Keywords: temperature sensors, temperature monitoring, ANNs, artificial neural networks, GMDH, group method, data handling, research reactors, nuclear reactors, nuclear energy, nuclear power, reactor modelling
Group method of data handling and neural networks applied in temperature sensors monitoring
In this work a monitoring system is developed based on the Group Method of Data Handling (GMDH) and Artificial Neural Networks (ANNs) methodologies. GMDH creates non-linear algebraic models for system characterisation and ANN is a massively parallel distributed processor made up of simple processing units called neurons. The monitoring system was applied to the IEA-R1 research reactor at Instituto de Pesquisas Energeticas e Nucleares (IPEN) by using a database obtained from a theoretical model of the reactor. The IEA-R1 research reactor is a pool-type reactor of 5 MW cooled and moderated by light water, and uses graphite and beryllium as reflector. The two methodologies (GMDH and ANN) were combined to develop a temperature monitoring system. The results were compared with previous works where GMDH and ANN were used separately and the results obtained showed an improved monitoring system.