OMFP : an approach for online mass flow prediction in CFB boilers

I. Zliobaite, J. Bakker, M. Pechenizkiy

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) boilers. If control systems fail to compensate the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. Accurate estimates of fuel consumption among other factors are needed for control systems operation. In this paper we address a problem of online mass flow prediction. Particularly, we consider the problems of (1) constructing the ground truth, (2) handling noise and abrupt concept drift, and (3) learning an accurate predictor. Last but not least we emphasize the importance of having the domain knowledge concerning the considered case. We demonstrate the performance of OMPF using real data sets collected from the experimental CFB boiler.
Original languageEnglish
Title of host publicationDiscovery Science (12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009. Proceedings)
EditorsJ. Gama, V. Santos Costa, A.M. Jorge, P.B. Brazdil
Place of PublicationBerlin
PublisherSpringer
Pages272-286
ISBN (Print)978-3-642-04746-6
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Computer Science
Volume5808
ISSN (Print)0302-9743

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