摘要
分析了电液伺服阀静态特性与故障模式之间的映射关系 ,介绍了基于BP神经网络电液伺服阀故障模式识别的方法 ,并进行了实验研究 ,结果表明该方法故障模式识别准确率较高 ,可以进一步与伺服阀试验台测试功能进行结合 ,形成一种具有自学习。
The mapping was described between the static ch ar acteristics and the state modular of electro-hydraulic servo valve. An intellige nt test system was developed and tested in basis of the modular identification f or BP nerve network,which can test the state characteristics of servo valve and to identify its state modular. The result shows that the method has better accur acy in fault model identification. It can form a check system which has self-lea rning, self-testing and intelligent diagnosis in combined with the test function of servo valve test-bed.
出处
《机床与液压》
北大核心
2004年第6期179-181,共3页
Machine Tool & Hydraulics
关键词
神经网络
模式识别
故障诊断
电液伺服阀
Nerve network
Modular identification
Fault diagno sis
Electro-hydraulic valve
