基于神经网络和遗传算法的机床床身优化设计研究

 于添1,黄旭2,范格非3

(1.沈阳鼓风机集团研究院,辽宁 沈阳 110869;2.沈阳鼓风机集团客服公司,辽宁 沈阳 110869;3.沈阳鼓风机集团设计院,辽宁 沈阳 110869)
摘要:机床的床身的动态特性和静刚度直接影响加工精度、生产效率以及机床的使用寿命,目前机床正朝着高速、高精度、复合化以及高自动化的方向发展,因此研究机床床身的动态特性和静刚度十分必要。为提高某机床床身和横梁的动态特性和静刚度,综合运用结构动态优化原理,神经网络和遗传算法,对床身和横梁进行了结构动态特性分析,提出了该床身结构的优化方案。分析结果表明,优化方案的床身和横梁的动态性能和静刚度得到了明显提高。可供相关机床床身优化设计参考。
关键词:动态特性;神经网络;遗传算法;固有频率
中图分类号:TG502.31 文献标志码:A doi:10.3969/j.issn.1006-0316.2016.03.006
文章编号:1006-0316 (2016) 03-0025-03
Study on optimization design of machine tool based on neural network and genetic algorithm
YU Tian1,HUANG Xu2,FAN Gefei3
( 1.Research Institute of Shenyang Blower Works, Shenyang 110869, China; 2.Customer Service Center of Shenyang Blower Works, Shenyang 110869, China;
3.Design Institute of Shenyang Blower Works, Shenyang 110869, China )
Abstract:Dynamic characteristics directly affect the service life, working accuracy and manufacturing efficiency of a machine tool. Nowadays machine tools industry, have been a popular area with high level requirements in speed, accuracy and automation. In order to improve the dynamic characteristics and static stiffness of a machine tool bed and beam, integrated use of structural dynamic optimization theory, do structural dynamic characteristic analysis of machine tool bed and beam, put forward the optimization scheme of them. The analysis results show that, the dynamic performance optimization of machine tool bed and beam and the static stiffness was improved significantly, which can be reference of the optimum structural design of the related machine tools.
Key words:the dynamic characteristics;the neural network;genetic algorithm;natural frequency
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收稿日期:2015-10-10
作者简介:于添(1987-),山东潍坊人,硕士研究生,助理工程师,主要研究方向为压缩机模型级实验;黄旭(1983-),天津人,本科,助理工程师,主要研究方向为压缩机装配;范格非(1988-),重庆人,硕士研究生,助理工程师,主要研究方向为压缩机设计。
 

 

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