Probabilistic analysis and design of piezoelectric energy harvesting devices under modulated and filtered white Gaussian noise

The possibility of adopting vibration-powered wireless sensors for structural monitoring applications has received great attention in the last few years. Therefore, the development of effective computational approaches in this field is of paramount importance in order to evalu-ate the feasibility of such technology and to improve current design procedures. In this per-spective, the present paper illustrates an efficient approach for the electromechanical probabilistic analysis and design of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN). Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN which is filtered through the Clough-Penzien filter, whose dominant frequency is a time-dependent deterministic parameter. The considered piezoelectric harvester is a cantilever bimorph modelled as Euler-Bernoulli beam with a con-centrated mass at the free-end and its global behaviour is approximated by the fundamental vibration mode. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original semi-analytical procedure is adopted to estimate mean and stand-ard deviation of the generated electrical energy.