The integration of autonomous wireless elements in health monitoring network increases the reliability by suppressing power supplies and data transmission wiring. Micro-power piezoelectric generators are an attractive alternative to primary batteries which are limited by a finite amount of energy, a limited capacity retention and a short shelf life (few years). Our goal is to implement such an energy harvesting system for powering a single AWT (Autonomous Wireless Transmitter) using our SSH (Synchronized Switch Harvesting) method. Based on a non linear process of the piezoelement voltage, this SSH method optimizes the energy extraction from the mechanical vibrations. This AWT has two main functions : The generation of an identifier code by RF transmission to the central receiver and the Lamb wave generation for the health monitoring of the host structure. A damage index is derived from the variation between the transmitted wave spectrum and a reference spectrum. The same piezoelements are used for the energy harvesting function and the Lamb wave generation, thus reducing mass and cost, A micro-controller drives the energy balance and synchronizes the functions. Such an autonomous transmitter has been evaluated on a 300×50×2 mm3 composite cantilever beam. Four 33×11×0.3 mm3 piezoelements are used for the energy harvesting and for the wave lamb generation. A piezoelectric sensor is placed at the free end of the beam to track the transmitted Lamb wave. In this configuration, the needed energy for the RF emission is 0.1 mJ for a 1 byte-information and the Lamb wave emission requires less than 0.1 mJ. The AWT can harvested an energy quantity of approximately 20 mJ (for a 1.5 Mpa lateral stress) with a 470 μF storage capacitor. This corresponds to a power density near to 6mW/cm3. The experimental AWT energy abilities are presented and the damage detection process is discussed. Finally, some envisaged solutions are introduced for the implementation of the required data processing into an autonomous wireless receiver, in terms of reduction of the energy and memory costs.