• Dynamic modeling
• Macro-Fiber Composite
• piezoelectric patches
• self-powered
• Structural Health-Monitoring system

This MSc Thesis focuses on the development of dynamic models of a self-powered Structural Health-Monitoring (SHM) system using Macro-Fiber Composite (MFC) piezoelectric patches, and its characterization of performances under relevant operative conditions. The main objective is to integrate the capabilities of the MFC patches related to sensing and energy harvesting functions to obtain a SHM system that automatically permits to measure and record abnormal vibration levels without need of external electrical power supply.
During normal flight maneuvers, under structural vibrations with normal levels, the MFC patches can operate as energy harvesters, charging a small battery of the SHM electronic board. In case that abnormal loadings or stiffness variations occur, the patches can act as sensors, so that the SHM board, powered by the battery can measure and record signals on a non-volatile memory. During maintenance, the recorded measurements can be used to evaluate the load cycles on the structure up to implement eventual recovery actions.
The Thesis presents the development of different dynamic models of a cantilevered composite laminate with three MFC patches, characterized by different granularity and frequency contents: a LTI model for basic interpretation of the working principle and an object-oriented MATLAB/Simulink/SimScape model for the analysis of the complete SHM system, which also includes a full wave rectifier, a 3V-65mAh Li-ion battery and the logics implemented by the electronic control board. The SimScape model is validated with experiments coming from previous research activities carried out at the University of Pisa laboratories, with reference to both quasi-static and dynamic responses.
The results demonstrate the potential feasibility of the system, highlighting the ability to recharge a small battery, when vibrations occur at the first bending mode of the laminate. In addition, the study shows robustness to variations of frequency and amplitude of the vibration signals.