IEE Proceedings - Generation Transmission and Distribution · 1995 · 22 citations · 0 references
ComputingComputer ScienceElectrical EngineeringArtificial IntelligenceElectric MachinesMachine LearningCondition MonitoringDiagnosticsElectrical System DiagnosticsFault DetectionFault DiagnosisNeural NetworksFault Diagnosis In RotorsMachine Fault DiagnosisMachine Learning For Fault DetectionNeural Network ModelingNeural Network-based DiagnosisOnline Anomaly DetectionOnline Fault DetectionStator Winding Faults
The paper demonstrates how artificial neural networks can be used for the online detection of interturn faults on the rotor of an alternator. A simple network has been designed and tested on a laboratory micromachine. The tests have shown that by employing a neural network to predict the field current from measurements at the stator terminals, operation with a faulted rotor can be successfully identified.