基于LS-SVR的钻削工艺参数优化研究  

Study of Parameter Optimization in Drilling Process Based on LS-SVR

作　　者：崔庆安 谷丰盈 禹建丽 CUI Qing'an;GU Fengying;YU Jianli(School of Economics and Management,Shanghai Maritime University,Shanghai 201306,China;School of Management Engineering,Zhengzhou University of Aeronautics,Zhengzhou,Henan 450046,China)

机构地区：[1]上海海事大学经济管理学院,上海201306 [2]郑州航空工业管理学院管理工程学院,河南郑州450046

出　　处：《工业工程与管理》2022年第5期11-18,共8页Industrial Engineering and Management

基　　金：国家自然科学基金面上项目(71571168);国家创新方法工作专项(2019IM020200);国家自然科学基金河南省联合基金重点项目(U1904211);河南省高校科技创新人才支持计划(2019cx007);河南省科技攻关计划项目(182102210107)。

摘　　要：为提高钻削工艺生产效率,同时得到与产品所需精度相匹配的参数,提出一种基于LSSVR的多响应模糊参数优化方法。首先,通过犹豫化处理,全面度量噪声干扰,增强参数设计的稳定性。其次,将灰色关联分析与LS-SVR相结合进行参数设计,获得最优模糊参数组合。最后,将所研究方法应用于AISI 304不锈钢钻削过程的实证研究中,得到3组优化参数组合,为生产决策者提供更多选择,有效解决了参数精度与生产条件不匹配的问题。To improve the productivity of drilling process and obtain the parameters matching the required precision of the product,a fuzzy parameter optimization approach of multi-response based on LS-SVR was proposed.Firstly,the hesitant processing measured the noise comprehensively,which enhanced the stability of parameter design.Secondly,grey relational analysis was combined with LSSVR for parameter design to obtain the optimal fuzzy parameter combination.Finally,the studied method was applied to the empirical research on the drilling process of AISI 304 stainless steel.Three sets of optimized parameter combinations were obtained,which provided more choices for production decision-makers.The optimized parameter combinations effectively solved the problem that the parameters’accuracy did not match with its production conditions.

关 键 词：多响应参数优化 LS-SVR 模糊参数组合 灰色关联分析 

分 类 号：TH162[机械工程—机械制造及自动化] TG146[一般工业技术—材料科学与工程]