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In the last few years, Motor Current Signature Analysis (MCSA) has proven tobe an effective method for electrical machines condition monitoring. Indeed,many mechanical and electrical faults manifest as side-band spectral componentsgenerated around the fundamental frequency component of the motor current.These components are called interharmonics and they are a major focus of faultdetection using MCSA. However, the main drawback of this approach is that theinterference of other more prevalent components can obstruct the effect ofinterharmonics in the spectrum and may therefore impede fault detectionaccuracy. Thus, we propose in this paper an alternative approach thatdecomposes the different current components based on the Vandermonde model andimplements the tracking of each distinct component in time and spectraldomains. This is achieved by estimating their respective relevant parametersusing the Gradient Descent algorithm. The results of this work prove to bepromising and establish the parametric tracking of the electrical currentcomponents using the Gradient Descent algorithm as a reliable monitoringapproach.

Parametric Tracking of Electrical Currents Components Using Gradient Descent Algorithm