An Expert System for Sensor Data Validation and Malfunction Detection

  • Siavash Hashemi
  • Brian K. Hajek
  • Don W. Miller


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.


Expert System Diagnostic Conclusion Knowledge Group Confidence Factor Abnormal Situation 
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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Copyright information

© Plenum Press, New York 1988

Authors and Affiliations

  • Siavash Hashemi
    • 1
  • Brian K. Hajek
    • 1
  • Don W. Miller
    • 1
  1. 1.Nuclear Engineering ProgramThe Ohio State UniversityColumbusUSA

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