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A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process

机译：确定多元过程中故障质量变量的混合ICA-SVM方法

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摘要

The monitoring of a multivariate process with the use of multivariate statistical process control (MSPC) charts has received considerable attention. However, in practice, the use of MSPC chart typically encounters a difficulty. This difficult involves which quality variable or which set of the quality variables is responsible for the generation of the signal. This study proposes a hybrid scheme which is composed of independent component analysis (ICA) and support vector machine (SVM) to determine the fault quality variables when a step-change disturbance existed in a multivariate process. The proposed hybrid ICA-SVM scheme initially applies ICA to the Hotelling T~2 MSPC chart to generate independent components (ICs). The hidden information of the fault quality variables can be identified in these ICs. The ICs are then served as the input variables of the classifier SVM for performing the classification process. The performance of various process designs is investigated and compared with the typical classification method. Using the proposed approach, the fault quality variables for a multivariate process can be accurately and reliably determined.
机译：使用多变量统计过程控制（MSPC）图表监视多变量过程已受到相当多的关注。但是，实际上，使用MSPC图表通常会遇到困难。这很困难，涉及哪个质量变量或哪个质量变量集负责信号的生成。该研究提出了一种混合方案，该方案由独立分量分析（ICA）和支持向量机（SVM）组成，用于确定多元过程中存在阶跃变化扰动时的故障质量变量。提出的混合ICA-SVM方案最初将ICA应用于Hotelling T〜2 MSPC图，以生成独立分量（IC）。故障质量变量的隐藏信息可以在这些IC中识别。然后，将这些IC用作分类器SVM的输入变量，以执行分类过程。研究了各种工艺设计的性能，并与典型的分类方法进行了比较。使用提出的方法，可以准确可靠地确定多元过程的故障质量变量。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第8期|284910.1-284910.12|共12页
  • 作者

    Yuehjen E. Shao; Chi-Jie Lu; Yu-Chiun Wang;

  • 作者单位

    Department of Statistics and Information Science, Fu Jen Catholic University, Hsinchuang, New Taipei City 24205, Taiwan;

    Department of Industrial Management, Chien Hsin University of Science and Technology,Taoyuan County, Zhongli 32097, Taiwan;

    Department of Statistics and Information Science, Fu Jen Catholic University, Hsinchuang, New Taipei City 24205, Taiwan;

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