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Real-Time Mass Flow Estimation in Circulating Fluidized Bed

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7377)

Abstract

The mass flow parameter identification is important for modeling and control purposes in Circulating Fluidized Bed technology. In this article we propose a novel method for estimating the mass flow in the Circulating Fluidized Bed and consider aspects of its application. The method is based on combining information obtained from both mass of fuel silo and velocity of fuel screw signals. The information from mass of fuel silo measurements is extracted by following the lower edge of the signal.

Keywords

  • CFB
  • control
  • estimation
  • mass flow
  • system identification

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References

  1. Bakker, J., Pechenizkiy, M., Žliobaite, I., Ivannikov, A., Kärkkäinen, T.: Handling outliers and concept drift in online mass flow prediction in CFB boilers. In: Proceedings KDD Workshop on Knowledge Discovery from Sensor Data, pp. 13–22 (2009)

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  2. Ivannikov, A., Pechenizkiy, M., Bakker, J., Leino, T., Jegoroff, M., Kärkkäinen, T., Äyrämö, S.: Online Mass Flow Prediction in CFB Boilers. In: Perner, P. (ed.) ICDM 2009. LNCS, vol. 5633, pp. 206–219. Springer, Heidelberg (2009)

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  3. Pechenizkiy, M., Bakker, J., Žliobaite, I., Ivannikov, A., Kärkkäinen, T.: Online Mass Flow Prediction in CFB Boilers with Explicit Detection of Sudden Concept Drift. SIGKDD Exploration 11(2), 109–116 (2009)

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  4. Soderstrom, T., Stoica, P.: System identification. Prentice-Hall, Englewood Cliffs (1989)

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© 2012 Springer-Verlag Berlin Heidelberg

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Ivannikov, A., Jegoroff, M., Kärkkäinen, T. (2012). Real-Time Mass Flow Estimation in Circulating Fluidized Bed. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2012. Lecture Notes in Computer Science(), vol 7377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31488-9_9

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  • DOI: https://doi.org/10.1007/978-3-642-31488-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31487-2

  • Online ISBN: 978-3-642-31488-9

  • eBook Packages: Computer ScienceComputer Science (R0)