Authors: Roozbeh Razavi-Far, Hadi Davilu, Caro Lucas
Addresses: Department of Nuclear Engineering, Amirkabir University of Technology, P.O. Box 15875-4413 Tehran, Iran. ' Department of Nuclear Engineering, Amirkabir University of Technology, P.O. Box 15875-4413 Tehran, Iran. ' Center of Excellence on Control and Intelligent Processing, Department of Electrical and Computer Engineering, University of Tehran, P.O. Box 14395-1515 Tehran, Iran
Abstract: Proper and timely fault diagnosis is of premier importance to guarantee the safe and reliable operation of Nuclear Power Plants (NPPs). If faults occur in NPPs, it is very difficult for a human operator to perform routine tasks, such as distinguishing normal from abnormal conditions and predicting future states, etc. In this paper, a fuzzy inference system is adopted for the diagnosis of abrupt faults in a nonlinear model of a typical Pressurised Water Reactor (PWR). The fuzzy system is tested with different shapes of Membership Functions (MFs). The if-then rules, representing the underlying processes, are inferred from the available fault-symptom relations. The symptoms are generated using plant model measurements.
Keywords: fault diagnosis; fault symptom tree; fuzzy inference systems; nuclear power plants; NPP; fuzzy logic; nuclear energy; nuclear safety; reliability; nonlinear modelling; pressurised water reactor; PWR.
International Journal of Nuclear Knowledge Management, 2009 Vol.3 No.3, pp.296 - 311
Published online: 13 Jul 2009 *Full-text access for editors Access for subscribers Free access Comment on this article