基于小波分析和神经网络的模拟电路故障诊断方法

A Method for Fault Diagnosis of Analog Circuits Based on Neural Network and Wavelet Analysis

提出了一种基于神经网络和小波分析的模拟电路故障诊断的系统方法。该方法通过对电路的可测性测度计算,选择电路的最佳测试节点,然后利用小波分析作为特征提取手段提取电路的故障特征向量,经归一化和主元分析(PCA)处理后,得到最优特征向量,最后输入到神经网络实现电路故障诊断。计算机仿真结果表明该方法具有更好的故障分辨率。

A systematic method for fault diagnosis of analogue circuits based on the combination of neural network and wavelet analysis is presented, the proposed method calculates the testability of the circuit then uses wavelet analysis as a tool to extract the best optimal feature information, the features are applied to the proposed neural network and the fault pattern are classified. The simulation result shows that the proposed method can classify the faults well.