数字孪生增强的领域自适应航天器多余物检测

由于标注数据的短缺，对航天器多余物进行在线检测受到了较大的限制。文章研究了多余物的物理特性，在航天器的数字孪生系统中构建相应的多余物模型，提出了一种结合数字孪生技术增强的跨域自适应航天器多余物检测方法。该方法通过数字孪生技术获取航天器的实时数据，并借助于历史标注数据中的相似结构，以跨域自适应技术辅助实时在线推理的进行。设计了一种新型的跨域自适应模型，该模型采用共享网络结构以及门控机制，从而在复杂任务中更有效地挖掘先验知识，实现了跨域自适应技术与数字孪生技术的有机结合，以实现更高效、准确和实时的预测。此种方法可以全面地检测航天器各个部件的多余物状态。

Digital-Twin-Enhanced Domain Adaptation Method for Spacecraft Remainders Detection

Spacecraft remainders online detection is affected by insufficient marker data. In this paper, the physical characteristics of remainders generation were studied, a remainders model in spacecraft digital twin systems was established, and a cross-domain adaptive spacecraft remainders detection method with digital twin enhancement was proposed. This method was augmented by digital twins to acquire real-time spacecraft data. It then combined similar structural historical marker data and applied a cross-domain adaptive approach to assist current online reasoning. In addition, a new type of cross-domain adaptive approach model was proposed to better mine prior knowledge from complex tasks through a shared network structure and gating mechanism. The model realizes a combination of cross-domain adaptive techniques and digital twins for more efficient, accurate and real-time prediction. This method can comprehensively detect the remainders states of different components of spacecraft.