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Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. Indoi:10.4173/mic.2017.3.4 fatcat:jwbakxroqrbrtphxr5ua644jn4