Analog Circuit Fault Diagnosis System Based On PSO-SVM

In the process of design verification and mass production of electronic products,analog circuit detection and fault diagnosis technology has always been an important research content in the field of electronic detection.Due to the nonlinearity and tolerance of analog circuit components,the development of analog circuit diagnosis related technologies is relatively slow,resulting in the absence of a relatively complete and mature analog circuit fault diagnosis system,which is difficult to meet the needs of circuit testing and diagnosis in the development of electronic industry.Therefore,the research on analog circuit fault diagnosis technology has important theoretical significance and practical application value.This paper focuses on the SVM analog circuit fault diagnosis model.Wavelet packet analysis has good time-frequency characteristics,which can decompose the original model into high-frequency signals and low-frequency signals.It is especially suitable for the analysis and processing of non-stationary signals.The fault response signals of analog circuits have non-stationary characteristics.Therefore,this paper uses wavelet packet analysis to extract the features of fault signal data.At the same time,in order to improve the accuracy of analog circuit fault diagnosis,this paper uses PSO algorithm to optimize the parameters of SVM model.This paper uses LabVIEW graphical programming language combined with MATLAB hybrid programming to realize analog circuit fault diagnosis software based on PSO-SVM.On this basis,the hardware and software are combined to build a complete analog circuit fault diagnosis experimental platform.The platform can collect,analyze and process signals from different circuit test points by changing the position of the probe,so as to realize the test and diagnosis of analog circuits.Then,the accuracy of analog circuit fault diagnosis is verified by controlling PCB test platform.