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Optimization of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network
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  • Journal title : Journal of Drive and Control
  • Volume 13, Issue 2,  2016, pp.34-41
  • Publisher : Korea Society of Fluid Power & Construction Equipments
  • DOI : 10.7839/ksfc.2016.13.2.034
 Title & Authors
Optimization of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network
Yoon, Ju Ho; Nguyen, Minh Nhat; Lee, Hyun Su; Youn, Jang Won; Kim, Dang Ju; Lee, Dong Won; Ahn, Kyoung Kwan;
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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.
 Keywords
EPPR Valve;Proportional Solenoid;Finite-elements analysis;Artificial Neural Network;Control Cone;
 Language
Korean
 Cited by
 References
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