基于神经网络与专家系统的火控系统故障诊断

为了能在火控系统发生故障时，更快更好地诊断和排除，分析了人工神经网络和专家系统各自特点及其局限性，采用人工神经网络技术与专家系统相结合的方法，建立基于人工神经网络与专家系统故障诊断机制，对火控系统的故障进行智能诊断。克服了传统的诊断专家系统缺少有效的自学习、自适应机制，难以解决非线性系统故障问题的不足。这对于解决火控系统多征兆、多原因的复杂故障问题，是一条方便快捷的途径。

Fire Control System Fault Diagnosis Based on the Neural Network and Expert System

In order to make a diagnosis and obviate the fault faster and better when fire control system goes wrong, this paper analyses the characteristic and limitation of the artificial neural network and expert system, applies the way of associating the both, and buildes fault diagnosis mechanism based on the artificial neural network and expert system to make a intelligent diagnosis for the faults of fire control system. This method overcomes the insufficiency of traditional expert system such as lack of the mechanism of effective self- study and self- adapt, be difficult to resolve the nonlinear system fault problems. It is a convenient way to resolve the multi - sign and multi - reason complex fault problems of fire control system.