Experience with data mining for the anaerobic wastewater treatment process |
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| Affiliation: | 1. Department of Computing, Communications Technology and Mathematics, London Metropolitan University, 31 Jewry Street, London EC3N 2EY, UK;2. Business and Information Technology Department, CCLRC Rutherford Appleton Laboratory, Chilton, Didcot, Oxon. OX11 0QX, UK;1. GFZ German Research Centre for Geosciences, Section 4.5 Geomicrobiology, 14473 Potsdam, Germany;2. LabMET, Ghent University, Coupure Links 653, B-9000 Gent, Belgium;1. Department of Agricultural and Biological Engineering, University of Illinois, Urbana-Champaign, 1304 W Pennsylvania Ave, Urbana, IL 61801, USA;2. Department of Crop Sciences, University of Illinois, Urbana-Champaign, N-423 Turner Hall 1102 S. Goodwin, Urbana 61801, USA;3. Tempus Health, Inc., 600 W Chicago St, Floor 7 Light Bank Office, Chicago, IL 60654, USA;4. SunPower Corporation, 1504 Eureka Rd Suite 130, Roseville, CA 95661, USA;1. Chemical and Environmental Engineering, School of Engineering, RMIT University, 3001, Melbourne, Australia;2. Department of Chemical & Material Engineering, The University of Auckland, Auckland, New Zealand;3. SCION, 49 Sala Street, Rotorua, 3010, New Zealand;1. DBFZ Deutsches Biomasseforschungszentrum gemeinnützige GmbH, Biochemical Conversion Department, Torgauer Straße 116, 04347 Leipzig, Germany;2. Helmholtz-Centre for Environmental Research GmbH—UFZ, Department of Environmental Microbiology, Permoserstraße 15, 04318 Leipzig, Germany;3. Technische Universität Dresden, Physical Chemistry, Measurement and Sensor Technology, 01062 Dresden, Germany;4. Kurt-Schwabe-Institut für Mess- und Sensortechnik e.V. Meinsberg, Kurt-Schwabe-Str. 4, 04736 Waldheim, Germany |
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| Abstract: | Anaerobic digestion provides an effective way of disposing organic material in wastewater. The EU-funded TELEMAC project aims at improving the reliability and efficiency of monitoring and control of this type of wastewater treatment plant. One of its special features is the idea of a telecontrol centre which monitors multiple, geographically distributed plants remotely, acts as a centre of expertise, and brings together the expertise of a network of remote experts. Data mining has been identified as a potentially useful contributing technology. Sensor data is now becoming available for some pilot, laboratory scale, and industrial sized digesters.This paper presents the directions of work and emerging results of data mining. Particular themes considered here include:- ?experience gained in the data mining exercise;
- ?the use of confidence and prediction intervals;
- ?prospects for generalisation over different sizes and types of anaerobic digester;
- ?relationship to the overall supervision system developed in the project.
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