Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling
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Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling
Chinese Journal of Chemical EngineeringVol. 16, Issue 1, Pages: 48-51(2008)
Affiliations:
College of Environmental and Applied Chemistry, Green Energy Center, Kyung Hee University, Gyeonggi,Do,Korea,446-701
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Published:2008
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Changkyoo Yoo, Minhan Kim, Sunjin Hwang, Yongmin Jo, Jongmin Oh. Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling[J]. , 2008, 16(1): 48-51.
DOI:
Changkyoo Yoo, Minhan Kim, Sunjin Hwang, Yongmin Jo, Jongmin Oh. Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling[J]. , 2008, 16(1): 48-51.DOI:
Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling
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 modeling 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 predictive 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 proposed 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 detection of the process fault than other traditional monitoring methods.
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