基于支持向量数据描述的指数加权移动平均控制图

摘要

基于支持向量数据描述(Support Vector Data Description,SVDD)的D2控制图的重要特点是对过程数据的抽样分布没有特定的要求.由于D2控制图仅使用当前观测点的值来计算统计量,对过程的小偏移并不敏感,在SVDD模型的基础上,提出了基于D2距离的多元加权移动平均(multivariate exponentially weighted moving average,MEWMA)控制图,用S-MEWMA表示.仿真结果表明,无论过程数据服从正态分布还是非正态分布,S-MEWMA控制图均优于D2控制图.%The D2 control chart based on support vector data description (SVDD) has an advantage that it does not require a known sampling distribution for the process data. However, it uses only the current samples , leading to that it is insensitive to small shifts. To solve this problem, based on SVDD method, a multivariate exponentially weighted moving average (MEWMA) control chart (denoted as S-MEWMA) is proposed in this paper. Simulation results show that the S-MEWMA chart outperforms the D control chart no matter whether a process follows a normal or non-normal distribution.