Structured Joint Sparse Principal Component Analysis for Fault Detection and Isolation

In order to improve the performance of fault isolation and diagnosis of principal component analysis (PCA) based methods, this article proposes a novel fault detection and isolation approach using the structured joint sparse PCA (SJSPCA). The objective function involves two regularization terms: the...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2019-05, Vol.15 (5), p.2721-2731
Main Authors: Liu, Yi, Zeng, Jiusun, Xie, Lei, Luo, Shihua, Su, Hongye
Format: Article
Language:English
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Blast furnace components
Blast furnace gas
Blast furnace practice
Fault detection
Fault detection and isolation
Gas flow
graph Laplacian
Informatics
Ironmaking
Laplace equations
Loading
Monitoring
Performance enhancement
Principal component analysis
Principal components analysis
Regularization
Sparse matrices
Sparsity
structured joint sparse principal component analysis (SJSPCA)
Variables
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Summary:In order to improve the performance of fault isolation and diagnosis of principal component analysis (PCA) based methods, this article proposes a novel fault detection and isolation approach using the structured joint sparse PCA (SJSPCA). The objective function involves two regularization terms: the l_{2,1} norm and the graph Laplacian. By imposing the l_{2,1} norm, SJSPCA is able to achieve row-wise sparsity, and introducing the graph Laplacian term can incorporate structured variable correlation information. The row-sparsity property of l_{2,1} norm ensures that the score indices associated with normal variables approaching zero and the graph Laplacian constraint helps the isolation of correlated faulty variables. Once a fault is detected, a two-stage fault-isolation strategy is considered and a score index is calculated for each variable. It is proved that the proposed two-stage strategy is capable of isolating faulty variables. The improved fault-isolation performance of SJSPCA is illustrated by a simulation example and a gas flow fault observed in an industrial blast furnace iron-making process.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2868364