Skip to main content

Abstract

Nuclear power plant operation and monitoring in general is a complex task which requires a large number of sensors, alarms and displays. At any instant in time, the operator is required to make a judgment about the state of the plant and to react accordingly. During abnormal situations, operators are further burdened with time constraints. The possibility of an undetected faulty instrumentation line, adds to the complexity of operators’reasoning tasks. Failure of human operators to cope with the conceptual complexity of abnormal situations often leads to more serious malfunctions and further damages to plant (TMI-2 as an example). During these abnormalities, operators rely on the information provided by the plant sensors and associated alarms. Their usefulness however, is quickly diminished by their large number and the extremely difficult task of interpreting and comprehending the information provided by them. The need for an aid to assist the operator in interpreting the available data and diagnosis of problems is obvious.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. T. Bylander, S. Mittal, B. Chandrasekaran, “CSRL: A Language for Expert Systems for Diagnosis”, Proc. of IJCAI 83, Los Altos, CA, PP 218–21.

    Google Scholar 

  2. B. Chandrasekaran, “Decomposition of Domain Expert Knowledge into Knowledge Sources: the MDX Approach”, Proc 4th National CSCSI/SCEIO, Sakatoon, Canada, May, 1982.

    Google Scholar 

  3. B.K. Hajek, S. Hashemi, D.D. Sharma, B. Chandrasekaran, D.W. Miller, Artificial Intelligence Enhancement to Safety Parameter Display Systems”, Proc. 6th Power Plant Dynamics, Control and Testing Symposium, Knoxville, Tenn, April, 1986.

    Google Scholar 

  4. B. Chandrasekaran, “Towards Taxonomy of Problem Solving Types”, AI Magazine, Vol 4, No. 1, Winter/Spring 1983.

    Google Scholar 

  5. J.J. Deyst, R.M. Kanazawa, J.P. Pasquenza, “Sensor Validation: A Method to Enhance the Quality of Man/Machine Interface in Nuclear Power Stations”, IEEE Transactions on NS, Vol NS-28, No. 1, Feb. 1981.

    Google Scholar 

  6. B. Chandrasekaran, W.F. Punch, “Data Validation During Diagnosis, a Step Beyond Traditional Sensor Validation”, Proc. AAAI, Seattle, WA, 1987.

    Google Scholar 

  7. B. Chandrasekaran, W.F. Punch, “Hierarchical Classification: Its Usefulness for Diagnosis and Sensor Validation”, Proc 2nd AIAA/NASA/USAF Symposium on Automation, Robotics, and Advanced Computing, Feb 1987.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1988 Plenum Press, New York

About this chapter

Cite this chapter

Hashemi, S., Hajek, B.K., Miller, D.W. (1988). An Expert System for Sensor Data Validation and Malfunction Detection. In: Majumdar, M.C., Majumdar, D., Sackett, J.I. (eds) Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1009-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-1009-9_19

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8290-7

  • Online ISBN: 978-1-4613-1009-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics