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

机译:广义似然比法在线核中子探测器的在线故障检测与诊断

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摘要

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.
机译:钒自供电中子探测器(VSPND)已被提议用于先进重水反应堆中以进行通量映射。但是,VSPND对中子通量变化的响应很慢,并且它们也可能会产生故障。本文提出了一种基于卡尔曼滤波方法的状态估计与基于VSPND的广义似然比(GLR)方法进行故障检测,诊断和纠正的混合方案。卡尔曼滤波器根据VSPND的延迟信号估计中子通量的迅速变化,而GLR方法分析了检测VSPND中故障的创新。随后,该方案还纠正了由于VSPND中的故障而引起的测量中的阶跃变化。通过模拟由于调节杆同时运动和需求功率变化而发生的中子通量变化,对提出的混合方案的性能进行了评估。结果表明,可以有效地估计由于故障引起的信号阶跃变化的大小和发生时间,从而可以在线校正阶跃变化。

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