基于知识的歼击机起飞爬升阶段的故障诊断与报警

Fault diagnosis and alarm based on knowledge for take-off and climbing of fighter

针对歼击机的起飞、爬升阶段 ,数据量大且复杂 ,对故障诊断要求精度高 ,实时性好 ,设计出粗集和神经网络相结合 ,分层诊断的方法 ,先定故障的类型 ,然后定故障的度 .其中在粗集诊断部分 ,提出了适合该研究对象的离散和简约方法 ,从而得到了少量但足够用的决策规则 ,使得实时诊断程序结构简单 ,实时性好 .包含诊断和报警模块的实时程序证明 ,此方法可以达到精度和实时性要求 .

A diagnosis method based on rough set theory and neural network is proposed for take-off and climbing of fighter. In this phase, the data are large and complex and high precision and real-time diagnosis are required, therefore a scheme is formed to diagnose fault style first with rough set theory and then fault degre e with neural network. Appropriate discretization method and reduction method are chos en and a few but enough decision rules are obtained, which can make the real-ti me diagnosis program simple. Real-time program with diagnosis modu le and alarm module proves that this method can satisfy the requirements.