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Prediction of core deflection in wax injection for investment casting by using SVM and BPNN

  • Donghong WangEmail author
  • Jinyu Sun
  • Anping Dong
  • Guoliang Zhu
  • Shumei Liu
  • Haijun Huang
  • Da Shu
ORIGINAL ARTICLE
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Abstract

Core shift is a common basic problem during the manufacture of those thin-walled hollow casting parts in investment casting. The core deflection during wax injection is the main reason for exceeding tolerance in final cast. The wax melt may advance asymmetrically along both sides of the core in wax injection process for a thin-walled hollow complex part, which causes the core to shift, resulting in non-uniform wall thickness of the wax pattern. The simulation results and experimental measurements of core deflection on the wax pattern for a hollow pump body were studied. The SVR (support vector regression) has been used to predict the core deflection for the wax pattern. Packing pressure, injection temperature and injection velocity were chosen as main process parameters. The core deflection of the wax pattern is most influenced by the melt temperature because of larger stress distribution acting on the cores in the viscous state at low injection temperature. SVR and BPNN (back-propagation neural network) were used to establish the prediction model; SVR has a better predictive ability compare with BPNN.

Keywords

Wax injection Core deflection Support vector machine (SVM) Back-propagation neural network (BPNN) Investment casting 

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Notes

Funding information

This work was financially supported by National Natural Science Foundation of China (51705314) and The Major State Basic Research Development Program of China (2016YFB0701405). The authors gratefully acknowledge the financial supports from the National Industrial Basis Improvement Project under Project (TC160A310-12-1) and The 13th Five-year Major Project of Aero Engine and Gas Turbine of China (2017-VII-008). The Science and Technology Committee of Shanghai Municipality (16DZ2260602) is gratefully acknowledged.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Donghong Wang
    • 1
    • 2
    Email author
  • Jinyu Sun
    • 1
    • 3
  • Anping Dong
    • 1
    • 2
  • Guoliang Zhu
    • 1
    • 2
  • Shumei Liu
    • 3
  • Haijun Huang
    • 2
  • Da Shu
    • 1
    • 2
    • 4
  1. 1.Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming, School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.State Key Laboratory of Metal Matrix Composites, School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  3. 3.School of Materials EngineeringShanghai University of Engineering ScienceShanghaiChina
  4. 4.Materials Genome Initiative CenterShanghai Jiao Tong UniversityShanghaiChina

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