Study Of The Fault Dictionary For Fault Diagnosis Of Analog Circuit

Testing and diagnosis on circuits and electronic devices are important fordevelopment andmaintenanceofsafeandreliableelectronicsystems.Althoughtest anddiagnosis on digital circuits and systems have been developed to a high level, test anddiagnosis on analog and mixed-signal circuits and systems still are evolved veryslowlydue to the lack of simple fault models and the presence of component tolerances andcircuit nonlinearities。According to collected statistics, although most part of anelectronic system is digital, about 80% of the faults occur in the analog segment. Sofaultdiagnosisofanalogcircuitismoreimportantnowadays.A further research to the fault dictionary method is presented in this paper andseveral techniques are applied in order to enhance the fault dictionary such as:application of Bayesian Theory, application of integer coding when building dictionaryand optimum test points selection. According to the experiments on circuit withtolerances, it shows that the application of these improves the capability of dictionaryonfaultdetectionandisolationwhenusingtodealwiththecircuitwithtolerance.Although these techniques improve the accuracy and definition of faultdictionary, workload increasing badly, this brings lots of work to simulation before test,this paper also makes improvement for example: using Bayesian Theory alternativelybases on the practical value (such as mean value and sigma of each fault we get bysimulating before test ). Noting that the circuit scale becomes more complex, faultdiagnosis requires heavy computations and large data structures. An artificial neuralnetworkwillbestudiedinfurtherresearch.