On the Application of PCA Technique to Fault Diagnosis

被引:36
作者
Naik A [1 ]
机构
[1] Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen
关键词
process monitoring; fault diagnosis; principal component analysis (PCA); multivariate analysis;
D O I
暂无
中图分类号
TH165.3 [];
学科分类号
080202 ;
摘要
In this paper, we briefly address the application of the standard principal component analysis (PCA) technique to fault detection and identification. Based on an analysis of the existing test statistic, we propose a new test statistic, which is similar to the Hawkin’s TH 2 statistic but without the numerical drawback. In comparison with the SPE index, the threshold setting associated with the new statistic is computationally simpler. Our further study is dedicated to the analysis of fault sensitivity. We consider the off-set and scaling faults, and evaluate the test statistic by viewing its sensitivity to the faults. Our final study focuses on identifying off-set and scaling faults. To this end, two algorithms are proposed. This paper also includes some critical remarks on the application of the PCA technique to fault diagnosis.
引用
收藏
页码:138 / 144
页数:7
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