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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 300x50x2 mm3 composite cantilever beam. Four 33x11x0.3 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 0.1mJ. 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.
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