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Abstract

Proposed is an apparatus for updating a digital twin-based model and method therefor, wherein the method includes collecting a sensor data representing a measured physical quantity of a component of a gas turbine apparatus and measured through a sensor when the gas turbine apparatus operates, deriving a state data representing whether a state of the component is a normal state or an abnormal state by analyzing the sensor data through an reduced order model generated using first training data derived through numerical analysis, deriving a state vector representing the state of the component as a probability by performing inference on the sensor data through a verification model generated from second training data, and controlling the gas turbine apparatus based on a comparison between the state data and the state vector.

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