Theoretical and experimental investigation on optimization of a non-contact air conveyor

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• 作者：Wei Zhong 钟伟 ; Xin Li 黎鑫 ; Guo-liang Tao 陶国良 ; Bo Lu 路波…
• 关键词：optimization ; genetic algorithm ; porous media ; air conveyor ; pressure distribution
• 刊名：Journal of Central South University
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：23
• 期：2
• 页码：353-361
• 全文大小：1,567 KB
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• 作者单位：Wei Zhong 钟伟 (1) (2)
  Xin Li 黎鑫 (3)
  Guo-liang Tao 陶国良 (3)
  Bo Lu 路波 (4)
  Toshiharu Kagawa 香川利春 (5)
  
  1. School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China
  2. Wuxi Pneumatic Technology Research Institute Co. Ltd., Wuxi, 214072, China
  3. State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, 310027, China
  4. Boyan Pneumatic Technology Institute of Ningbo, Fenghua, 315500, China
  5. Precision and Intelligence Laboratory, Tokyo Institute of Technology, Yokohama, 226-8503, Japan
  
• 刊物类别：Engineering
• 刊物主题：Engineering, general
  Metallic Materials
  Chinese Library of Science
  
• 出版者：Central South University, co-published with Springer
• ISSN：2227-5223

文摘

Air film conveyors equipped with porous pads have been developed to bring the liquid crystal display (LCD) into a non-contact state during transportation process. In this work, a theoretical model including flow property of porous media and Reynolds equation is established within a representative region in order to optimize the design parameters of a partial porous air conveyor. With the theoretical model, an optimization method using nondominated sorting genetic algorithm–II (NSGA-II) is applied for a two-objective optimization to achieve a minimum air consumption and maximum load capacity. Three Pareto-optimal solutions are selected to analyze the influence of each parameter on the characteristics of the air conveyor, and the results indicate that the position of the porous pads has the most significant impact on the performance and of course must be determined with care. Furthermore, experimental results in terms of the supporting force versus gap clearance show that the optimized air conveyor can greatly improve the load capacity over the normal one, indicating that the optimization method is applicable for practical use. Keywords optimization genetic algorithm porous media air conveyor pressure distribution