摘要
为防止传感器故障影响空空导弹飞行任务达成,针对空空导弹非线性气动力模型参数难以确定的问题,提出了一种基于神经网络的传感器在线故障诊断方法。利用该方法构造了空空导弹加速度传感器的故障诊断器,并以数字仿真平台对常见的加速度传感器故障进行在线故障检测。仿真结果表明,设计的故障诊断器可有效诊断故障并准确估计传感器输出,具有一定工程应用价值。
In order to prevent sensor fault impact air-to-air missile flight mission accomplished,aiming at the parameter uncertainty for nonlinear aerodynamic model of air-to-air missile,a method for sensor online fault diagnosis based on BP neural network is proposed.A fault diagnosis for the acceleration sensor of air-to-air missile is constructed,which applies to the digital simulation,and analyzed the common fault of acceleration sensor online.The simulation results show that,the fault is effectively diagnosed and the sensor output is accurately estimated by the fault diagnosis,which has practical value.
作者
李伟
花文华
张金鹏
LI Wei;HUA Wenhua;ZHANG Jinpeng(China Airborne Missile Academy,Henan Luoyang 471009,China;Aviation Key Laboratory of Science and Technology on Airborne Guided Weapons,Henan Luoyang 471009,China)
出处
《弹箭与制导学报》
北大核心
2021年第3期11-14,共4页
Journal of Projectiles,Rockets,Missiles and Guidance
基金
装备预研重点实验室基金(61422110202)资助。
关键词
神经网络
在线故障诊断
传感器
空空导弹
neural network
online fault diagnosis
sensor
air-to-air missile