Model based fault diagnosis of a PWR nuclear power plant using fuzzy inference approach
Document Type
Conference Proceeding
Publication Date
12-1-2008
Publication Title
World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference
First Page
945
Last Page
950
Abstract
The proper and timely fault diagnosis is of premier importance to guarantee the safe and reliable operation of nuclear power plants (NPPs). In this paper, fuzzy inference system is adopted for the diagnosis of abrupt faults in a nonlinear model of a typical pressurized water reactor (PWR). The fuzzy system is tested with different shape 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.
ISBN
981279946X,9789812799463
Recommended Citation
Far, Roozbeh Razavi; Davilu, Hadi; and Lucas, Caro. (2008). Model based fault diagnosis of a PWR nuclear power plant using fuzzy inference approach. World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference, 945-950.
https://scholar.uwindsor.ca/electricalengpub/180