摘要
分析了飞机电源系统欠压故障的发生原因和判别,尝试了一种基于改进E lm an神经网络的飞机电源欠压故障仿真方法,在阐述E lm an网络理论的基础上,将改进E lm an网络应用于飞机电源欠压故障的诊断,分析了网络结构、学习算法、特征提取和故障判别方法;网络模型应用了故障样本及专家经验知识,并通过学习使模型不断完善。通过实验数据验证,该网络模型和故障诊断方法是可行和有效的。
The root cause and discrimination of the under-voltage fault of aircraft power supply system is analyzed. A simulation method for under-voltage fault diagnosis based on improved Elman neural network was attempted. The improved Elman network was applied to the diagnosis of under-voltage fault of aircraft power supply. The network structure, learning algorithm, feature extraction and method of the fault discrimination were investigated. Fault samples and expert experience knowledge were applied in the network model, and the model is optimized by learning. The simulation results showed that the network model and the method of fault diagnosis are feasible and effective.
出处
《电光与控制》
北大核心
2009年第8期90-92,96,共4页
Electronics Optics & Control
关键词
飞机电源系统
欠压保护
ELMAN神经网络
故障诊断
aircraft power supply
under-voltage protection
Elaman neural network
fault diagnosis
作者简介
程建兴（1962-），男。陕西兴平人，博士生，高级工程师，研究方向为飞机电源技术及自动检测。E—mail：jianxingch@163．com
