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• W3016593928 abstract "This article presents an experimental contribution to detect and diagnose mechanical faults, including bearing faults, which are the cause of most faults in single or variable speed fan motor systems. For this, we proceed to the extraction of the characteristics appearing in the supply current signal of the diagnostic system, by the application of three complementary approaches. During our experimental study, we found that one of the best methods for diagnosing single or multiple mechanical faults in induction motor systems is MCSA (Motors Current Signature Analysis), to which we applied the FFT (Fast Fourier transform) spectral analysis completed by the park vector approach orbital (OPVA) applied to the components of the current stator vector. In order to confirm the reliability of our diagnosis, these two approaches have been supplemented by the Gabor spectrogram (STFT). The practical validation of this plural methodology, in the case of a bearing degradation, was carried out on a variable speed fan motor of 0.25 HP. The results obtained by this fault detection technique are satisfactory and interesting because they make it possible to anticipate breakdowns and, therefore, to program and control the maintenance costs of industrial systems without affecting production." @default.
• W3016593928 created "2020-04-24" @default.
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• W3016593928 date "2020-04-13" @default.
• W3016593928 modified "2023-09-27" @default.
• W3016593928 title "Experimental detection of defects in variable speed fan bearing using stator current monitoring" @default.
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• W3016593928 doi "https://doi.org/10.1007/s42452-020-2687-2" @default.
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