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基于智能算法的预成形模具优化设计

Optimization design of pre-forming die based on intelligence algorithm

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【作者】 王梦寒杨永超郭涛王周田周文武肖贵乾

【Author】 WANG Menghan;YANG Yongchao;GUO Tao;WANG Zhoutian;ZHOU Wenwu;XIAO Guiqian;College of Materials Science and Engineering, Chongqing University;China National Erzhong Wanghang Die Forging Co., Ltd.;

【通讯作者】 王梦寒;

【机构】 重庆大学材料科学与工程学院中国第二重型机械集团德阳万航模锻有限责任公司

【摘要】 为了保证航空发动机盘类锻件组织变形均匀,提高人工模拟效率,提出基于多软件协同仿真的回转体类锻件预成形模具智能优化算法。首先,利用CATIA构建预锻模具的参数化几何模型,并用Deform-2D计算终锻过程中锻件等效应变,然后使用MATLAB的遗传算法工具箱作为控制模块进行智能化控制。其次,编写3个软件的接口程序,使3个软件之间实现自动、协同、实时动态优化。最后,将该优化算法应用于钛合金整体叶盘的生产试制。研究结果表明:该优化系统具有良好的智能性和鲁棒性,优化后的锻件内部等效应变在理想区间(0.45~1.05)所占比例由54.8%提高到了94.3%,并且通过产品试制测试零件性能满足要求。

【Abstract】 In order to ensure more uniformity microstructure distribution of forging and improve the efficiency of artificial simulation of Aeroengine disk parts, an intelligent optimization algorithm for pre-forming dies based on multisoftware collaborative simulation was developed. Firstly, the parametric modeling was realized by CATIA software and the effective strain distribution of forging was simulated by DEFORM-2 D. Secondly, Genetic Algorithm toolbox embedded in MATLAB was used as a controller which controls the whole optimization process automatically. An automatic, cooperative and real-time dynamic optimization process was realized by coding corresponding interface program. Finally, the optimization algorithm was applied to the production of titanium alloy blisk. The results indicate that the optimization system has a good intelligence and robustness, the proportion of the internal effective strain value in the ideal range(0.45-1.05) of the optimized forgings increased from 54.8% to 94.3%, and the performance of the parts meets the requirements.

【基金】 工信部绿色制造系统集成项目(2018272106-1)~~
  • 【文献出处】 中南大学学报(自然科学版) ,Journal of Central South University(Science and Technology) , 编辑部邮箱 ,2019年06期
  • 【分类号】V263
  • 【被引频次】6
  • 【下载频次】223
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