Application of Adaptive Learning Network technique to detection of sodium boiling noise in fast reactors

Abstract

Results from studies on the application of the Adaptive Learning Network (ALN) technique for detecting sodium boiling noise are presented. The technique is tested on data from in-pile boiling experiments and from out-of-pile boiling experiments. A new approach to ALN technique where knowledge of the background noise is adequate for training the Network is suggested and tested. The new approach is suitable for developing on-line sodium boiling noise detection systems in fast reactors.