基于遗传PNN网络的组合导航故障诊断研究

针对INS/GPS组合导航系统观测信息无冗余且观测信息可能存在故障的情形,提出一种基于状态x2检验与自适应概率神经网络( APNN)相结合的组合导航故障诊断方法.该方法通过监测组合导航系统状态分量,提取故障的特征值并利用APNN确定故障的类别,从而实现故障的定位与隔离.APNN采用高斯函数作为激励函数,通过遗传算法获得模式层矢量最佳数目及匹配的平滑因子参数集,使每个神经元传递函数具有不同的平滑参数,提高了网络的泛化能力以及诊断精度.数值仿真结果表明,该算法能够有效地识别出INS/GPS组合导航系统的故障,确保了系统的安全性和可靠性.

Fault-diagnosis method for INS/GPS integrated navigation system based on PNN and genetic algorithm

Aiming at the characteristics of no redundant observation information and possible faults of INS/GPS integrated navigation,an improved fault diagnosis method for integrated navigation based on state chi-square test and adaptive probabilistic neural network(APNN) is proposed.Through monitoring the state vectors of the integrated navigation system,the normalized results of state chi-square test can be extracted as the input for APNN to identify the pattern of the fault,and then implement fault locating and isolating.The APNN is improved with GA algorithm to achieve the optimum number of the pattern layer neurons and match the smoothing parameters for each transfer function of neurons,which improve the generalization ability and diagnostic accuracy of the neural network.Simulation results show that the new method can not only identify the faults efficiently,but also improve the reliability and safety of the system.