摘要： 针对微小卫星强实时性和资源受限的特点，提出一种基于故障树的专家系统推理机。根据广度优先搜索设计正向推理算法，根据深度优先搜索设计逆向推理算法，2种算法在时间和空间上均满足线性复杂度。实验结果表明，该推理机可满足微小卫星对实时性的要求，同时也能节省星上资源。

关键词: 推理机, 专家系统, 故障树, 故障诊断, 图算法, 微小卫星

Abstract: According to the rigorous requirements for real-time performance and conditional resource of the micro-satellite, inference engine of expert system is designed based on fault tree. It designs forward direction inference algorithm based on breadth-first search, and reverse direction inference algorithm based on depth-first search search. Time complexity and space complexity of two algorithms are both linear. Experimental result shows that the engine can not only improve the efficiency of inference engine, but also save the resource of the micro-satellite.

Key words: inference engine, expert system, fault tree, fault diagnosis, graph algorithms, micro-satellite

中图分类号: 

• TN912