Optimization of investment casting process parameters to reduce warpage of turbine blade platform in DD6 alloy

被引:1
|
作者
Jia-wei Tian [1 ]
Kun Bu [1 ]
Jin-hui Song [1 ]
Guo-liang Tian [1 ]
Fei Qiu [1 ]
Dan-qing Zhao [1 ]
Zong-li Jin [1 ]
Yang Li [1 ]
机构
[1] Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University
基金
中国国家自然科学基金;
关键词
ProCAST; optimization of process parameters; warping deformation of platform; orthogonal test; genetic algorithm; BP-neural network;
D O I
暂无
中图分类号
V263 [航空发动机制造];
学科分类号
摘要
The large warping deformation at platform of turbine blade directly affects the forming precision. In the present research, equivalent warping deformation was firstly presented to describe the extent of deformation at platform. To optimize the process parameters during investment casting to minimize the warping deformation of the platform, based on simulation with Pro CAST, the single factor method, orthogonal test, neural network and genetic algorithm were subsequently used to analyze the influence of pouring temperature, shell mold preheating temperature, furnace temperature and withdrawal velocity on dimensional accuracy of the platform of superalloyDD6 turbine blade. The accuracy of investment casting simulation was verified by measurement of platform at blade casting. The simulation results with the optimal process parameters illustrate that the equivalent warping deformation was dramatically reduced by 21.8% from 0.232295 mm to 0.181698 mm.
引用
收藏
页码:469 / 477
页数:9
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