Journal
ISA TRANSACTIONS
Volume 53, Issue 5, Pages 1446-1455Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2013.12.018
Keywords
Imperial smelting process monitoring; Fault diagnosis; Adaptive principal component analysis
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Funding
- Natural Science Foundation of China [60904077, 61105080, 61273159]
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In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. (C) 2013 ISA. Published by Elsevier Ltd. All rights reserved.
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