摘要
零件表面粗糙度对其使用性能有重要影响。为了解决零件表面单一粗糙度参数不能全面反映零件加工表面缺陷的问题,提出一种将基于相关性分析和主元分析的多变量统计过程控制应用于电化学光整加工零件表面均匀性评价的方法。设计无表面缺陷和有表面缺陷两个样件进行对比实验,在电化学光整加工之后记录两个样件的多项表面粗糙度参数,先进行多个参数的单变量统计过程控制,再对多个粗糙度参数进行相关性分析和主元分析,得到综合评价值绘制统计控制图。对比分析结果表明:对于存在局部缺陷的表面,相比单一粗糙度参数,采用综合评价控制图检测零件表面缺陷更准确;基于相关性分析和主元分析的多变量统计过程控制是评价电化学光整加工零件表面均匀性的有效方法。
Surface roughness of a part has a significant impact on its performance.In order to solve the problem that the single roughness parameter of the part surface cannot fully reflect the surface defects of the part,a method of applying multivariate statistical process control based on correlation analysis and principal component analysis was proposed to evalute the surface uniformity of electrochemical finishing parts.Two samples without and with surface defects were designed for comparative experiments,and a set of surface roughness parameters of the two samples were recorded after electrochemical finishing.Univariate statistical process control of multiple parameters was carried out,and then correlation analysis and principal component analysis of multiple roughness parameters were carried out to obtain the comprehensive evaluation value and to draw statistical control charts.The comparative analysis results show that for the surface with local defects,compared with the single roughness parameter,the comprehensive evaluation control chart is more accurate in detecting the surface defects of the parts.Multivariate statistical process control based on correlation analysis and principal component analysis is an effective method to evaluate the surface uniformity of electrochemical finishing parts.
作者
樊双蛟
李登榜
杨逸
庞桂兵
FAN Shuangjiao;LI Dengbang;YANG Yi;PANG Guibing(School of Mechanical Engineering and Automation,Dalian Polytechnic University,Dalian Liaoning 116034,China)
出处
《机床与液压》
北大核心
2024年第19期21-26,共6页
Machine Tool & Hydraulics
基金
国家自然科学基金面上项目(51975081)
辽宁省教育厅科学研究经费项目(J2020106)。
关键词
表面质量
多变量统计过程控制
主元分析
粗糙度参数
surface quality
multivariate statistical process control
principal component analysis
roughness parameters
