Detection and Discrimination Between Unbalanced Supply and Phase Loss in PMSM Using ANN-Based Protection Scheme
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Recently, Permanent Magnet Synchronous Motors (PMSM) is one of the most attractive electric machine in industrial applications, therefor must be protected against electrical and mechanical failures for continue their operation safely. However, different kinds of faults are unavoidable in motors during their operational service. Unbalancing in the supply voltage is common in grid supply. However, the unbalance supply and phase loss produces similar symptoms. Therefore, this paper focuses on unbalanced supply condition diagnosis and discrimination between unbalancing in supply and single phasing or phase loss fault based. The proposed technique utilizes the ratio of third harmonic to fundamental of stator line currents and supply voltages using artificial neural network (ANN). The presented approach gives high degree of accuracy in detection and diagnosis of phase loss fault and those due to supply voltages unbalance using artificial neural network. All simulations in this paper are conducted using finite element analysis software. The approach is proven effectively through experimental validation. © 2013 IEEE.
author list (cited authors)
Refaat, S. S., Abu-Rub, H., Saad, M. S., Aboul-Zahab, E. M., & Iqbal, A.