Optimization design of pre-forming die based on intelligence algorithm

被引：0

作者：

Wang M. ^{[1
]}

Yang Y. ^{[1
]}

Guo T. ^{[1
]}

Wang Z. ^{[2
]}

Zhou W. ^{[2
]}

Xiao G. ^{[1
]}

机构：

[1] College of Materials Science and Engineering, Chongqing University, Chongqing

[2] China National Erzhong Wanghang Die Forging Co., Ltd., Deyang

来源：

Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2019年 / 50卷 / 06期

关键词：

Blisk; Cooperative simulation; Finite element analysis; Genetic algorithm; Pre-forming;

D O I：

10.11817/j.issn.1672-7207.2019.06.005

中图分类号：

学科分类号：

摘要：

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 multi-software collaborative simulation was developed. Firstly, the parametric modeling was realized by CATIA software and the effective strain distribution of forging was simulated by DEFORM-2D. 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. © 2019, Central South University Press. All right reserved.

引用

页码：1298 / 1305

页数：7

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