Batch process monitoring based on WGNPE-GSVDD related and independent variables

doi:10.1016/j.cjche.2018.09.022

Chinese Journal of Chemical Engineering ›› 2018, Vol. 26 ›› Issue (12): 2549-2561.DOI: 10.1016/j.cjche.2018.09.022

• Process Systems Engineering and Process Safety • 上一篇下一篇

Batch process monitoring based on WGNPE-GSVDD related and independent variables

Yongyong Hui^1,2, Xiaoqiang Zhao^1,2,3

1 College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
2 Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China;
3 National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou 730050, China

收稿日期:2018-05-16 修回日期:2018-08-15 出版日期:2018-12-28 发布日期:2019-01-09
通讯作者: Xiaoqiang Zhao
基金资助:
Supported by the National Natural Science Foundation of China (No. 61763029), and the Natural Science Foundation of Gansu Province (1610RJZA016).

Batch process monitoring based on WGNPE-GSVDD related and independent variables

Yongyong Hui^1,2, Xiaoqiang Zhao^1,2,3

1 College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
2 Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China;
3 National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Received:2018-05-16 Revised:2018-08-15 Online:2018-12-28 Published:2019-01-09
Contact: Xiaoqiang Zhao
Supported by:
Supported by the National Natural Science Foundation of China (No. 61763029), and the Natural Science Foundation of Gansu Province (1610RJZA016).

摘要/Abstract

摘要： In many batch processes, there are related or independence relationships among process variables. The traditional monitoring method usually carries out a single statistical model according to the related or independent method, and in the feature extraction there is not fully taken into account the characterization of fault information, it will make the process monitoring ineffective, so a fault monitoring method based on WGNPE (weighted global neighborhood preserving embedding)-GSVDD (greedy support vector data description) related and independent variables is proposed. First, mutual information method is used to separate the related variables and independent variables. Secondly, WGNPE method is used to extract the local and global structures of the related variables in batch process and highlight the fault information, GSVDD method is used to extract the process information of the independent variables quickly and effectively. Finally, the statistical monitoring model is established to achieve process monitoring based on WGNPE and GSVDD. The effectiveness of the proposed method was verified by the penicillin fermentation process.

关键词: Batch process, Monitoring, Related and independent variables, Global-local, Support vector data description

Abstract: In many batch processes, there are related or independence relationships among process variables. The traditional monitoring method usually carries out a single statistical model according to the related or independent method, and in the feature extraction there is not fully taken into account the characterization of fault information, it will make the process monitoring ineffective, so a fault monitoring method based on WGNPE (weighted global neighborhood preserving embedding)-GSVDD (greedy support vector data description) related and independent variables is proposed. First, mutual information method is used to separate the related variables and independent variables. Secondly, WGNPE method is used to extract the local and global structures of the related variables in batch process and highlight the fault information, GSVDD method is used to extract the process information of the independent variables quickly and effectively. Finally, the statistical monitoring model is established to achieve process monitoring based on WGNPE and GSVDD. The effectiveness of the proposed method was verified by the penicillin fermentation process.

Key words: Batch process, Monitoring, Related and independent variables, Global-local, Support vector data description

Yongyong Hui, Xiaoqiang Zhao. Batch process monitoring based on WGNPE-GSVDD related and independent variables[J]. Chinese Journal of Chemical Engineering, 2018, 26(12): 2549-2561.

Yongyong Hui, Xiaoqiang Zhao. Batch process monitoring based on WGNPE-GSVDD related and independent variables[J]. Chin.J.Chem.Eng., 2018, 26(12): 2549-2561.

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Batch process monitoring based on WGNPE-GSVDD related and independent variables

Batch process monitoring based on WGNPE-GSVDD related and independent variables

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