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Analysis of PCA-based reconstruction method for fault diagnosis

Lookup NU author(s): Dr Jie ZhangORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Abstract

The reconstruction method, de ned in the frame of principal component analysis, is a popular and representative method for fault diagnosis. It has been successfully applied in several industrial processes. Although the sucient condition of the uniquely fault subspace identi cation has been provided in literature, it cannot be used in practice due to the true fault subspace and magnitude is unknown. Thus this condition cannot be used to con rm whether an identi ed subspace is the true fault subspace once there are more than one subspace determined as the possible candidates. This paper shows that the true fault subspace is hard to be identi ed when a fault occurred and caused a signi cant change in the correlation of the variables while the T2 index is still in control. Through the theoretical analysis and some illustrative examples, it is shown that the reconstruction method cannot always uniquely identify the true fault subspace in these cases. This indicates that care must be taken when using the reconstruction method. Some possible solutions are also provided in order to further improve the reconstruction method.


Publication metadata

Author(s): Zhou Z, Yang C, Wen C, Zhang J

Publication type: Article

Publication status: Published

Journal: Industrial & Engineering Chemistry Research

Year: 2016

Volume: 55

Issue: 27

Pages: 7402-7410

Print publication date: 13/07/2016

Online publication date: 16/06/2016

Acceptance date: 16/06/2016

Date deposited: 17/06/2016

ISSN (print): 0888-5885

ISSN (electronic): 1520-5045

Publisher: American Chemical Society

URL: http://dx.doi.org/10.1021/acs.iecr.5b04822

DOI: 10.1021/acs.iecr.5b04822


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Funding

Funder referenceFunder name
China Scholarship Council
61290321National Science Foundation of China
61333005National Science Foundation of China
61433001National Science Foundation of China
2012AA041709National 863 Program
61490701National Science Foundation of China
61573137National Science Foundation of China

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