Abstract
Multifunctional smart boards with embedded piezoelectric sensors and actuators for health monitoring, impact identification, and vibration and noise control are under development at Tohoku University. In this paper the health monitoring function of the smart board to identify the position of an attached mass is introduced. The localization used the variation of peak frequency in the electric impedance curve of the imbedded piezoelectric elements and a radial basis neural network. The peaks in the electric impedance curve of the PZT elements correspond to the natural frequency of the in-plane vibration mode of the board and their frequency changes due to the attachment of mass. The effectiveness of this method was verified in the experiment.
