基于模糊神经网络的液压动力机构故障诊断研究  

Fault Diagnosis of Hydro Dynamical Outfit Based on the Blurring Nerve Network Technique

作　　者：蔡桂芳[1] 李君[2] 

机构地区：[1]空军第一航空学院,河南信阳464000 [2]长沙理工大学桥梁与结构工程学院,湖南长沙410076

出　　处：《机电产品开发与创新》2007年第3期17-18,共2页Development & Innovation of Machinery & Electrical Products

摘　　要：介绍了模糊规则网络的原理及算法,并用该网络对一种由三通阀和差动液压缸构成的液压动力机构的故障进行了趋势预测。实验证明:用模糊神经网络技术能够及时准确的预报机器故障,为机器的尽快维修提供了可靠的依据。The theory and algorithm of blurring rule network is introduced, and it has been used in the fault trend prediction for hydro dynamical outfit made up of differential hydro cylinder. The experiments proved that blurring rule network is a effective method in fault prediction, and it can predict the faults of device quickly and accuracy, at the same time ,it can provide reliable basis for device overhaul.

关 键 词：模糊神经网络 液压动力机构 故障诊断 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]