An Analog Circuit Diagnosis Based on SVM Parameter Optimization and Feature Process

In order to solve the complexity of the fault caused by the nonlinear circuit and the variation of component parameter tolerance, the fault diagnosis method of analog circuit based on the SVM is deeply studied and used in the analog circuit. First, in order to solve the problems of the low efficiency and the low precision of traditional SVM parameter optimization methods, take QPSO as the starting point and improve the diversity of particle swarm optimization as the goal, combine with the emerging swarm intelligence optimization algorithm QPSO(quantum-behaved PSO) to improve the SVM parameter optimization; Secondly, in view of the problem of higher dimension and lower diagnosis efficiency caused by the increase of attribute types, from the perspective of feature selection, the IBQPSO algorithm is used to combine the feature to be selected with the parameter optimization of SVM, in order to improve the classification accuracy and generalization ability of the SVM; Finally, an example of typical filter circuit is given to show that the processed method should be feasible and effective to be used in the fault diagnosis of analog circuit of photoelectric equipment.