A Method for Identifying Single Faults in Nonlinear Circuits

The paper focuses on fault diagnosis in nonlinear analog circuits. Due to its complexity, the problem, which has been the subject of research for over 50 years, remains unsolved. The paper proposes a comprehensive method for identifying single hard and soft faults in nonlinear DC circuits. The dictionary-based method belongs to the simulation-before-test method group. During dictionary creation, the possibility of multiple equilibrium points in transistor circuits is considered. For this purpose, Monte Carlo simulations that account for the spread of circuit parameters within tolerance limits are preceded by circuit analyses using a method that guarantees the determination of all operating points. A method for selecting nodes for hard faults is proposed. Two dictionaries are formulated for soft and hard faults. After performing measurements in the circuit under test, the dictionaries are searched to determine the fault type. In the case of soft faults, unlike methods that use artificial intelligence tools, it is possible not only to identify the faulty element but also to determine its approximate range of values. Furthermore, the paper highlights several problems and risks at the dictionary-creation stage. The method was verified through simulation and on a test bench under various test conditions.