Data mining to support anaerobic waste water treatment plant monitoring and control in the TELEMAC project

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Persistent URL	http://purl.org/net/epubs/work/30122
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Record Id	30122
Title	Data mining to support anaerobic waste water treatment plant monitoring and control in the TELEMAC project
Contributors	M Dixon (London Metropolitan U.), JR Gallop (CCLRC Rutherford Appleton Lab.), SC Lambert (CCLRC Rutherford Appleton Lab.), L Lardon (INRA), J-P Steyer (INRA), JV Healy (London Metropolitan U.)
Abstract	The stable and efficient operation of anaerobic WWTPs (Waste Water Treatment Plants) is a major challenge for monitoring and control systems. TELEMAC is an EU-funded project for supporting distributed anaerobic WWTPs by remotely monitoring their data and by offering expert advice. This paper describes how the accumulating filtered sensor data is being mined to contribute to the refining of expert experience for insights into digester states. Visualisation techniques are used to present cluster analyses of digester states. A procedure for determining prediction intervals is described together with its application for volatile fatty acid concentrations; this procedure enables prediction risk assessment.
Organisation	CCLRC , BITD
Keywords	Engineering , Wastewater treatment , Anaerobic digestion , Process control , Data mining
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Language	English (EN)

Type	Details	URI(s)	Local file(s)	Year
Paper In Conference Proceedings	In IFAC Workshop on Modelling and Control for Participatory Planning and Managing Water Systems, Venice, Italy, 29 Sep 2004 - 1 Oct 2004, (2004).		IFAC_poster_Dixon_etal.pdf	2004