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Sensor Drift Estimation for Reactor Systems by Fusing Multiple Sensor Measurements...

by Nageswara S Rao, Christopher R Greulich, Pradeep Ramuhalli, Mustafa S Cetiner, Pravallika Devineni
Publication Type
Conference Paper
Journal Name
IEEE Nuclear Science Symposium and Medical Imaging Conference
Book Title
2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Publication Date
Page Numbers
1 to 2
Conference Name
IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC 2019)
Conference Location
Manchester, United Kingdom
Conference Sponsor
IEEE
Conference Date
-

A nuclear power plant is instrumented with a variety of sensors that monitor its variables to estimate the state and initiate safety actions, if needed. We address the problem of estimating drifts or errors in sensor measurements due to factors such as calibration changes. We propose an information fusion method that uses measurements from other sensors to generate an estimate of a sensor measurement, and its difference from an actual measurement provides an error estimate. We present two fusers based on the ensemble of trees and support vector machine that are trained using sensor measurements collected at an emulated test loop of a pressurized water reactor under no-drift conditions. We present error estimates for a differential pressure sensor of the heat exchanger of the primary coolant system, under twenty controlled scenarios using the test loop. Both positive and negative errors are captured by both methods in scenarios involving calibration drifts, blocking, air gap and electromagnetic interference. The root mean square errors of estimated drifts are typically within 2% percent of the maximum.