容差模拟电路的软故障诊断的小波方法

Wavelet Method for Soft Fault Diagnosis of Tolerance Analog Circuit

给出了容差模拟电路软故障诊断的小波与量子神经网络方法,利用小波分析,取其能反映故障信号特征的成分做为电路故障特征,再输入给量子神经网络,不仅解决了一个可测试点问题,并提高了辨识故障类别的能力,而且在网络训练之前,利用主元分析降低了网络输入维数。实验证明了这种方法的可行性与适用性。

The article presents the wavelet of soft fault diagnosis for tolerance analog circuits and the quantum neural network method; using wavelet analysis, it selects the fault signal that can reflect the characteristics of circuit components as fault features, and then enter it to the quantum neural networks. This not only solves a test point problem and improves the identification capabilities of fault types. Before the network training, it uses principal component analysis to reduce the importation of network dimension. Experiments show the feasibility and applicability of this method is.