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The Industrialisation of a Multi-Agent System for Power Transformer Condition Monitoring

  • V. M. Catterson
  • S. D. J. McArthur

Abstract

Electrical utilities have a pressing need for help with asset management, particularly for large plant items such as transformers. Transformer aging, problems and faults are intimated by partial discharge activity, which can be categorised into defect types. This can be achieved by a condition monitoring system using multiple intelligent classification techniques to provide accurate diagnoses. On-line operation of this system will remove the data processing burden from personnel, allowing for concentration on alleviating the fault’s effects rather than interpreting raw data.

Keywords

Power Transformer Partial Discharge Fault Prediction Interaction Protocol Information Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    A. Ottele and R Shoureshi, “Neural Network-Based Adaptive Monitoring System for Power Transformer”, Journal of Dynamic Systems, Measurement, and Control, September 2001, Volume 123, Issue 3.Google Scholar
  2. [2]
    S. D. J. McArthur, M. D. Judd and J. R. McDonald, “Advances in Intelligent Condition Monitoring and Asset Management of Power Transformers”, Proc. Euro TechCon 2003, November 2003.Google Scholar
  3. [3]
    S. D. J. McArthur, S. M. Strachan and G. Jahn, “The Design of a Multi-Agent Transformer Condition Monitoring System”, To appear in IEEE Transactions on Power Systems.Google Scholar
  4. [4]
    S. M. Strachan, G. Jahn, S. D. J. McArthur and J. R. McDonald, “Intelligent Diagnosis of Defects Responsible for Partial Discharge Activity Detected in Power Transformers”, Intelligent System Applications in Power Systems Conf. (ISAP2003), 2003.Google Scholar
  5. [5]
    Barry H. Ward, “A Survey of New Techniques in Insulation Monitoring of Power Transformers”, IEEE Electrical Insulation Magazine, May/June 2001, Volume 17, Number 3, pp 16–23.CrossRefGoogle Scholar
  6. [6]
    G. P. Cleary and M. D. Judd, “An Investigation of Discharges in Oil Insulation using UHF PD Detection”, Proc. 14th Int. Conf. on Dielectric Liquids (ICDL 2002), July 2002.Google Scholar
  7. [7]
    E. Gulski, “Computer-Aided Recognition of Partial Discharges Using Statistical Tools”, PhD Dissertation, Delft University Press, 1991.Google Scholar
  8. [8]
    M. D. Judd, G. P. Cleary, and C. J. Bennoch, “Applying UHF Partial Discharge Detection to Power Transformers”, IEEE Power Engineering Review, August 2002.Google Scholar
  9. [9]
    Foundation for Intelligent Physical Agents (FIPA), http://fipa.org, 2003.
  10. [10]
    Foundation for Intelligent Physical Agents, “Communicative Act Library Specification”, http://fipa.org/specs/fipa00037/SC00037J.html, 2002.
  11. [11]
    Foundation for Intelligent Physical Agents, “Interaction Protocol Specifications”, http://fipa.org/repository/ips.php3, 2002.
  12. [12]
    Foundation for Intelligent Physical Agents, “FIPA SL Content Language Specification”, http://fipa.org/specs/fipa00008/SC00008I.html, 2002.
  13. [13]
    British Telecommunications plc., The Zeus Website, http://more.btexact.com/projects/agents/zeus/, 2001.
  14. [14]
    Telecom Italia Lab., http://sharon.cselt.it/projects/jade/, 2004.
  15. [15]
    Stanford Medical Informatics, The Protégé Ontology Editor and Knowledge Acquisition System, http://protege.stanford.edu/, 2004.
  16. [16]
    C. van Aart, The beangenerator Homepage, http://gaper.swi.psy.uva.nl/beangenerator/content/main.php, 2004.

Copyright information

© Springer-Verlag London Limited 2005

Authors and Affiliations

  • V. M. Catterson
    • 1
  • S. D. J. McArthur
    • 1
  1. 1.Institute for Energy and EnvironmentUniversity of StrathclydeGlasgowUK

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