Application of Weighted Dynamic SVDD in Nonlinear Process Monitoring

Authors

Yanhong Xie, 1. Department of Science Shenyang University of Chemical Technology, Shenyang 110142, China;;
Chengao Sun, 2. College of Information Engineering Shenyang University of Chemical Technology, Shenyang 110142, China;
Li Yuan, 2. College of Information Engineering Shenyang University of Chemical Technology, Shenyang 110142, China;

Abstract

Abstract: Due to the complexity of the chemical process, the data are often characterized by dynamics and correlation between sequences. Traditional support vector data description (SVDD) methods are difficult to guarantee real-time monitoring online. A Weighted-Dynamic-SVDD (WDSVDD) method was proposed to monitor fault in real time online. The dynamic method was introduced, and the correlation between the data was considered. The weighted information was used to highlight the useful information. The model was established by using SVDD method, and the online real-time fault monitoring was realized. The method not only overcomes the adverse effect of non-Gaussian and nonlinearity, but also considers dynamic characteristics and correlation between sequences of the processing data. Applications in the numerical simulation and TE process instance verify the effectiveness of the proposed method.

Recommended Citation

Xie, Yanhong; Sun, Chengao; and Yuan, Li (2020) "Application of Weighted Dynamic SVDD in Nonlinear Process Monitoring," Journal of System Simulation: Vol. 29: Iss. 7, Article 15.
DOI: 10.16182/j.issn1004731x.joss.201707015
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss7/15

First Page

1506

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201707015

Last Page

1513

CLC

TP277

Recommended Citation

Xie Yanhong, Sun Chengao, Li Yuan. Application of Weighted Dynamic SVDD in Nonlinear Process Monitoring[J]. Journal of System Simulation, 2017, 29(7): 1506-1513.

DOI

10.16182/j.issn1004731x.joss.201707015