Title: Group method of data handling and neural networks applied in temperature sensors monitoring

Authors: Elaine Inacio Bueno, Iraci Martinez Pereira, Antonio Teixeira Silva

Addresses: Instituto Federal de Educacao, Ciencia e Tecnologia – Campus Braganca Paulista (IFSP – Campus BRA), Av. Francisco Samuel Lucchesi Filho, 770 12920-600 Braganca Paulista, SP, Brazil; Instituto de Pesquisas Energeticas Nucleares (IPEN-CNEN), Av. Professor Lineu Prestes, 2242, 05508-000 Sao Paulo, SP, Brazil. ' Instituto de Pesquisas Energeticas Nucleares (IPEN-CNEN), Av. Professor Lineu Prestes, 2242, 05508-000 Sao Paulo, SP, Brazil. ' Instituto de Pesquisas Energeticas Nucleares (IPEN-CNEN), Av. Professor Lineu Prestes, 2242, 05508-000 Sao Paulo, SP, Brazil

Abstract: 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.

Keywords: temperature sensors; temperature monitoring; ANNs; artificial neural networks; GMDH; group method; data handling; research reactors; nuclear reactors; nuclear energy; nuclear power; reactor modelling.

DOI: 10.1504/IJNKM.2011.042003

International Journal of Nuclear Knowledge Management, 2011 Vol.5 No.3, pp.260 - 271

Published online: 18 Feb 2015 *

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