Optimization of technological parameters in the calescent superplastic bulge forming of Ti-6Al-4V alloys sheet based on fuzzy neural network

被引:0
作者
Chen, MH [1 ]
Gao, L
Zhu, ZS
Zuo, DW
Wang, M
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, Nanjing 210016, Peoples R China
[2] Beijing Inst Aeronaut, Beijing 100095, Peoples R China
来源
ADVANCES IN MATERIALS MANUFACTURING SCIENCE AND TECHNOLOGY | 2004年 / 471-472卷
关键词
fuzzy neural network; calescent superplastic bulge forming; titanium alloy; optimization;
D O I
10.4028/www.scientific.net/MSF.471-472.596
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The calescent superplastic bulge forming (CSPBF) of Ti-6Al-4V (TC4) alloy sheet was investigated using experimental method, and carried out the research that optimized its technological parameters using fuzzy neural network (FNN). The experimental results show that the CSPBF may save processing time, can also improve materials' formability as well as get ideal microstructure. The study indicated that the FNN adapt to solve complex nonlinear problem such as technological parameters of CSPBF of TC4 sheet. Utilizing optimized technological parameters successfully have formed the part of aerostat, the nominiformity of wall thickness is less than 8% and part' forming time maybe shorten 10minute.
引用
收藏
页码:596 / 602
页数:7
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