Abstract
Misalignment faults in drive systems occur when the motor and load are not properly aligned, leading to deviations in the centerlines of the coupled shafts. These faults can cause significant damage to bearings, shafts, and couplings, making early detection essential. Traditional diagnostic techniques rely on vibration monitoring, which provides insights into both mechanical and electromagnetic fault signatures. However, its main drawback is the need for external sensors, which may not be feasible in certain applications. Alternatively, motor current signature analysis (MCSA) has proven effective in detecting faults without requiring additional sensors. This study investigates misalignment faults in synchronous reluctance motors (SynRMs) by analyzing both vibration and current signals under different load conditions and operating speeds. Fast Fourier transform (FFT) is applied to extract characteristic frequency components linked to misalignment. Experimental results reveal that the amplitudes of rotational frequency harmonics ((Formula presented.), (Formula presented.), and (Formula presented.)) increase in the presence of misalignment, with (Formula presented.) exhibiting the most stable progression. Additionally, acceleration-based vibration analysis proves to be a more reliable diagnostic tool compared to velocity measurements. These findings highlight the potential of combining current and vibration analysis to enhance misalignment detection in SynRMs, improving predictive maintenance strategies in industrial applications.
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Navarro-Navarro, A., Biot-Monterde, V., Ruiz-Sarrio, J. E., & Antonino-Daviu, J. A. (2025). Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors. Machines, 13(4). https://doi.org/10.3390/machines13040319
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