On soft fault diagnosis method based HHT for analog circuits

To diagnose soft fault for analog circuits, a method based on Hilbert-Huang Transform (HHT) is established. Through applying an alternating signal to the circuit under test and the output point as the sole test point, HHT processes output voltage signal, energy of intrinsic mode function (IMF) components and Hilbert marginal spectrum composed of fault feature vector. The fault components can be localized combined with BP neural network. This method can not only diagnose single fault, but also diagnose multiple faults. The simulation experimental results demonstrate that the average single fault diagnosis rate is 96% and the average multiple faults diagnosis rate is 91.3%, the actual experimental results demonstrate that the average fault diagnosis rate is 82%, verify the effectiveness and practicality of the proposed approach.