基于MS-LSSVM的多元残差控制图质量诊断方法研究
首发时间:2019-04-30
摘要:利用多变量残差控制图对多元变量进行质量诊断是当前质量管控的热门课题,当数据特征差别较大时,该方法的诊断精度不高。为此,针对这一问题,本文提出了基于主成分分析与数据分类的多阶最小二乘支持向量机(MS-LSSVM)的残差控制图诊质量诊断方法。阐述了基于MS-LSSVM的控制图诊断流程,以某公司的实际生产数据为例进行验证,并与基本的LS-SVM控制图诊断方法进行了对比,证实了改进方法在诊断精度与灵敏度上的优越性。
关键词: 多变量诊断 残差控制图 多阶最小二乘支持向量机
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Research on Multivariate Residual Control Chart Quality Diagnosis Method Based on MS-LSSVM
Abstract:The quality diagnosis method research by using multivariate residual control chart is a hot topic in current quality control field. But when the quality data characteristics are apparently different, this method can not get high diagnostic accuracy. Therefore, this paper proposes a diagnosis model of residual control chart based on Multi-Step Least Squares Support Vector Machines(MS-LSSVM). Firstly, this paper have an introduce on the control chart diagnosis process based on MS-LSSVM, and then the actual data of a company is taken as an example to verify and compare with the basic least squares support vector machine algorithm model. It is verified that the improved algorithm has better performance in diagnostic accuracy and diagnostic sensitivity.
Keywords: Multivariate Diagnosis Residual Control Chart MS-LSSVM
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