遗传算法
超弹性材料
弯曲
灵敏度(控制系统)
优化设计
计算机科学
实验设计
算法
结构工程
数学优化
工程类
有限元法
数学
电子工程
机器学习
统计
作者
Zhenlong LI,Ke Zhang,Yalin Guo,Haiyun Song,Mengyao Zhang,Li Na Zhang,Zhilong Du
出处
期刊:
[SPIE]
日期:2024-08-29
卷期号:: 13-13
摘要
Aiming at the highly nonlinear characteristics of the pneumatic soft finger, the static analysis of its bending performance is carried out, and the multi-objective optimization design is carried out by using the response surface method and the multi-objective genetic algorithm (MOGA). Firstly, the structural design and working principle of the soft finger are described in detail, including its overall structural design, and bending deformation principle based on hyperelastic materials. Then, the structural parameters which have great influence on the bending angle, the maximum stress and the volume are selected as the design variables by the sensitivity analysis method. The experimental design method of BoxBehnken design is used to design the sample points, and the Kriging method is used to construct the approximate model to reveal the relationship between the design variables and the performance index of the soft finger. Combined with the MOGA algorithm, the multi-objective optimization of the structural parameters of the soft finger is realized. After verification, while ensuring the structural strength, the bending angle of the optimal scheme optimization target result is increased by 14.21 % and the volume is reduced by 8.46 %. The results show that the optimization scheme can effectively improve the dynamic and static characteristics of the pneumatic soft finger and provide a theoretical basis for its optimization design.
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