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《中国化学工程学报(英文版)》 2008-01
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Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling

Changkyoo Yoo, Minhan Kim, Sunjin Hwang, Yongmin Jo and Jongmin OhCollege of Environmental and Applied Chemistry, Green Energy Center, Kyung Hee University, Gyeonggi-Do,446-701, Korea  
A new on-line predictive monitoring and prediction model for periodic biological processes is proposedusing the multiway non-Gaussian modeling. The basic idea of this approach is to use multiway non-Gaussian mod-eling to extract some dominant key components from daily normal operation data in a periodic process, and subse-quently combining these components with predictive statistical process monitoring techniques. The proposed pre-dictive monitoring method has been applied to fault detection and diagnosis in the biological wastewater-treatmentprocess, which is based on strong diurnal characteristics. The results show the power and advantages of the pro-posed predictive monitoring of a continuous process using the multiway predictive monitoring concept, which isthus able to give very useful conceptual results for a daily monitoring process and also enables a more rapid detec-tion of the process fault than other traditional monitoring methods.
【Fund】: the Korea Research Foundation Grant Funded by the Korean Government (MOEHRD) (KRF-2007-331-D00089) ;; Funded by Seoul Development Institute (CS070160)
【CateGory Index】: TQ06
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1 ZHANG Xian-lin,YU Zuo-jun(College of Information and Control Engineering,University of Petroleum,Dongying 257061,China);Application of a Modified Fuzzy Partial Least Squares Model in Soft Measurement[J];Control Engineering of China;2008-S2
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