基于NSGA-Ⅱ算法的龙门横梁多目标结构优化

Multi-Objective Structure Optimization of Gantry Beam based on NSGA-II Algorithm

  • 摘要: 数控龙门横梁作为机床的主要承载结构,其高刚度与轻量化设计是关键研究目标。为实现横梁的轻量化设计,该文采用ANSYS仿真平台对两种横梁结构进行了静态和动态分析,并对比了分析结果。结果表明,十型横梁在变形量、应力和固有频率等方面优于鼠笼型,具有较大优化潜力。然后,基于响应面模型和非支配排序遗传算法Ⅱ对十型横梁进行了多目标优化设计。在满足要求的前提下,最终使横梁质量减轻了335.5 kg,约占原重量的7.34%。研究内容可为数控机床轻量化和高性能设计研究提供参考。

     

    Abstract: As the main bearing structure, the CNC gantry beam is the focus of high stiffness and lightweight design. To achieve a lightweight design of the crossbeam, this paper employs the ANSYS simulation platform to perform static and dynamic analyses of two crossbeam structures and compares the corresponding results. The results show that the ten-type beam performs better than the rat cage type in terms of deformation, stress, and natural frequency, demonstrating significant optimization potential. Based on the response surface model and non-dominant ranking genetic algorithm, the beam mass is ultimately reduced by 335.5 kg, accounting for about 7.34% of the original weight, which provides a reference for the lightweight and high-performance design research of CNC machine tools.

     

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