摘要
文章探索了将离散Hopfield神经网络(DHNN)应用于船舶发电机故障诊断。利用DHNN作为按记忆内容寻址(CAM)的联想记忆能力,针对船舶发电机5种故障状态进行诊断。仿真的结果显示DHNN网络可以对几种常见故障进行有效的识别。
This paper discussed how to use the discrete Hopfield neural network （DHNN） for the fault diagnosis of marine generators. With the capacity of associative memory as DHNN being content -addressed memory （CAM）device,DHNN achieved diagnosis of shipboard generator for 5 fault-states.Simulation results show that the network can effectively identify several common faults.
出处
《仪器仪表用户》
2007年第6期114-116,共3页
Instrumentation
