We propose a new approach to the study of diffusion dynamics in vibrated granularsystems. The dynamic of a granular material is mainly defined by dry frictioninteractions. This type of interaction is difficult to model for a large quantity ofparticles. In this work, we study a granular system by analyzing the angularposition time series of an immersed torsion oscillator and of an identical, torsionallyunconstrained probe. In order to interpret the behavior of our mechanical system, theexperiments are compared to simulations. We generate simulated time series using asimple model of a confined random walk. The global properties of the recordedsignals, both experimental and simulated, are extracted by applying fractal signalprocessing analysis. We show that the Hurst exponent of the time series can beemployed to discriminate the dynamics of the system. We conclude that the immersedprobe behaves as a Brownian particle that can switch between three distinctdynamical regimes, depending on the strength of the torsional constraint applied toit. If the probe is strongly constrained, its trail can be described with a fractalBrownian motion showing anomalous diffusion (subdiffusive behavior). As thestrength of the constraint is reduced, the system ‘unjams’ in a ordinary Brownianmotion (normal diffusion). Finally, as the constraints are further reduced, weobserve the onset of convection phenomena, which in turn induce a superdiffusivebehavior.