Publication | Open Access
On-field experience with online diagnosis of large induction motors cage failures using MCSA
176
Citations
9
References
2002
Year
Large Induction MotorsFault DiagnosisCondition MonitoringReliability EngineeringEngineeringCurrent Power SpectrumDiagnosisOnline DiagnosisEnel ProduzioneSystems EngineeringAutomatic Fault DetectionFault DetectionOn-field ExperienceItalian Electric Board
The experience gained by ENEL Produzione (previously the Italian Electric Board) on monitoring the cage condition of large induction motors is reported in this paper. The diagnostic procedure is based on the motor current signature analysis and, in particular, on the two sideband current components near the frequency fundamental line that appear in the current power spectrum when a rotor bar/ring breakage occurs. According to the developed procedure, a diagnostic index obtained from these components is stored and its trend as a function of time allows for the detection of the occurrence of a failure in most cases. This event is clearly shown by the overcoming of a prefixed and triggered threshold. Moreover, machines with particular rotor magnetic structure are considered. In this case, unexpectedly high sideband components appear, even in the presence of healthy cages, and the test procedure was adapted to account for these conditions.
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