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

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