Abstract

In this paper, data-driven modeling and multiresolution analysis (MRA) are applied for a full-scale wastewater treatment plant (WWTP). The proposed method is based on modeling by partial least squares (PLS) and multiscale monitoring by a generic dissimilarity measure (GDM), which is suitable for nonstationary and non-normal process monitoring such as a biological process. Case study in an industrial plant showed that the PLS model could give good modeling performance and analyze the dynamics of a complex plant and MRA was useful to detect and isolate various faults due to its multiscale nature. The proposed method enables us to show the underlying phenomena as well as to filter out unwanted and disturbing phenomena.

참고문헌 (22)

1. Olsson, G. and Newell, B., Wastewater Treatment Systems: Modelling, diagnosis and Control, IWA, UK (1999) 
2. Teppola, P., Multivariate process monitoring of sequential process data - A chemometric approach, Ph.D. Thesis, Lappeenranta University, Finland (1999) 
3. Yoo, C. K., Choi, S. W. and Lee, I., 'Disturbance detection and Isolation in the Activated Sludge Process,' Water Sci. Tech., 45(4-5), 217-226 (2002) 
4. Yoo, C. K. Vanrolleghem, P. A. and Lee, I., 'Nonlinear modeling and adaptive monitoring with Fuzzy and multivariate statistical method in biological wastewater treatment plant,' J. Biotechnol., 105(1-2), 135-163 (2003) 
5. Yoo, C. K., Lee, D. S. and Vanrolleghem, P. A., 'Application of multiway ICA for on-line monitoring of a sequencing batch reactor,' Water Res., 38(7), 1715-1732 (2004a) 
6. Yoo, C. K., Yoon, H. B., Lee, I. B., Vanrolleghem, P. A. and Rosen, C., 'Application of fuzzy partial least squares (FPLS) modeling nonlinear biological processes,' Korean J. Chem. Eng., 21(6), 1087-1097 (2004b) 
7. Ragot, J., Grapin, G., Chatellier, P. and Colin, F., 'Modeling of a water treatment plant. A multi-model representation,' Environmetrics, 12, 599-623 (2001) 
8. Henze, M., Guier, W., Mino, T. And van Loosdrecht M. C. M., Activated sludge models ASM1, ASM2, ASM2d and ASM3 IAWPRC Scientific and Technical Report No.9. International Water Association, UK (2000) 
9. Yoon, S. P., 'Comparison of biological nutrient removal processes by activated sludge model no.2,' J. of Korean Society of Environmental Engineers, 21(4) 609-616 (1999) 
10. Kim, I. S., Young, J. C., Kim, S. Y. and Kim, S. M., 'Development of monitoring methodology to fingerprint the activated sludge processes using oxygen uptake rate,' Environ. Eng. Res., 6(4), 251-259 (2001) 
11. Kim, S. H., Lee, H. J., Kim, C. W., Ko, J. H. and Woo, H. J., 'Application of the genetic algorithm for the parameter estimation of activated sludge models No.1,' J. of Korean Society of Environmental Engineers, 24(10), 1723-1730 (2002) 
12. Jeong, H. S., Choi, D. J. and Shin, H. S., 'Estimation of model parameters in organic degradation and nitrification processes of ASM3 using respirometry and genetic algorithm,' J. of Korean Society of Environmental Engineers, 26(8), 904-910 (2004) 
13. Johnson, R. A. and Wichern, D. W., Applied Multivariate Statistical Analysis, 3nd ed., Prentice Hall, Englewood Cliffs, USA (1992) 
14. Wise, B. M. and Gallagher, N. B., 'The process chemometrics approach to process monitoring and fault detection,' J. Process Control, 6, 329-348 (1996) 
15. Krofta, M., Herath, B., Burgess, D. and Lampman, L., 'An attempt to understand dissolved air flotation using multivariate analysis,' Water Sci. Tech., 31(3-4), 191-201 (1995) 
16. Van Dongen, G. and Geuens, L., 'Multivariate tie series analysis for design and operation of a biological wastewater treatment plant,' Water Res., 32, 691-700 (1998) 
17. Bakshi, B. R., 'Multiscale PCA with application to multivariate statistical process monitoring,' AlChE J, 44, 1596-1610 (1998) 
18. Yoo, C. K., Choi, S. W. and Lee, I., 'Dynamic monitoring method for multiscale fault detection and diagnosis in MSPC,' Ind. Eng. Chem. Res., 41, 4303-4317 (2003) 
19. Eriksson, L., Hermens, J. L. M., Johansson, E., Verhaar, H. J. M. and Wold, S., 'Multivariate analysis of aquatic toxicity data with PLS,' Aqu. Sci., 57(3), 1015-1621 (1995) 
20. Lee, D. S., Neural Network Modeling of Biological Wastewater Treatment Processes, Ph.D. Dissertation, POSTECH, Korea (2000) 
21. Rosen, C. and Lennox, J. A., 'Multivariate and multiscle monitoring of wastewater treatment operation,' Water Res., 35(14), 3402-3410 (2001) 
22. Kano, M., Nagao, K., Hasebe, S., Hashimoto, I., Ohno, H., Strauss, R. and Bakshi, B., 'Comparison of statistical process monitoring methods: Application to the eastman challenge Problem,' Comput. Chem. Eng., 24, pp. 175-181 (2000) 

이 논문을 인용한 문헌 (0)

1. 이 논문을 인용한 문헌 없음