基于模糊数学和神经网络BP算法的切削液选择  

Selection of Cutting Fluid Based on Fuzzy Mathematics and Neural Network BP Algorithm

作　　者：黄建 汪永超[1] 贾明刚 HUANG Jian;WANG Yong-chao;JIA Ming-gang(School of Manufacturing Science and Engineering,Sichuan University,Chengdu 610065,China)

机构地区：[1]四川大学制造科学与工程学院,成都610065

出　　处：《组合机床与自动化加工技术》2018年第8期160-163,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家"十一五"科技支撑计划项目(2006BAC02A02)

摘　　要：以机械加工工艺过程中切削液为研究对象,从机加工产品的精度,加工成本,零件的寿命,零件的质量,加工的速度与效率,环境的影响等方面来研究机械加工过程和产品的生产质量等相关问题。切削液的选择是采取了一个多目标,多方案,多原则的过程。文章提出一种以模糊数学和神经网络BP算法为基础的切削液选择方法,实现了对切削液识别和分析。文章以基本模糊数,建立起切削液选择方案模型;以大量的切削数据用神经网络BP算法建立应用识别模型。从结果中对比以前的选择方法,发现选择的效果有待提高,在加工质量保证的情况下,文章从经济性,效率性,环保性等角度的优化。切削液的选择在机械加工的质量上有着重要的作用,合理的选择切削液对能明显改善机加工产品质量。The machining process and the production of the products are studied from the aspects of machining precision,processing cost,part life,parts quality,processing speed and efficiency,environmental impact,etc. in the machining process of machining process. Quality and other related issues. The choice of cutting fluid is to take a multi-objective,multi-program,multi-principle process. In this paper,a cutting fluid selection method based on fuzzy mathematics and neural network BP algorithm is proposed to realize the recognition and analysis of cutting fluid. In this paper,the model of cutting fluid selection is established with the basic fuzzy number. The application recognition model is established by using the neural network BP algorithm with a lot of cutting data. From the results in comparison with the previous selection method,found that the effect of choice to be improved,in the case of processing quality assurance,the article from the economic,efficiency,environmental protection and other aspects of optimization. The choice of cutting fluid in the quality of mechanical processing has an important role,a reasonable choice of cutting fluid can significantly improve the quality of machining products.

关 键 词：切削液 模糊数学 神经网络 

分 类 号：TH166[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]