Blind Separation of rotating machine signals using Penalized Mutual Information criterion and Minimal Distortion Principle
The Blind Separation problem of convolutive mixtures is addressed in this paper. We have developed a new algorithm based on a penalized mutual information criterion recently introduced in [El Rhabi et al., A penalized mutual information criterion for blind separation of convolutive mixtures, Signal Processing 84 (2004) 19791984] and which also allows to choose an optimal separator among an infinite number of valid separators that can extract the source signals in a certain sense according to the Minimal Distortion Principle. So, the minimisation of this criterion is easily done using a direct gradient approach without constraint on the displacements. Thus, our approach allows to restore directly the contribution of the sources to the sensor signals without post-processing as it is usually done. Finally, we illustrate the performances of our algorithm through simulations and on real rotating machine vibration signals.
rotating machine mutual information minimal distortion principle signal processing fault detection condition monitoring mechanical systems blind source separation