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Genetic algorithm based optimization design of miniature piezoelectric forceps

机译:基于遗传算法的微型压电钳优化设计

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This paper studies about a simulation of a derived model for the steady-state force-deflection behavior of a miniature piezoelectric forceps actuator (PFA) based on complementary strain energy. Utilizing a genetic algorithm (GA) based as a design tool to simulate and optimize the physical design parameters of the PFA to get the optimum grasping force-deflection end tip of the PFA within desired physical constraints. Simulation studies of the optimized PFA parameters based on GA are presented. The piezoelectric forceps is remotely controlled miniature gripper and potentially to be used in tele-surgery, minimally invasive surgery, MEMS industrial assembly line, pick and place hazardous materials in tight and small space.
机译:本文基于互补应变能,关于微型压电钳致动器(PFA)的稳态力偏转行为的衍生模型的模拟研究。利用基于基于遗传算法(GA)作为设计工具来模拟和优化PFA的物理设计参数,以在所需的物理约束内获得PFA的最佳抓握力偏转端尖端。介绍了基于GA的优化PFA参数的仿真研究。压电钳是远程控制的微型夹具,并且可能用于远程手术,微创手术,MEMS工业装配线,挑选和放置紧密和小空间的危险材料。

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