Application of pattern recognition technique on randon signals for automatic monitoring of dynamic systems with emphasis on nuclear reactors

The time varying or noise component of dynamic system parameters contains information on the system state. Pattern recognition analysis of noise signals for such systems is a powerful technique for assessing 'system normality' or 'correct operation'. Data analysis with modern small computers enables the otherwise unmanageable volumes of data to be processed on line and the results presented in a meaningful form. These informations provide necessary data for maintaining the system at optimum operating conditions. An automatic pattern recognition program, PSDREC, developmed for the surveillance of nuclear reactor and rotating machinery is described, and the relevant theory is outlined. This program, which applies 8 statistical tests to calculated power spectral density (PSD) distributions, was earlier installed in a PDP-11/45 computer at IPEN. In this work it has been used to separately analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel motor (vibration signals). The latter two were, respectively, operated over a wide-range of flow and load conditions. The statistical tests were applied to frequency bands of (0,1-40) Hz, (0-1000) Hz and (0,20000) Hz. for the BWR, pump and diesel signal data, respectively. Operation and analysis conditions are given together with representative graphs of the analysed PSD distributions. Results of the tests - discussed in some detail - are considered to be satisfactory. (Author)