期刊文献+

Thermal Compensation and Fuzzy Control for Developing a High-Precision Optical Lens Mold

下载PDF
导出
摘要 Precision plastic lenses often exhibit dimensional deviations due to the thermal expansion of the mold during injection molding.Although this deviation is smaller in micron-sized(1–5μm)lenses,it exceeds the tolerance requirement of such lenses.It is difficult to resolve this dimensional issue by using injection molding parameters(e.g.,melt temperature,injection speed,and hold pressure).In this study,the thermal analysis of a mold was conducted,and it was confirmed that the deviation of lens dimension was caused by the thermal instability and thermal expansion of the mold.Due to the inconsistent heat distribution of the fixed and the movable side of the mold,the position of the location system was displaced approximately 1 to 5μm.In this study,thermal compensation technology for this the mold was investigated.The temperature on both sides of the mold was measured,and mold temperature could be adjusted automatically using a control strategy based on fuzzy theory.During the mold preheating or mass production stage,the temperature on both sides of the mold could be easily adjusted to quickly obtain the required temperature range.The dilatation on both sides of the mold was revised to improve the alignment accuracy of the cavity,and the decenter error of these injection lenses was reduced to 1μm.This technology can markedly improve the production yield and efficiency of plastic products requiring an extremely high dimensional accuracy.
出处 《Journal of Mechanics Engineering and Automation》 2018年第5期189-197,共9页 机械工程与自动化(英文版)
  • 相关文献

参考文献1

二级参考文献16

  • 1K. Wang, Intelligent Condition Monitoring and Diagnosis Systems: A Computational Intelligence Approach, IOS Press, Amsterdam, 2003.
  • 2T. Pulecchi, F. Casella, M. Lovera, Object-oriented modeling for spacecraft dynamics: Tools and applications, Simulation Modelling Practice and Theory 18 (2010) 63-86.
  • 3J.K. Sinha, A.R. Rao, R.K. Sinha, Realistic seismic qualification using the updating finite element model for in-core components of reactors, Nuclear Engineering and Design 236 (2006) 232-237.
  • 4D.G. Cople, E.S. Brick, A simulation framework for technical systems life cycle cost analysis, Simulation Modelling Practice and Theory 18 (2010) 9-34.
  • 5H. Ahmadian, J.E. Mottershead, M.I. Friswell, Regularization methods for finite element model updating, Mechanical Systems and Signal Processing 12 (1998) 47-64.
  • 6S. Kindermann, A. Neubauer, On the convergence of the quasioptimality criterion for (iterated) Tikhonov regularization, Inverse Problems and Imaging 2 (2008) 291-299.
  • 7A. Poullikkas, Effects of two-phase liquid-gas flow on the performance of nuclear reactor cooling pumps, Progress in Nuclear Energy 42 (2003) 3-10.
  • 8J.W. Park, Analytical evaluation of two-phase natural circulation flow characteristics under external reactor vessel cooling, Annals of Nuclear Energy 36 (2009) 1668-1675.
  • 9V.G. Kinelev, P.M. Shkapov, V.D. Sulimov, Application of global optimization to VVER-1000 reactor diagnostics, Progress in Nuclear Energy 43 (2003) 51-56.
  • 10W.F. Sacco, C.R.E. de Oliveira, A new stochastic optimization algorithm based on particle collisions, Transactions of the American Nuclear Society 92 (2005) 657-659.

共引文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部