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Regularization of Feedwater Flow Rate Evaluation for Venturi Meter Fouling Problem in Nuclear Power Plants

Abstract Inferential sensing is a method that can be used to evaluate parameters of a physical system based on a set of measurements related to these parameters. The most common method of inferential sensing uses mathematical models to infer a parameter value from correlated sensor values. However, since inferential sensing is an inverse problem, it can produce inconsistent results due to minor perturbations in the data. This research shows that regularization can be used in inferential sensing to produce consistent results. Data from Florida Power Corporation’s Crystal River nuclear power plant (NPP) are used to give an important example of monitoring NPP feedwater flow rate.