Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISIE.2011.5984490
Title: Online fault detection of induction motors using frequency domain independent components analysis
Authors: Wang, Z.
Chang, C.S. 
Keywords: Fast Fourier Transform (FFT)
Fault detection
Features of the frequency signatures (FS features)
Independent Component Analysis (ICA)
Induction Motor
Issue Date: 2011
Source: Wang, Z.,Chang, C.S. (2011). Online fault detection of induction motors using frequency domain independent components analysis. Proceedings - ISIE 2011: 2011 IEEE International Symposium on Industrial Electronics : 2132-2137. ScholarBank@NUS Repository. https://doi.org/10.1109/ISIE.2011.5984490
Abstract: This paper proposes an online fault detection method for induction motors using frequency-domain independent component analysis. Frequency-domain results, which are obtained by applying Fast Fourier Transform (FFT) to measured stator current time-domain waveforms, are analyzed with the aim of extracting frequency signatures of healthy and faulty motors with broken rotor-bar or bearing problem. Independent components analysis (ICA) is applied for such an aim to the FFT results. The obtained independent components as well as the FFT results are then used to obtain the combined fault signatures. The proposed method overcomes problems occurring in many existing FFT-based methods. Results using laboratory-collected data demonstrate the robustness of the proposed method, as well as its immunity against measurement noises and motor parameters. © 2011 IEEE.
Source Title: Proceedings - ISIE 2011: 2011 IEEE International Symposium on Industrial Electronics
URI: http://scholarbank.nus.edu.sg/handle/10635/71257
ISBN: 9781424493128
DOI: 10.1109/ISIE.2011.5984490
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