Paper Title:
Optimization of Technological Parameters in the Calescent Superplastic Bulge Forming of Ti-6Al-4V Alloys Sheet Based on Fuzzy Neural Network
  Abstract

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 nonuniformity of wall thickness is less than 8% and part' forming time may be shorten 10minute.

  Info
Periodical
Materials Science Forum (Volumes 471-472)
Edited by
Xing Ai, Jianfeng Li and Chuanzhen Huang
Pages
596-602
DOI
10.4028/www.scientific.net/MSF.471-472.596
Citation
M. H. Chen, L. Gao, Z.S. Zhu, D. W. Zuo, M. Wang, "Optimization of Technological Parameters in the Calescent Superplastic Bulge Forming of Ti-6Al-4V Alloys Sheet Based on Fuzzy Neural Network", Materials Science Forum, Vols. 471-472, pp. 596-602, 2004
Online since
December 2004
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$32.00
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