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[해외논문] Deep neural network approach for fault detection and diagnosis during startup transient of liquid-propellant rocket engine

Acta astronautica, v.177, 2020년, pp.714 - 730  

Park, Soon-Young (Korea Advanced Institute of Science and Technology (KAIST)) ,  Ahn, Jaemyung (Korea Advanced Institute of Science and Technology (KAIST))

Abstract AI-Helper 아이콘AI-Helper

Abstract We propose a fault detection and diagnosis (FDD) method for liquid-propellant rocket engine tests during startup transient based on deep learning. A numerical model describing the startup transient for the hot-firing test of the rocket engine allows to simulate normal and abnormal situatio...

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