On-Line Adaptive and Nonlinear Process Monitoring of a Pilot-Scale Sequencing Batch Reactor |
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Authors: | Chang Kyoo Yoo In-Beum Lee Peter A Vanrolleghem |
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Institution: | (1) BIOMATH, Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, B-9000 Gent, Belgium;(2) School of Environmental Science and Engineering, Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, Korea |
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Abstract: | This article describes the application of on-line nonlinear monitoring of a sequencing batch reactor (SBR). Three-way batch data of SBR are unfolded batch-wisely, and then a adaptive and nonlinear multivariate monitoring method is used to capture the nonlinear characteristics of normal batches. The approach is successfully applied to an 80 L SBR for biological wastewater treatment, where the SBR poses an interesting challenge in view of process monitoring since it is characterized by nonstationary, batchwise, multistage, and nonlinear dynamics. In on-line batch monitoring, the developed adaptive and nonlinear process monitoring method can effectively capture the nonlinear relationship among process variables of a biological process in a SBR. The results of this pilot-scale SBR monitoring system using simple on-line measurements clearly demonstrated that the adaptive and nonlinear monitoring technique showed lower false alarm rate and physically meaningful, that is, robust monitoring results. |
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Keywords: | adaptive batch monitoring multiway kernel principal component analysis (MKPCA) nonlinear biological process sequencing batch reactor (SBR) |
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