Metrology and Measurement Systems · 2009 · 14 citations · 12 references
EngineeringElectrical EngineeringAnalog ElectronicsMachine LearningMicroelectronicsAnalog Integrated CircuitsDiagnosisDiagnosticsElectrical System DiagnosticsFault DetectionFault DiagnosisBand-pass FiltersCircuit Response AnalysisCircuit State VariablesElectrical Fault DiagnosisNeural Network-based DiagnosisOperational Amplifier CircuitsParametric FaultsVoltage
A method of global parametric fault diagnosis in analog integrated circuits is presented in this paper. The method is based on basic features calculated from a circuit under the test’s time domain response to a voltage step, i.e. locations of maxima and minima of the circuit-under-test response and its first order derivative. The testing and diagnosis process is executed with the use of an artificial neural network. The neural network is supplied with extracted basic features. After evaluation and discrimination, the output indicates the circuit state. The proposed diagnosis method has been verified with the use of exemplary integrated circuits – an operational amplifier μA741, a sinewave oscillator and an integrated band-pass filter.
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