Redelico, FranciscoTraversaro Varela, FranciscoOyarzábal, Nicolás AndrésVilaboa, IvánRosso, Osvaldo A.2019-09-192019-09-192017-030378-4371http://ri.itba.edu.ar/handle/123456789/1761"In this paper several causal Information Theory quantifiers, i.e. Shannon entropy, statistical complexity and Fisher information using the Bandt and Pompe permutation probability distribution, measure are applied to describe the behavior of a rotating machine. An experiment was conducted where a rotating machine runs balanced and then, after a misalignment, runs unbalanced. All the causal Information Theory quantifiers applied are capable to distinguish between both states and grasp the corresponding transition between them. "enESTADISTICAMAQUINARIA ROTATIVAANALISIS DE FALLASTEORIA DE LA INFORMACIONENTROPIAArtículos de Publicaciones Periódicas