Smart Soft-Sensing for the Feedwater Flowrate at PWRs Using a GMDH Algorithm

Abstract

The thermal reactor power in pressurized water reactors (PWRs) is typically assessed using secondary system calorimetric calculations based on accurate measurements of the feedwater flowrate. Therefore, precise measurements of the feedwater flowrate are essential. In most PWRs, Venturi meters are used to measure the feedwater flowrate. However, the fouling phenomena of the Venturi meter deteriorate the accuracy of the existing hardware sensors. Consequently, it is essential to resolve the inaccurate measurements of the feedwater flowrate. In this study, in order to estimate the feedwater flowrate online with high precision, a smart soft sensing model for monitoring the feedwater flowrate was developed using a group method of data handling (GMDH) algorithm combined with a sequential probability ratio test (SPRT). The uncertainty of the GMDH model was also analyzed. The proposed sensing and monitoring algorithm was verified using the acquired real plant data from Yonggwang Nuclear Power Plant Unit 3.