Analog circuit soft fault diagnosis utilizing matrix perturbation analysis

This paper proposes a novel approach of analog circuit soft fault diagnosis utilizing matrix perturbation analysis. This method establishes an output response square matrix whose elements will change if circuits fail. Fault can be diagnosed via comparing the difference between the fault-free output matrix and the faulty. According to matrix theory, matrix spectral radius and perturbation matrix m1 norm are utilized to describe the difference. Differing from artificial intelligence algorithms, it is all completely unnecessary to train samples, and can be applied to more complex circuit diagnostics with fewer test nodes. Fault diagnosis, fault location and parameter identification can be realized by quadratic curve fitting in single fault mode. Experiments confirm the feasibility and correctness of this method.