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Bayesian Networks in Decision Support

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Power Plant Surveillance and Diagnostics

Part of the book series: Power Systems ((POWSYS))

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Abstract

Since the beginning of industrialism, the complexity of industrial processes has been continuously increasing. In modem plants during normal operation this complexity is handled by the computerised control system. However, some process conditions outside the design of the control system still have to be managed by the human operator. These conditions can be due to equipment malfunction, unknown inputs and disturbances. Due to the complexity and the limited direct process interaction that operators experience, they often have difficulties making the right decisions in these abnormal situations.

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Industrial Ecology and Process Safety, Royal Institute of Technology, SE-100 44, Stockholm, Sweden

    Tomas O. Carlsson & Ronald Wennersten

Authors
  1. Tomas O. Carlsson
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  2. Ronald Wennersten
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Editor information

Editors and Affiliations

  1. Belgian Nuclear Research Centre (SCK·CEN), Boeretang 200, B- 2400, Mol, Belgium

    Da Ruan

  2. Institute for Energy (IFE), P.O. Box 173, N-1751, Halden, Norway

    Paolo F. Fantoni

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© 2002 Springer-Verlag Berlin Heidelberg

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Carlsson, T.O., Wennersten, R. (2002). Bayesian Networks in Decision Support. In: Ruan, D., Fantoni, P.F. (eds) Power Plant Surveillance and Diagnostics. Power Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04945-7_6

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  • DOI: https://doi.org/10.1007/978-3-662-04945-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-07754-8

  • Online ISBN: 978-3-662-04945-7

  • eBook Packages: Springer Book Archive

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