SCI和EI收录∣中国化工学会会刊

中国化学工程学报 ›› 2021, Vol. 39 ›› Issue (11): 183-192.DOI: 10.1016/j.cjche.2020.09.067

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

Quality oriented multimode processes monitoring based on a novel hierarchical common and specific structure with different order information

Yun Wang1, Yuchen He2, De Gu3   

  1. 1 Mechanical and Electrical Engineering Department, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou 311231, China;
    2 College of Mechanical & Electrical Engineering, China Jiliang University, Hangzhou 310018, China;
    3 School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
  • 收稿日期:2020-04-03 修回日期:2020-09-04 出版日期:2021-11-28 发布日期:2021-12-27
  • 通讯作者: Yuchen He
  • 基金资助:
    This work is supported by the National Natural Science Foundation of China (61903352), China Postdoctoral Science Foundation (2020M671721), Zhejiang Province Natural Science Foundation of China (LQ19F030007), Natural Science Foundation of Jiangsu Province (BK20180594), Project of department of education of Zhejiang province (Y202044960),Project of Zhejiang Tongji Vocational College of Science and Technology (TRC1904) and Foundation of Key Laboratory of Advanced Process Control for Light Industry (Jiangnan University), Ministry of Education, P.R. China, APCLI1803.

Quality oriented multimode processes monitoring based on a novel hierarchical common and specific structure with different order information

Yun Wang1, Yuchen He2, De Gu3   

  1. 1 Mechanical and Electrical Engineering Department, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou 311231, China;
    2 College of Mechanical & Electrical Engineering, China Jiliang University, Hangzhou 310018, China;
    3 School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
  • Received:2020-04-03 Revised:2020-09-04 Online:2021-11-28 Published:2021-12-27
  • Contact: Yuchen He
  • Supported by:
    This work is supported by the National Natural Science Foundation of China (61903352), China Postdoctoral Science Foundation (2020M671721), Zhejiang Province Natural Science Foundation of China (LQ19F030007), Natural Science Foundation of Jiangsu Province (BK20180594), Project of department of education of Zhejiang province (Y202044960),Project of Zhejiang Tongji Vocational College of Science and Technology (TRC1904) and Foundation of Key Laboratory of Advanced Process Control for Light Industry (Jiangnan University), Ministry of Education, P.R. China, APCLI1803.

摘要: Due to higher demands on product diversity, flexible shift between productions of different products in one equipment becomes a popular solution, resulting in existence of multiple operation modes in a single process. In order to handle such multi-mode process, a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode. In addition, both low and high order information are considered in each layer. The common and specific information within each mode can be captured and separated into several subspaces according to the different order information. The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman (TE) benchmark. Compared with previous methods, superiority of the proposed method is validated by the better monitoring results.

关键词: Multimode processes monitoring, Dual iterations, Double layer information extraction, High order expansion, Quality related

Abstract: Due to higher demands on product diversity, flexible shift between productions of different products in one equipment becomes a popular solution, resulting in existence of multiple operation modes in a single process. In order to handle such multi-mode process, a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode. In addition, both low and high order information are considered in each layer. The common and specific information within each mode can be captured and separated into several subspaces according to the different order information. The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman (TE) benchmark. Compared with previous methods, superiority of the proposed method is validated by the better monitoring results.

Key words: Multimode processes monitoring, Dual iterations, Double layer information extraction, High order expansion, Quality related