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Blind Separation of rotating machine signals using Penalized Mutual Information criterion and Minimal Distortion Principle

Abstract : 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) 1979–1984] 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.
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https://hal-enpc.archives-ouvertes.fr/hal-01812922
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Soumis le : mardi 12 juin 2018 - 00:03:43
Dernière modification le : mercredi 21 octobre 2020 - 12:02:02
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Mohammed El Rhabi, Hassan Fenniri, Guillaume Gelle, Georges Delaunay. Blind Separation of rotating machine signals using Penalized Mutual Information criterion and Minimal Distortion Principle. Mechanical Systems and Signal Processing, Elsevier, 2005, 19 (6), pp.1282 - 1292. ⟨10.1016/j.ymssp.2005.08.028⟩. ⟨hal-01812922⟩

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