JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 110-117.doi: 10.6040/j.issn.1672-3961.0.2017.176

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Chemical process monitoring based on two step subspace division

YANG Yawei, SONG Bing, SHI Hongbo*   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

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Abstract: In order to solve the problem of high dimension and complex distribution of data collected from modern chemical processes, a method for monitoring chemical process was presented based on two step subspace division(TSSD). In order to reduce the complexity of process analysis, variables with similar characteristic were divided into the same space. Considering the complex distribution of data, the subspace obtained from the first step was divided into Gaussian subspace and non-Gaussian subspace. Principal component analysis(PCA)and independent component analysis(ICA)were used to establish the detection models and construct the statistics. All statistics of subspaces were integrated and used to construct the final statistics based on local outlier factor(LOF). The process results showed that the optimal missed detection rates of TSSD can be obtained for 16 faults, especially 15.375% for fault 10 and 6.75% for fault 16. The superiority monitoring performance of the proposed two steps subspace division method was proved.

Key words: process monitoring, two step subspace division, principal component analysis, local outlier factor, independent component analysis

CLC Number: 

  • TP273
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