摘要
新体制雷达系统的复杂性增加了雷达故障诊断的难度.为保证新体制雷达工作的可靠性和维修性能,运用人工智能理论,将神经网络与案例推理相结合,提出了雷达故障诊断系统结构和基于RBF神经网络故障诊断模型,给出了雷达故障案例的表示方法及快速检索算法.最后,通过实例分析证明了模型及方法的合理性和有效性.
The difficulty for radar fault diagnosis is increased due to the complexity of new system radars. For ensuring its performance on reliability and maintenance,the radar fault diagnosis system structure was presented by using the artificial intelligence theory and integrating the artificial neural network （ANN） with case-based reasoning （CBR）. And the representation of radar fault cases and their quick search were given,based on the RBF neural network fault diagnosis model. Eventually,by analysis of an example it shows that the proposed model and method are of feasibility and effectiveness.
出处
《空军雷达学院学报》
2010年第2期91-93,共3页
Journal of Air Force Radar Academy
关键词
雷达故障诊断
人工神经网络
案例推理
radar fault diagnosis
artificial neural network （ANN）
case-based reasoning （CBR）
