Multivariate Nonlinear Statistical Process Control of a Sequencing Batch Reactor

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概要

• 論文の詳細を見る

• This research describes the application of a multivariate statistical process control method to a pilot-scale sequencing batch reactor (SBR) using a batchwise nonlinear monitoring technique for a denoising effect. Three-way batch data of normal batches are unfolded batch-wise and then a kernel principal component analysis (KPCA) is applied to capture the nonlinear dynamics within normal batch processes. The developed monitoring method was successfully applied to an 80-l sequencing batch reactor (SBR) for biological wastewater treatment, which is characterized by a variety of nonstationary and nonlinear characteristics. In the multivariate analysis and batch-wise monitoring, the developed nonlinear monitoring method can effectively capture the nonlinear relations within the batch process data and clearly showed the power of nonlinear process monitoring and denoising performance in comparison with linear methods.

• 社団法人 化学工学会の論文
• 2006-01-01

著者

• Lee In-beum

  Biomath : Department Of Applied Mathematics Biometrics And Process Control Ghent University

• Yoo Chang

  Biomath : Department Of Applied Mathematics Biometrics And Process Control Ghent University

• VILLEZ Kris

  School of Environmental Science and Engineering, Department of Chemical Engineering, Pohang Universi

• VANROLLEGHEM A.

  School of Environmental Science and Engineering, Department of Chemical Engineering, Pohang Universi

• Villez Kris

  School Of Environmental Science And Engineering Department Of Chemical Engineering Pohang University

• Vanrolleghem A.

  School Of Environmental Science And Engineering Department Of Chemical Engineering Pohang University

関連論文

• Multivariate Nonlinear Statistical Process Control of a Sequencing Batch Reactor

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