Analog circuit fault diagnosis based on PCA and LVQ

In order to solve the difficulty of recognition in analog circuit fault diagnosis,a new analog circuit fault diagnosis method based on principal component analysis(PCA) and learning vector quantization(LVQ) is proposed in this paper.PCA is applied to extract the feature of the response signals to circuit under test(CUT).Then the optimal feature is inputted into an LVQ network to train and identify different fault cases.The example of Sallen-Key bandpass filter circuit fault diagnosis shows that this method is effective and has higher fault diagnosis rate.