@inproceedings{aca7e863708f4e819cb2c779b91b8fa0,
title = "Open and closed-loop motor control system with incipient broken rotor bar fault detection using current signature",
abstract = "Motor drive system is considered the most important asset in industrial applications. Detection of broken rotor bars has long been important but difficult job in detection area of incipient motor faults. The need for highly efficient motor control drive systems becomes more and more important. Motors are controlled in closed-loop or open-loop modes of operation. This paper develops a novel approach for fault-detection scheme of broken rotor bar faults for three-phase induction motor using stator current signal. The empirical mode decomposition (EMD) combined with Wigner-Ville distribution (WVD) has been employed for the analysis of stator current signal. Artificial neural network is then used for pattern recognition of broken rotor bar signature. The proposed algorithm offers high performance in detecting broken rotor bar fault. Both simulation and experimental results show that stator current-based monitoring in conjunction with Winger-Ville distribution based on EMD yields a reliable indicator for detection and diagnosis of broken rotor bar faults using artificial neural network. All simulations in this paper are conducted using finite element analysis software. Experimental results validate the simulation and analytical results.",
keywords = "ANN, Broken rotor bar fault, Empirical mode decomposition, Induction machine, Wigner-Ville",
author = "Refaat, {Shady S.} and Haitham Abu-Rub and Saad, {M. S.} and Atif Iqbal",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = feb,
day = "24",
doi = "10.1109/IECON.2014.7048588",
language = "English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "774--780",
booktitle = "IECON Proceedings (Industrial Electronics Conference)",
address = "United States",
}