Experimental detection of defects in variable speed fan bearing using stator current monitoring
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Experimental detection of defects in variable speed fan bearing using stator current monitoring Abdelkarim Bouras1 · Soumaya Bennedjai2 · Slimane Bouras2 Received: 20 October 2019 / Accepted: 3 April 2020 © Springer Nature Switzerland AG 2020
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. Keywords Fan motor · Bearing defects · Motor current signature analysis · FFT · STFT · Gabor spectrogram
1 Introduction The monitoring of electromechanical systems composed of an induction motor and a fan in an industrial environment is a fundamental task, considering their importance in the animation of technological processes [1–3]. Following mechanical alterations (loss of fin, erosion or fouling of the blades, etc.), these systems are often subject to unbalance faults which are generally at the origin of the deterioration of the bearings. In the presence of these mechanical faults, significant pumping of the supply current is observed, as well as vibrations and torque fluctuations which have very critical consequences for the safety of the equipment and the personnel.
The fact of detecting and correctly characterizing these failures at an early stage is necessary to anticipate the definitive shutdown of the system, whose cost has a significant financial impact. Vibration analysis is one of the best diagnostic methods especially for the study of mechanical failures on rotating machines [4]. Nevertheless, these approaches have shown their limits when it comes to defects inducing torque variations or incipient defects that are almost imperceptible. To accurately extract information about these failures, research was particularly directed to the MCSA (Motors Current Signature Analysis) [5–9]. The contribution to this work lies primarily in the simultaneous application of the FFT, OPVA and STFT. C
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