An Industrial Information Integration Approach to In-Orbit Spacecraft
Enterprise Information Systems
Taylor & Francis
To operate an in-orbit spacecraft, the spacecraft status has to be monitored autonomously by collecting and analysing real-time data, and then detecting abnormities and malfunctions of system components. To develop an information system for spacecraft state detection, we investigate the feasibility of using ontology-based artificial intelligence in the system development. We propose a new modelling technique based on the semantic web, agent, scenarios and ontologies model. In modelling, the subjects of astronautics fields are classified, corresponding agents and scenarios are defined, and they are connected by the semantic web to analyse data and detect failures. We introduce the modelling methodologies and the resulted framework of the status detection information system in this paper. We discuss system components as well as their interactions in details. The system has been prototyped and tested to illustrate its feasibility and effectiveness. The proposed modelling technique is generic which can be extended and applied to the system development of other large-scale and complex information systems.
Space industry, deep space exploration, industrial information integration engineering, IIIE, SASO model
Xiaoning Du, Hong Wang, Yuhao Du, Li Da Xu, Sohail Chaudhry, Zhuming M. Bi, Rong Guo, Yongxuan Huang, and Jisheng Li (2017).
An Industrial Information Integration Approach to In-Orbit Spacecraft. Enterprise Information Systems.11 (1), 86-104. Taylor & Francis.