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