摘要
通用航空存在布局分散、企业机队小及维修技术力量薄弱等特点,使通用航空飞机排故困难;为解决这种情况,对基于故障树和神经网络的航空活塞发动机故障诊断技术进行了研究,构建了基于故障树和神经网络结合,辅以远程专家视频会诊的航空活塞发动机故障诊断专家系统,并给出了故障知识库的构建和管理方法,三种故障诊断模型的推理机制和融合方法;利用收集的航空活塞发动机故障数据对神经网络故障诊断方法进行了验证,有效地诊断出航空活塞发动机的故障。
The character of general aviation is scattered layout,small fleet and weak maintenance technology,so it is difficult for troubleshooting of general aviation aircraft.To solve this problem,this thesis researches fault diagnosis technology based on the Neural Network and fault tree of the air piston engine,constructs fault diagnosis expert system based on fault tree and Neural Network,supplemented by a remote expert videos consultation.The construction and management method of knowledge base,reasoning and integration method of three type fault diagnosis are proposed.Utilizing the collected data of aero piston engine to demonstrate,the Neural Network fault diagnosis is effective for aero engine.
出处
《计算机测量与控制》
CSCD
北大核心
2010年第10期2265-2267,共3页
Computer Measurement &Control
基金
民航局科技基金项目(MHRD200927)
