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Fault Detection and Classification of Faulty Induction Motors using Z-index and Frequency Analysis  

Lee, Sang-Hyuk (Department of Electrical Engineering, Pusan National University)
Publication Information
Journal of the Korean Society of Safety / v.20, no.3, 2005 , pp. 64-70 More about this Journal
Abstract
In this literature, fault detection and classification of faulty induction motors are carried out through Z-index and frequency analysis. Above frequency analysis refer Fourier transformation and Wavelet transformation. Z-index is defined as the similar form of energy function, also the faulty and healthy conditions are classified through Z-index. For the detection and classification feature extraction for the fault detection of an induction motor is carried out using the information from stator current. Fourier and Wavelet transforms are applied to detect the characteristics under the healthy and various faulty conditions. We can obtain feature vectors from two transformations, and the results illustrate that the feature vectors are complementary each other.
Keywords
induction motor; fault detection; wavelet transformation;
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