Journal of Drive and Control (드라이브 ㆍ 컨트롤)

The Korean Society for Fluid Power and Construction Equipment (유공압건설기계학회)
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Optimization of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network

인공 신경회로망을 이용한 전자비례 감압밸브의 솔레노이드 형상 최적화

  • Received : 2016.03.23
  • Accepted : 2016.05.13
  • Published : 2016.06.01
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Abstract

Unlike the commonly used On/Off solenoid, constant attraction force which is independent of plunger displacement is a considerably important characteristic to proportional solenoid of the EPPR Valve. Attraction force uniformity is mainly affected by the internal shape design parameters. Due to a number of shape design parameters, the optimal parameter values are very complex and time consuming to find by trial and error method. Much research has been conducted or are still in progress to find the optimal parameter values by applying various optimization techniques like Genetic Algorithm, Evolution Strategy, Simulated Annealing, or the Taguchi method. In this paper, the design parameters which have primary effects on the attraction force uniformity and the average attraction force are decided by main effects analysis of Design of Experiments. Optimal parameter values are derived using finite-element analysis and a neural network model.

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References

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