A method for fault diagnosis of analog circuits based on optimized fuzzy inference

Because of the difficulty of disposing of fuzzy inference rules for fault diagnosis, a systematic approach for fault diagnosis of analog circuits based on optimized fuzzy inference is presented. The fuzzy logic system for based on fuzzy inference analog circuits fault diagnosis, quantum-inspired evolutionary algorithm (QEA) is used to optimize the membership function of the rules of the fault diagnosis fuzzy logic system, then self adapted genetic algorithm to select the optimum fuzzy rule aggregate, so the number of fuzzy rules is decreased to make it easy to dispose fault diagnosis of analog circuits. The simulation results of a analog power magnifier circuits show the fault diagnosis method of the analog circuits with optimized fuzzy inference is effective.