Sun Xuan, Liu Ting, Jia Jiguang, Chen Zhihui, Shang Jing
School of Mechanic and Control Engineering, Guilin University of Technology Guilin, Guilin, China.
Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of Technology, Education Department of Guangxi Zhuang Autonomous Region, Guilin, China.
Sci Prog. 2023 Jul-Sep;106(3):368504231203108. doi: 10.1177/00368504231203108.
In this study, the multi-objective optimal design of the Hinge Sleeve of Cubic (HSC) was achieved by combining the central composite design (CCD), Kriging and multi-objective genetic algorithm (MOGA) approaches. Firstly, the model of the HSC was established and the appropriate design variables were selected. The mass, the maximum deformation and the maximum equivalent stress of the HSC were taken as the optimization objectives. After comparative analysis of the parameters, the parameter with the greatest influence on the optimization objectives was selected as the geometric constraint. Subsequently, according to the results of the experimental design, the Kriging model was used to establish the response surface optimization model of the objective function. And finally the best optimization results were obtained by using MOGA. The experimental results show that the optimization strategy is reliable and the mass of the optimized model is reduced by 24.84%, which achieves the lightweight design of the HSC while meeting the actual production requirements, saves the design cost and improves the material utilization.
在本研究中，通过结合中心复合设计（CCD）、克里金法和多目标遗传算法（MOGA）实现了立方铰链套筒（HSC）的多目标优化设计。首先，建立了HSC的模型并选择了合适的设计变量。将HSC的质量、最大变形和最大等效应力作为优化目标。在对参数进行对比分析后，选择对优化目标影响最大的参数作为几何约束。随后，根据实验设计结果，利用克里金模型建立目标函数的响应面优化模型。最后使用MOGA获得了最佳优化结果。实验结果表明，该优化策略可靠，优化模型的质量降低了24.84%，在满足实际生产要求的同时实现了HSC的轻量化设计，节省了设计成本并提高了材料利用率。
