摘要
快速、准确地对火炮修后水弹试验评估与诊断是火炮水弹试验的重要环节。基于火炮结构原理,对火炮水弹试验故障树进行分析,在把握火炮水弹试验故障总体原因基础上,建立了基于RBF神经网络的火炮水弹试验故障诊断模型,并以某新型火炮水弹试验为例,对人工设置的故障进行了故障诊断,诊断结果表明了所建立诊断模型的正确性,以及诊断结果的可信性,该诊断模型可应用于火炮水弹试验工程实践。
The rapid and accurate detection and fault diagnosis posterior to the gun repair is an important link in the gun water-projectile test.The gun water-projectile test fault tree was built based on gun structure principle,which is conducive to the overall grasp of the fault of gun.The fault diagnosis model of artillery water bomb test was established based on RBF neural network.With the aid of a new type of gun water-projectile test,fault diagnosis was conducted in terms of the artificially set defects.The diagnostic results show that diagnosis model built in this paper is correct,and that considering the reliability of diagnostic results,the diagnosis model can be applied to the gun water-projectile test in engineering practice.
出处
《火炮发射与控制学报》
北大核心
2017年第1期95-100,共6页
Journal of Gun Launch & Control
关键词
火炮
故障诊断
故障树
RBF神经网络
水弹试验
gun
fault diagnosis
fault tree
RBF neural network
water-projectile test
