基于田口算法和灰色关联理论的车削参数多目标优化研究

Multi-object Optimization of Parameters for Turning Based on Taughi Method and Grey Relational Analysis

车削的优化过程受限于多个参数的限制,这也决定了对车削的优化必须是多目标优化。为了使车削的能耗和粗糙度同时降低,通过正交矩阵设计实验,减少实验数量的同时,运用灰色关联法对车削过程进行分析,衡量各个参数对各个目标函数的影响。并运用田口法进行多目标优化,找到了实验中较好的解。通过优化,粗糙度降低75.9%,切削比能降低73.1%,找到了能耗和粗糙度均较低的加工参数,并大大提升了加工效率。与实验比对,优化效果与理论差别不大,且加工参数易于满足优化的要求。

Due to the condition of the manufacture, the optimization of the process parameters for turning is constraint by many requirement, which determines that the optimization should be a multi-criteria optimization . This paper outline a way of optimizing the turning process to achieve the minimum power consumption and best surface quality. To cut off the number of experiment, the whole experiment is conducted by the orthogonal experiment. By using grey relational analysis, the influence of every parameter is estimated, which offers foundation to optimize. By using the Taughi method, better pa-rameters are found. After tested by the experiment, the optimum parameter is confirmed to achieve a better performance that power consumption is reduced by 73. 1% while the surface roughness reduced by 75. 9% . What is more, the parame-ters can increase the productivity significantly and are easy to get, which means that the optimization is achieved.