Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor

Research output: Contribution to journalArticle


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.


  • Chang Kyoo Yoo
  • Kris Villez
  • In-Beum Lee
  • Christian Rosén
  • Peter A. Vanrolleghem
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Other Electrical Engineering, Electronic Engineering, Information Engineering


  • sequencing batch reactor, probabilistic modeling, operational modes, multiple, batch monitoring and supervision, biological system, (SBR), wastewater treatment
Original languageEnglish
Pages (from-to)687-701
JournalBiotechnology and Bioengineering
Issue number4
Publication statusPublished - 2007
Publication categoryResearch