Abstract
A methodology for the study of the relationship between different reactor signals is presented. The application of the methodology leads to identify dominant frequencies and the contribution from other different signals to the dominant frequencies. The methodology firstly uses a linear model to estimate the response characteristics of the system and the spectra of the noise source. The estimate of the process linear predictor is obtained by the ordinary least squares method. Then, the model performs a multivariate autoregressive analysis, and a relative power contribution index is computed to determine the inter-relationship between the different reactor noise signals. The power contribution index is an indication of how the fluctuation of one variable depends on other variables, at each frequency. In this work we analyze reactor signals acquired during two operational events occurred at Laguna Verde Nuclear Power Plant (LVNPP), the only NPP of MEXICO. These events are: an event where a 12% amplitude power peak occurred and other event where power oscillations occurred in 1995. For the first event, signals from the average power range monitor, driven recirculation flows, position of recirculation flow control valves, and position and recirculation flow controllers, were used for the analysis. For the second transient, signals from the average power range monitor, total flow through the core, pressure drop in the core, jet pump flow and driven recirculation flow driven in both loops are analyzed. The results of the application of the methodology showed the relation between the variables during the transient events. Specifically, for the first transient, a frequency peak of 1.7 Hz was detected on the power spectrum from an APRM signal. In this case the major contribution to this frequency came from the driven recirculation flow at loop B. In the second event, the prominent power oscillation frequency (0.54 Hz) was tracked within the data from different signals. The major contribution to this 0.54 Hz peak came from both jet pump arrays (A and B) flow signals. Each array has 10 jet pumps.
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