摘要
切削参数的选择和优化是提高机械零件加工精度和稳定性的重要保证。本文以汽车轴承支架轴承孔的精镗切削为例,选择对零件切削精度影响较大的五种参数,采用田口实验及计算机智能技术中的倒传递神经网络和遗传算法等方法的综合运用,对切削参数进行优化,迅速有效地找出最佳切削参数组合,从而提升零件质量和加工过程的稳定性,为提高机械加工企业的市场竞争力开辟了一种新的思路和途径。
Selecting and optimizing cutting parameters ensures the processing precision and stability of mechanical components. Based on the fine boring of the bearing holes of the auto bearing support, Taguchi experiments, the back-propagation neural network and genetic algorithms were employed to optimize five cutting parameters that may largely affect cutting precision. Optimum cutting parameter settings were obtained. The results indicate that the integrated use of the methods can improve the quality of the mechanical components and the stability of processing.
出处
《福建工程学院学报》
CAS
2013年第6期573-577,共5页
Journal of Fujian University of Technology
基金
全国统计科研计划重点项目(2012LZ037)
关键词
切削参数
田口方法
倒传递神经网络
遗传算法
cutting parameter
Taguchi method
back-propagation neural network
genetic algorithm
