Title :
QES-Shell: An Expert System for Nuclear Power Plant Operator´s Training
Author :
Qudrat-Ullah, Hassan
Author_Institution :
Sch. of Administrative Studies, York Univ., Toronto, ON, Canada
Abstract :
Decision making in complex systems such as nuclear power plants is a difficult task at best. The nuclear power plant operators are susceptible to various operational mistakes causing the high risk accidents and safety issues. Therefore, the role of expert systems in the offline training program for the operators is ever increasing. In this paper, we describe the development of an Expert System Shell, "QES_SHELL", to assist, off-line, QNPP operators and plant personnel in a better familiarization to infer the anticipated and foreseen malfunctions from the observed symptoms. The "QES_SHELL" has been implemented in the Turbo Prolog language. Its inferencing mechanism is of the "Rule-based" type and it adopts the "Depth First" technique to search the knowledge base. The performance of the QES_SHELL on "LOCA Diagnostics" at QNPP has been found satisfactory through Turing test.
Keywords :
PROLOG; Turing machines; decision making; expert systems; inference mechanisms; nuclear engineering computing; nuclear power stations; personnel; risk analysis; safety; training; tree searching; LOCA diagnostics; QES-Shell; QNPP operators; Turbo Prolog language; Turing test; complex systems; decision making; depth first search technique; expert system; inferencing mechanism; knowledge base; nuclear power plant; offline training program; operators training; plant personnel; risk accidents; rule-based system; safety; Accidents; Engines; Expert systems; Monitoring; Power generation; Training; LOCA; Nuclear power plants; expert system; fault diagnosis; operators; training;
Conference_Titel :
Intelligent Systems, Modelling and Simulation (ISMS), 2012 Third International Conference on
Conference_Location :
Kota Kinabalu
Print_ISBN :
978-1-4673-0886-1
DOI :
10.1109/ISMS.2012.26