External fault identification experienced by 3-phase induction motor using PSVM
作者： A. P. Mittal , Hasmat Malik , Saarang Rastogi , Vihan Talur
DOI: 10.1109/34084POWERI.2014.7117762
关键词:
摘要: Fault diagnosis and condition assessment (FDCA) of rotating machines becomes important due to the age machine in service. Proper FDCA enhance machine's operational life, efficiency reducing catastrophic failure. This paper describes a realistic method for three phase induction motors (IMs) using readily available data. External faults experienced by IM are monitored proximal support vector (PSVM) compared its performance with standard artificial neural network which revealed that PSVM algorithm is quite faster investigations leading reduction computational load. RMS value 3-phase voltages currents utilized as input variable model identify six types external normal operating (NF) condition. Testing analysis 160 samples has been carried out represent robustness investigated seven status conditions wide changes loading perturbation.
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