Adaptive physics-encoded graph neural network for health stage assessment of liquid-propellant rocket engines
Meng Ma,
Zhizhen Wang,
Tianfu Li
et al.
Abstract:The improvement of reliable health monitoring system (HMS) for liquid-propellant rocket engines (LREs) is a crucial part for reusable launch vehicle, which contributes to providing competitive and cost-effective propulsion systems. Thus, it accentuates the need for reliable and quick health stage assessment of system and follow-up damage-mitigating control. In this paper, we propose a novel adaptive physics-encoded graph neural network (APGNN) for health stage assessment of LREs. Our approach embeds the relati… Show more
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