Abstract
The generalized likelihood ratio (GLR) technique performs statistical tests on the innovations sequence of a Kalman filter state estimator. Using the results of these tests, failures in the sensors of a pressurized water reactor pressurizer are detected and identified. A third-order, linear model of the pressurizer dynamics, which is required by both the GLR and Kalman filter formulations, is developed from first principles. Using actual pressurizer data, the GLR method is employed to identify a bias in one of three level sensors.
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