Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor
SCIE
SCOPUS
- Title
- Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor
- Authors
- Yoo, CK; Villez, K; Lee, IB; Rosen, C; Vanrolleghem, PA
- Date Issued
- 2007-03-01
- Publisher
- JOHN WILEY & SONS INC
- Abstract
- Biological processes exhibit different behavior depending on the influent loads, temperature, microorganism activity, and soon. It has been shown that a combination of several models can provide a suitable approach to model such processes. In the present study, we developed a multiple statistical model approach for the monitoring of biological batch processes. The proposed method consists of four main components: (1) multiway principal component analysis (MPCA) to reduce the dimensionality of data and to remove collinearty; (2) multiple models with a;posterior probability for modeling different operating regions; (3) local batch monitoring by the T-2- and Q-statistics of the specific local model; and (4) a new discrimination measure (DM) to identify when the system has shifted to a new operating condition. Under this approach, local monitoring by multiple models divides the entire historical data set into separate regions, which are then modeled separately. Then; these local regions can be supervised separately; leading to more effective batch monitoring. The proposed method is applied to a pilot-scale 80-L sequencing batch reactor (SBR) for biological wastewater treatment. This SBR is characterized by nonstationary, batchwise, and multiple operation modes. The results obtained for the pilot-scale SBR indicate that the proposed method has the ability to model multiple operating conditions, to identify various operating regions, and also to determine whether the biosystem has shifted to a new operating condition. Our findings show that the local monitoring approach can give more reliable and higher resolution monitoring results than the global model. (c) 2006 Wiley Periodicals, Inc.
- Keywords
- batch monitoring and supervision; biological system; multiple operational modes; probabilistic modeling; sequencing batch reactor (SBR); wastewater treatment; PRINCIPAL COMPONENT ANALYSIS; MULTIVARIATE; REMOVAL
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/23557
- DOI
- 10.1002/BIT.21220
- ISSN
- 0006-3592
- Article Type
- Article
- Citation
- BIOTECHNOLOGY AND BIOENGINEERING, vol. 96, no. 4, page. 687 - 701, 2007-03-01
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