Automated state identification systems facilitate reactor monitoring and control of nuclear systems by consolidating information collected by deployed sensors. In the current paper, we present the use of relevance vector machines (RVM) for real-time state identification of boiling water reactors (BWR). In particular, RVM models utilize the incoming signals of interest and identify in real time the state of the BWR either as normal or as one of the transition states. Each of the RVM models is assigned to a single signal; it receives the measured value at each instance and outputs the identified BWR state. The state that has been designated by the majority of the signals is displayed to the human operator as the identified BWR state. The proposed methodology is applied and tested on a set of signals taken from the FIX-II experimental facility that is a scaled representation of a BWR. Copyright © 2016 by ASME.

Real-time state identification of boiling water reactors using relevance vector machines

Cappelli, M.
2016

Abstract

Automated state identification systems facilitate reactor monitoring and control of nuclear systems by consolidating information collected by deployed sensors. In the current paper, we present the use of relevance vector machines (RVM) for real-time state identification of boiling water reactors (BWR). In particular, RVM models utilize the incoming signals of interest and identify in real time the state of the BWR either as normal or as one of the transition states. Each of the RVM models is assigned to a single signal; it receives the measured value at each instance and outputs the identified BWR state. The state that has been designated by the majority of the signals is displayed to the human operator as the identified BWR state. The proposed methodology is applied and tested on a set of signals taken from the FIX-II experimental facility that is a scaled representation of a BWR. Copyright © 2016 by ASME.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/5882
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