Online Fault Detection and Diagnosis of In-Core Neutron Detectors Using Generalized Likelihood Ratio Method

Vanadium self-powered neutron detectors (VSPNDs) have been proposed to be used in the Advanced Heavy Water Reactor for flux mapping purposes. However, response of VSPNDs to neutron flux variations is slow, and they might also develop faults. This paper proposes a hybrid scheme for state estimation based on the Kalman filtering approach and fault detection, diagnosis, and correction based on the generalized likelihood ratio (GLR) method for VSPNDs. The Kalman filter estimates prompt neutron flux variations from the delayed signal of VSPND, while the GLR method analyzes the innovations to detect fault in VSPND. Subsequently, the scheme also corrects for the step changes in the measurement emanating from fault in VSPND. Performance of the proposed hybrid scheme has been evaluated from simulation of neutron flux variations occurring due to simultaneous movement of regulating rods and demand power variations. It is shown that the magnitude and time of occurrence of step change in signal due to the fault are effectively estimated, and thus the step change can be corrected online.

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