A NOVEL SIGNAL VALIDATION METHOD APPLIED TO A STOCHASTIC-PROCESS

A novel methodology is presented for the purposes of modelling the pro cess dynamics of neutron flux during induced boiling of the coolant in a nuclear reactor environment. The proposed approach is based on the utilisation of radial basis functions from the point of view of functi on approximation, regularisation, and noisy interpolation. Data-driven multiple-input/multiple-output radial basis function networks are sub jected to faulty input signals and their signal validation capabilitie s are studied. Networks based on radial basis functions employ trainin g procedures that are substantially faster than the methods used in tr aining multi-layer perception networks. Auto-associative schemes of th e proposed technique are shown capable of identifying faulty process s ignal measurements and provide the operator with an estimate of the ac tual process value. The data utilised for the purposes of this project are obtained from an experimental facility constructed to simulate bo iling phenomena and positioned next to tie core of the IRI research re actor. (C) 1997 Published by Elsevier Science Ltd.