基于神经网络的模拟电路故障诊断的仿真研究

Simulation Research on Fault Diagnosis of Analog Circuit Based on Neural Network

为了辅助学生进行模拟电路板特定故障的诊断训练,基于人工神经网络模型通过LabVIEW和MATLAB软件联合编程进行仿真研究,利用MATLAB软件工具建立神经网络模型,并使用预先采集的电路板故障样本数据对模型的参数进行训练,利用LabVIEW软件调用已训练好的神经网络模型对输入的待诊断数据进行分析,得出故障类型结果并显示,系统诊断准确率较高,效果较好。

In order to assist students in the diagnosis training of analog circuit board specific fault,and based on the artificial neural network model,joint programming and simulation research are carried out by softwares of LABVIEW and MATLAB.The neural network model is established by using MATLAB software tools,and the parameters of the model are trained by using the pre-collected circuit board fault sample data.LABVIEW software was used to call the trained neural network model to analyze the input data to be diagnosed.LABVIEW software is used to call the trained neural network model to analyze the input data to be diagnosed.The fault type was obtained,and the result showed that the system diagnosis accuracy is higher and the effect is better.