화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Journal of Industrial and Engineering Chemistry, Vol.21, 328-337, January, 2015
DOI10.1016/j.jiec.2014.02.042  Export Citation
A fast monitoring method for multiple operating batch processes with incomplete modeling data types
Ya-Jun Wang1, 2, Ming-Xing Jia1, †, and Zhi-Zhong Mao1
  • 1College of Information Science and Engineering, Northeastern University, Shenyang, China
  • 2College of Electronics & Information Engineering, Liaoning University of Technology, Jinzhou, China
E-mail:
For complex industrial processes with multiple operating conditions, a novel fast monitoring method, called up-down multi-model dynamic principal component analysis, is proposed with incomplete modeling data types in this paper. The method firstly classifies the process into several stages according to the operations. In each stage the data with similar operations are clustered together. Multiple model structures are constructed along with the variation of the cluster number. When on-linemonitoring, the up-down monitoringmethod is proposed to monitor a new batch type. The effectiveness of the proposed monitoring method is demonstrated through the 120 t ladle furnace (LF) steelmaking process.
Keywords:Multiple operating batch process;Incomplete modeling data types;Up-Down MDPCA;120 t Ladle furnace (LF) steelmaking process
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