Fuzzy logic

In this paper a methodology is presented that integrates pretrained artificial neural networks (ANNs) with rule-based fuzzy logic systems, for the purpose of distinguishing different transients in a Nuclear power Plant (NPP). In general this approach appears to provide timely, concise and task specific information about the status of a system under consideration. The pretrained neural network typifies different transient scenarios and derives membership functions which independently represent individual transient scenarios and derives membership functions which independently represent individual transients. The overall system successfully performs transient identification, in a time span gaster or at least comparable to that of transient development. In order to examine the proposed methodology simulated accidents are used. The results obtained demonstrate the excellent noise tolerance of ANNs and suggest a new approach for transient identification