Method of fault detection and isolation in nonlinear electrical circuits

Fault diagnosis in analog electrical circuits: data-driven method

“…-the simulation of a circuit for different faults to generate training data for an artificial neural network is presented in [2,15]; -the method of establishing a fault dictionary using Wavelet transform is developed in [13]; -in [6,7] the probabilistic graphical models are used; here faulty components are identified by looking for high probabilities for values of characteristic magnitude that deviate considerably from the nominal values; -the probabilistic model-based approach presented in [12] is formally founded and based on Bayesian network and arithmetic circuits; -the method based on diagnostic observers of states developed in [5,[20][21][22] considers linear and nonlinear circuits as dynamic systems; it is necessary to stress that the method suggested in [21] can be used for diagnosis in electrical circuits containing non-smooth nonlinearities such as hysteresis and saturation.…”

Filaretov, V. F.; Zhirabok, A. N. and Tkachev, D.: Non-Parametric Method for Fault Diagnosis in Electrical Circuits

“…the probabilistic model-based approach presented in [11] is formally founded and based on Bayesian network and arithmetic circuits; the method based on diagnostic observers developed in [5,18,19,20] considers linear and nonlinear circuits as dynamic systems; it is necessary to stress that the method suggested in [20] can be used for diagnosis in electrical circuits containing non-smoth nonlinearities such as hysteresis and saturation.…”