Adaptive PCA based fault diagnosis scheme in imperial smelting process

作者：Hu, Zhikun; Chen, Zhiwen^*; Gui, Weihua; Jiang, Bin

来源：ISA Transactions, 2014, 53(5): 1446-1455.

DOI：10.1016/j.isatra.2013.12.018

• Imperial smelting process monitoring
• Fault diagnosis
• Adaptive principal component analysis

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.

• 出版日期2014-9
• 单位南京航空航天大学; 中南大学