VIRTUAL SENSORS FOR ROBUST ON-LINE MONITORING (OLM) AND DIAGNOSTICS

摘要

Unscheduled shutdown of nuclear power facilities for recalibration and replacement of faulty sensors can be expensive and disruptive to grid management. In this work, we present virtual (software) sensors that can replace a faulty physical sensor for a short duration thus allowing recalibration to be safely deferred to a later time. The virtual sensor model uses a Gaussian process model to process input data from redundant and other nearby sensors. Predicted data includes uncertainty bounds including spatial association uncertainty and measurement noise and error. Using data from an instrumented cooling water flow loop testbed, the virtual sensor model has predicted correct sensor measurements and the associated error corresponding to a faulty sensor.