基于IRN神经网络的雷达天线伺服系统故障诊断

Fault Diagnosis of Radar Servo System Using IRN Neutral Network

文中主要针对雷达天线伺服系统故障,提出了一种基于内部回归(Internally Recurrent Net,IRN)神经网络的故障诊断手段。通过分析雷达伺服系统的信号流程图,找到了导致天线故障的所有可能部件。利用故障树的分析手段对这些部件分类,发现同一故障部件可能引发不同的故障现象,同时对所有部件进行编号。建立适用于雷达天线伺服系统的IRN神经网络,其中输入层共有23个神经元对应23个测试点,输出层共有4个神经元对应所有故障的编号。对所建立的神经网络进行训练与测试,发现IRN神经网络能够很好地完成对所有故障部件的分类。

A fault diagnosis method for the radar servo system using the internally recurrent net(IRN) neutral network is presented in this paper.All the potential faulty components in the servo system are found out by analyzing the signal flow chart.The fault tree analysis(FTA) is then used to classify all faulty components.It is found that one faulty component can cause different faults.All the components have been labelled with numbers.Next,the IRN neutral network for the radar servo system is established,including 23 input neurons(corresponding to 23 test points) and 4 output neurons(corresponding to all fault numbers).The data from FTA are used as an input to train and test established IRN neutral network.It is found that the IRN neutral network can successfully classify all the faulty components.