Semi-qualitative Encoding of Manifestations at Faults in Conductive Flow Systems (original) (raw)

Abstract

A complex system in industry is often a conductive flow system. Its abnormal behaviour is difficult to manage due to incomplete and imprecise knowledge on it, also due to propagated effects that appear at faults. Human experts use knowledge from practice to represent abnormal ranges as interval values but they have poor knowledge on variables with no direct link to target system’s goals. The paper proposes a new fuzzy arithmetic, suited to calculate abnormal ranges at test points located far deep in the conductive flow structure of the target system. It uses a semiqualitative encoding of manifestations at faults, and exploits the negative correlation of the power variables (pressure like and flow-rate like) in faulty cases. The method is compared to other approaches and it is tested on a practical case.

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Authors and Affiliations

  1. “Danubius” University from Galati, Lunca Siretului no.3, 800416, Galati, Romania
    Viorel Ariton

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK
    Bogdan Gabrys
  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK
    Robert J. Howlett
  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia
    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Ariton, V. (2006). Semi-qualitative Encoding of Manifestations at Faults in Conductive Flow Systems. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004\_74

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