摘要
探讨了G2的知识表示、知识库管理及实时推理。针对飞船推进系统的工程实际问题,分析了推进舱推进子系统的故障特点,采用神经 模糊系统理论对推进舱推进子系统故障模式的知识表示进行研究,提出了推进舱推进子系统故障的知识表示形式。运用G2软件平台设计了飞船推进系统的故障诊断推理机。该推理机可以实时地诊断出相应的故障模式,记录相关的故障信息,还可以对故障进行预报,以避免故障的发生。
The knowledge representation, knowledge base management and real-time inference mechanism on G2 are studied. For the engineering practical problem of spacecraft propulsive system the diagnosis characteristics of propulsive subsystem in spacecraft propulsive cabin using neuro-fuzzy system theory ane analysed. After the study of knowledge representation of its fault mode its knowledge representation form is provided. The fault diagnosis mechanism of spacecraft propulsive system using G2 is designed, which can diagnose the correspondence fault mode in the real-time, record correlative fault information, and predict faults also in order to avoid their occurrence.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2004年第1期122-124,136,共4页
Systems Engineering and Electronics
基金
国家"863"高技术计划资助课题
关键词
故障诊断
神经网络
人工智能
飞船
fault diagnosis
neural network
artificial intelligence
spacecraft
