基于遗传算法的光固化成形变形控制

原型件的变形是影响光固化成形精度的主要因素,制作参数的优化是减小变形的主要途径之一,但由于变形的影响因素复杂,变形机制尚不明确,所以这方面的研究进展缓慢.文章首先选取了影响变形的可控制作参数,采用Taguchi方法进行了实验研究, 根据实验数据建立了基于神经网络的变形评价模型,以此作为优化目标函数,提出了基于遗传算法实现约束条件下的多参数综合优化方案,并用于制作过程控制,试验证明可有效减小变形.

Research on Control Method to Reduce Deformation in Stereolithography Using Genetic Algorithm

Optimization of build parameters is the main way to reduce part deformation, which is the fatal factor to influence part accuracy in stereolithography. In the paper, an experimental investigation about selected controllable build parameters has been carried out using Taguchi method, and then the deformation model is set up employing neural networks. Using this deformation model as the objective function, an optimization scheme to build parameters based on Genetic Algorithm is proposed to control build process and reduce deformation.