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http://dx.doi.org/10.5050/KSNVE.2014.24.9.675

Development of EMD-based Fault Diagnosis System for Induction Motor  

Kang, Jungsun (School of Electricity & Electronics, Ulsan College)
Publication Information
Transactions of the Korean Society for Noise and Vibration Engineering / v.24, no.9, 2014 , pp. 675-681 More about this Journal
Abstract
This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.
Keywords
Induction Motor; Fault Diagnosis; Empirical Mode Decomposition; Intrinsic Mode Function; Neural Network;
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Times Cited By KSCI : 5  (Citation Analysis)
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