Abstract:This paper examines the development of a data-driven anomaly detection methodology for servo-actuated hydraulic valves installed in a gas turbine fuel delivery system. Degraded operation of these valves is a leading cause of unavailability for gas turbine driven power plants. Nearlyeighty potential features were generated from the limited raw sensors and control system signals through a combination of domain expertise, statistical feature extraction, and insight gains from prior physics-based simulations. Impo… Show more
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