Online mass flow prediction in CFB boilers

Andriy Ivannikov, Mykola Pechenizkiy, Jorn Bakker, Timo Leino, Mikko Jegoroff, Tommi Kärkkäinen, Sami Äyrämö

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

    4 Citations (Scopus)


    Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate for the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. This phenomenon causes a reduction of efficiency and lifetime of process components. Therefore, domain experts are interested in developing tools and techniques for getting better understanding of underlying processes and their mutual dependencies in CFB boilers. In this paper we consider an application of data mining technology to the analysis of time series data from a pilot CFB reactor. Namely, we present a rather simple and intuitive approach for online mass flow prediction in CFB boilers. This approach is based on learning and switching regression models. Additionally, noise canceling, and windowing mechanisms are used for improving the robustness of online prediction. We validate our approach with a set of simulation experiments with real data collected from the pilot CFB boiler.
    Original languageEnglish
    Title of host publicationAdvances in Data Mining. Applications and Theoretical Aspects
    Subtitle of host publication9th Industrial Conference, ICDM 2009 proceedings
    EditorsPetra Perner
    Place of PublicationBerlin - Heidelberg
    ISBN (Electronic) 9783642030666
    Publication statusPublished - 2009
    MoE publication typeA4 Article in a conference publication
    EventAdvances in data mining : applications and theoretical aspects : 9th Industrial Conference, ICDM 2009 - Leipzig, Germany
    Duration: 20 Jul 200922 Jul 2009

    Publication series

    SeriesLecture Notes in Computer Science


    ConferenceAdvances in data mining : applications and theoretical aspects
    Abbreviated titleICDM 2009


    Dive into the research topics of 'Online mass flow prediction in CFB boilers'. Together they form a unique fingerprint.

    Cite this