International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Monitoring of Bioreactor using Statistical Techniques

Author Affiliations

  • 1Department of Chemical Engineering, NIT Rourkela, Orissa-769008, INDIA
  • 2Department of Chemical Engineering, NIT Rourkela, Orissa-769008, INDIA

Res.J.chem.sci., Volume 1, Issue (3), Pages 114-119, June,18 (2011)

Abstract

Present study addresses the monitoring of a continuous bioreactor operation. New methodologies; based on clustering time series data and moving window based pattern matching have been proposed for the detection of fault in the chosen bioreactor process. A modified k-means clustering algorithm using similarity measure as a convergence criterion has been adopted for discriminating among time series data pertaining to various operating conditions. The proposed distance and PCA based combined similarity along with the moving window approach were used to discriminate among the normal operating conditions as well as detection of fault for the process taken up.

References

  1. Singhal A. and Seborg D.E., Pattern matching in multivariate time series databases using a moving window approach, Ind. Eng. Chem. Res., 41, 3822-3838 (2002)
  2. Singhal A. and Seborg D.E., Matching Patterns from Historical Data Using PCA and Distance Similarity Factors, Proceedings of the 2001 American Control Conference; IEEE: Piscataway, NJ., 1759-1764 (2001)
  3. Johannesmeyer M.C., Singhal A. and Seborg D.E., Pattern Matching in Historical Data, AIChE J., 48, 2022-2038 (2002)
  4. Edwards V.H., Ko R.C. and Balogh S.A., Dynamics and control of continuous microbial propagators to subject substrate inhibition, Biotechnol, Bioeng., 14, 939-974 (1972)
  5. Agrawal P. and Lim H.C., Analysis of various control schemes for continuous bioreactors, Adv. Biochem. Eng./Biotechnol., 30, 61-90 1984)
  6. Kaushikram K.S., Damarla S.K. and Kundu M., Design of neural controllers for various configurations of continuous bioreactor, International Conference on System Dynamics and Control-ICSDC (2010)
  7. Kourti T. and MacGregor J.F., Multivariate SPC methods for process and product monitoring, J. Quality Tech., 28,409–428 1996)
  8. Martin E.B. and Morris A.J., An overview of multivariate statistical process control in continuous and batch performance monitoring, Trans. Inst. Meas. and Control, 18, 51–60 1996)
  9. Krzanowski W.J., Between-groups comparison of principal components, J. Amer. Stat. Association., 74, 703–707 (1979)
  10. Singhal A. and Seborg D.E., Clustering multivariate time series data, J. Chemometrics, 19, 427-438 (2005)