GMDH and Artificial Neural Network Applied in an Experimental Reactor Sensors Monitoring

Abstract

In this work a Monitoring System was developed using GMDH (Group Method of Data Handling) algorithm and Artificial Neural Networks (ANN) which was applied in the IEA-R1 research reactor at IPEN. GMDH is used in two different ways to perform an input data preprocessing to the ANN. The system perform the monitoring by comparing the estimative calculated values with the measured ones. Each Monitoring System was developed and tested for five different sets of input data, ancluding data from a Reactor Teoretical Model and for four different sets of reactor variables. The results for the most of cases show an improvement when GMDH is combined with ANN algorithm in the Monitoring Systems. The good results obtained in the present work show the viability of using GMDH algorithm in the study of the best input variables to the ANN, thus making possible the use of these methods in the implementation of a new Monitoring Methodology applied in sensors of a nuclear power plant.