Identification of Multivariate Models for Noise Analysis of Nuclear Plant

摘要

During the normal operation of a pressurized water reactor, neutron noise analysis with multivariate autoregressive procedures in a valuable diagnostic tool to extract dynamic characteristics for incipient failure detection. The first part of the paper will describe in details the equations for estimating the multivariate autoregressive model matrices and the structure of various matrices. The matrices are estimated by solving a set of matrix operations, called Yule-Walker equations. The selection of optimal model order will also be discussed. Once the optimal parameter set is obtained, simple and fast calculations are used to determine the auto power spectral density, cross spectra, coherence function, phase. In addition the spectra may be decomposed into components being contributed from different noise sources. An application using neutron flux data collected on a nuclear plant will illustrate the efficiency of the method. (Atomindex citation 11:532056)