45(6):16-21.

[2]李旭斌, 张治民,李国俊,等. 镁合金复杂构件预成形体积分配及量化设计[J].塑性工程学报,2019,26(5):1-6.

Li X B, Zhang Z M, Li G J, et al. Volume distribution and quantitative design of preforming for magnesium alloy complex components [J]. Journal of Plasticity Engineering, 2019, 26(5):1-6.

[3]李志伟.  滑动轴承预成形件热挤压有限元分析及工艺参数优化研究[D]. 太原:中北大学,2020.

Li Z W. Finite Element Analysis and Optimization of Process Parameters for Hot Extrusion of Sliding Bearing Preforms [D]. Taiyuan: North University of China, 2020.

[4]黄超群, 来飞. 基于智能算法的轴对称锻件预成形优化设计[J].锻压技术,2020,45(2):29-35.

Huang C Q, Lai F. Optimal design on preforming of axisymmetric forgings based on intelligent algorithm [J]. Forging & Stamping Technology, 2020, 45(2):29-35.

[5]卢蔚红. 探析基于有限元逆向模拟技术的预成形模具设计[J].中国新通信,2020,22(17):241-242.

Lu W H. Analysis of preforming die design based on finite element reverse simulation technology [J]. China New Telecommunications, 2020, 22(17):241-242.

[6]Sedighi M, Toklllechi S. A new approach to preform design in forging Process of complex parts[J]. Journal of Materials Processing Technology, 2008, 197:314-324.

[7]周玉婷. 某飞机主起支撑接头锻件的锻造工艺分析及预成形优化设计[D]. 重庆:重庆大学,2018.

Zhou Y T. Analysis of Forging Process and Preform Shape Design for Aircraft Main Supporting Joint Part [D]. Chongqing: Chongqing University, 2018.

[8]张倩, 胡仁喜,康士廷. ANSYS12.0电磁学有限元分析从入门到精通[M]. 北京:机械工业出版社,2010.

Zhang Q, Hu R X, Kang S T. ANSYS12.0 Finite Element Analysis of Electromagnetics [M]. Beijing: China Machine Press, 2010.

[9]罗锐, 曹赟,邱宇,等.基于BP人工神经网络喷射成形7055铝合金的本构模型[J].航空材料学报,2021,41(1):35-44.

Luo R, Cao Y, Qiu Y, et al. Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network [J]. Journal of Aeronautical Materials, 2021, 41(1):35-44.

[10]单良, 李浩然,洪波,等. 基于人工蜂群算法的多峰颗粒粒度分布反演[J].光子学报,2020,49(12):197-210.

Shan L, Li H R, Hong B, et al. Inversion of multimodal particle size distribution based on the artificial bee colony algorithm [J]. Acta Photonica Sinica, 2020, 49(12):197-210.

[11]刘刚, 裴红蕾. 复合形引导蜂群寻优的无人机航迹多目标规划[J].机械设计与制造,2020,(4):253-257.

Liu G, Pei H L. Unmanned air vehicle route multi-object planning based on bee colony algorithm guided by complex form [J]. Machinery Design & Manufacture, 2020,(4):253-257.

[12]He D, Jia R, Shi S. An artificial bee colony optimization algorithm guided by complex method[A]. The Fifth International Symposium on Computational Intelligence and Design[C]. IEEE, 2013.
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