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Study on small multiplicative fault detection using Canonical Correlation Analysis with the local approach

机译:基于规范相关分析的局部方法小乘法故障检测研究

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Canonical correlation analysis(CCA) could be utilized for analyzing a linear static process when the input-output relationship is explicitly existing. Based on the canonical variates obtained by the CCA method, a novel fault detection approach can be designed by resembling the principal component analysis (PCA) and the partial least squares (PLS) approaches. However, in this paper, the traditional CCA approach will be shown insensitive to one kind of fault, i.e., multiplicative fault (change). Based on this motivation, a modified statistic based on the local approach is introduced to help CCA approach further improve its acceptance for detecting multiplicative changes in the static processes. The new method will be verified through its application to a continuous stirred tank heater (CSTH).
机译:当输入-输出关系显式存在时,典型相关分析(CCA)可用于分析线性静态过程。基于CCA方法得到的典型变量,可以设计一种新的故障检测方法,类似于主成分分析(PCA)和偏最小二乘法(PLS)。然而,在本文中,传统的CCA方法将对一种故障(即乘法故障(变化))不敏感。基于这一动机,该文引入一种基于局部方法的修正统计量,以帮助CCA方法进一步提高其对静态过程中乘法变化检测的接受度。新方法将通过应用于连续搅拌罐式加热器(CSTH)进行验证。

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