Scientia Iranica · 2012 · 22 citations · 7 references
ComputingElectrical EngineeringFeature EngineeringMachine LearningPower ElectronicsDiagnosisDiagnosticsFault DetectionFault DiagnosisPattern RecognitionSupport Vector MachinesElectrical Fault DiagnosisFault ClassificationFault IdentificationMachine Learning For Fault DetectionNoise RobustnessPower Electronics Fault DiagnosisRobustness To Noise
A method based on S transforms and support vector machines was presented for fault diagnosis of power electronics circuits in which the S transform time-frequency analysis of the fault signal is used to extract the features corresponding to various faults. Then, fault types are identified through the pattern recognition classifier, based on SVM. The simulation results show that the proposed method can accurately diagnose faults and locate fault elements for power electronics circuits. It also has excellent performance for noise robustness and calculation complexity, thus, having good practical engineering value in the solution to fault problems for power electronics circuits.
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