Fault Detection Method of Low-Orbit Satellite Internet Based on Deep Uncertainty Estimation Network

Autor: Wenyu SUN, Weijia ZHANG, Limin WANG
Jazyk: čínština
Rok vydání: 2022
Předmět:
Zdroj: 天地一体化信息网络, Vol 3, Pp 89-97 (2022)
Druh dokumentu: article
ISSN: 2096-8930
DOI: 10.11959/j.issn.2096-8930.2022025
Popis: Low-orbit satellite internet technology is a highly innovative direction of development with few existing cases.Low-orbit satellite internet systems are characterised by a large number of constituent satellites, frequent topology changes, and complex payload types.The fault categories of such complex systems are diffi cult to be completely mastered with methods such as expert systems or practical engineering experience.Moreover, traditional fault detection and diagnosis methods tailored for a single satellite and a single functionality are diffi cult to predict uncertain faults under sophisticated and transient environment conditions.For the above problems, a fault prediction model based on the deep uncertainty estimation network for low-orbit satellite internet was proposed, and was verifi ed used self-collected data from simulated joint satellite-ground tests.Experimental results showed that the proposed method could improved the detection accuracy of known types of faults and demonstrated particular eff ectiveness in predicting faults of unknown types.
Databáze: Directory of Open Access Journals