On-Line Predictive Monitoring and Prediction for Periodic Process Through Multiway Non-Gaussain Modeling
A new on-line predictive monitoring and prediction for periodic biological process is proposed using multiway non-Gaussian modeling. The basic idea of this approach is to use the multiway non-Gaussian modeling to extract some daily dominant key components from normal operating data in a periodic process and to combine them with predictive statistical process monitoring techniques. The proposed predictive monitoring method was applied to fault detection and diagnosis in the biological wastewater treatment process, which is based on strong diurnal characteristics. The results show the power and advantages of the proposed predictive monitoring of a continuous process using multi-way predictive monitoring concept, which is able to give very useful concept result of a daily monitoring and also to provide more rapid detection of the process fault than the other traditional monitoring method.
inferential sensing multiway modeling non-Gaussian distribution on-line predictive monitoring process supervision wastewater treatment process (WWTP)
ChangKyoo Yoo
College of Environmental and Applied Chemistry/Center for Environmental Study,Kyung Hee University,Gyeonggi-Do,446-701,Korea
国际会议
西安
英文
2007-08-15（万方平台首次上网日期，不代表论文的发表时间）