Diagnosing Upsets in Anaerobic Wastewater Treatment Using Bayesian Belief Networks
Publication: Journal of Environmental Engineering
Volume 127, Issue 4
Abstract
Bayesian belief networks are probabilistic knowledge-based expert systems that predict the probability of an event occurring or diagnose the most probable causes of specific problems. Although Bayesian belief networks calculate the probabilities of events both before and after the introduction of evidence and are particularly useful for complicated systems with nonlinear relationships between causes and effects, they have not been widely applied to wastewater treatment systems. A Bayesian belief network for diagnosing upsets in an anaerobic wastewater treatment system was developed using the anaerobic sequencing batch reactor as a model system. A new approach for determining the conditional probabilities of the states of the variables was developed using a microbial kinetics model in conjunction with Monte Carlo simulation. The completed network suggests the most probable cause of upsets to the anaerobic sequencing batch reactor and updates its suggestions as more evidence is provided. The approach used is general and may be applied to other anaerobic treatment systems.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Angenent, L. T., and Dague, R. R. ( 1995). “A laboratory-scale comparison of the UASB and ASBR processes.” 50th Purdue Industrial Waste Conf. Proc., Ann Arbor Press, Inc., Chelsea, Mich., 365–377.
2.
Bagley, D. M., and Brodkorb, T. S. ( 1999). “Modeling microbial kinetics in an anaerobic sequencing batch reactor—Model development and experimental validation.” Water Envir. Res., 71(7), 1320–1332.
3.
Barnett, M. W., and Andrews, J. F. (1992). “Expert system for anaerobic-digestion-process operation.”J. Envir. Engrg., ASCE, 118(6), 949–963.
4.
Chong, H. G., and Walley, W. J. ( 1996). “Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes.” Artificial Intelligence in Engrg., 1, 265–273.
5.
Dague, R. R., and Pidaparti, S. R. ( 1992). “Anaerobic sequencing batch reactor treatment of swine wastes.” 46th Purdue Industrial Waste Conf. Proc., Lewis, Boca Raton, Fla., 751–760.
6.
Fernandes, L., Kennedy, K. J., and Ning, Z. ( 1993). “Dynamic modelling of substrate degradation in sequencing batch anaerobic reactors (SBARs).” Water Res., 27(11), 1619–1628.
7.
Heckerman, D., Mamdani, E. H., and Wellman, M. P. ( 1995). “Real world applications of Bayesian networks.” Communications of ACM, 38(3), 24–26.
8.
Jensen, F. V. ( 1996). An introduction to Bayesian networks, Springer, New York.
9.
Kennedy, K. J., Sanchez, W. A., Hamoda, M. F., and Droste, R. L. ( 1991). “Performance of anaerobic sludge blanket sequencing batch reactors.” Res. J. Water Pollution Control Fedn., 63(1), 75–83.
10.
Korver, M., and Lucas, P. J. F. ( 1993). “Converting a rule-based expert system into a belief network.” Medical Informatics, 18, 219–241.
11.
McCabe, B., AbouRizk, S. M., and Goebel, R. (1998). “Belief networks for construction performance diagnostics.”J. Comp. in Civ. Engrg., ASCE, 12(2), 93–100.
12.
Pradhan, M., Henrion, M., Provan, G., Favero, B. D., and Huang, K. ( 1996). “The sensitivity of belief networks to imprecise probabilities: An experimental investigation.” Artificial Intelligence, 85(1–2), 363–397.
13.
Schmit, C. G., and Dague, R. R. ( 1993). “Anaerobic sequencing batch reactor treatment of swine wastes at 20°C, 25°C, and 35°C.” 48th Purdue Industrial Waste Conf. Proc., Lewis, Boca Raton, Fla., 541–549.
14.
Shizas, I. ( 2000). “Start-up of a laboratory-scale anaerobic sequencing batch reactor treating glucose.” MASc thesis, Grad. Dept. of Civ. Engrg., University of Toronto, Toronto.
15.
Speece, R. E. ( 1996). Anaerobic biotechnology for industrial wastewaters, Archae Press, Nashville, Tenn.
16.
Stiber, N. A., Pantazidou, M., and Small, M. J. ( 1999). “Expert system methodology for evaluating reductive dechlorination at TCE sites.” Envir. Sci. and Technol., 33(17), 3012–3020.
17.
Sung, S., and Dague, R. R. ( 1995). “Laboratory studies on the anaerobic sequencing batch reactor.” Water Envir. Res., 67(3), 294–301.
18.
Wirtz, R. A., and Dague, R. R. ( 1996). “Enhancement of granulation and start-up in the anaerobic sequencing batch reactor.” Water Envir. Res., 68(5), 883–892.
Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 127 • Issue 4 • April 2001
Pages: 302 - 310
History
Received: Jun 6, 2000
Published online: Apr 1, 2001
Published in print: Apr 2001
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.