Piezoelectric materials exhibit significant deformation in response to an applied electric field, as well as generating an electrical charge in response to mechanical strain. Control designs and characterization of structural damage can take advantage of these dual properties. In this paper, the identification of damage is realized in two steps. The first uses the electric impedance technique in order to determine the location of the damage, and the second uses an optimization method to quantify the severity of the damage. Damage identification is an inverse problem, and has no unique solution. The hybrid approach proposed in this paper takes advantage of the electric impedance technique to localize the damaged regions with accuracy. This information permits a decrease in the number of variables involved in the process, which is a goal for any optimization technique. The procedure is validated through different particle swarm optimization approaches using an operator with random numbers based on Gaussian and Cauchy distributions.
piezoelectric sensor and actuator; smart structure; electric impedance; swarm intelligence; particle swarm optimization; system optimization; fault detection
