Identification of structural parameters based on PZT impedance using genetic algorithms

Electromechanical (EIM) impedance method for structural health monitoring (SHM) is based on detecting the changes of the measured signatures of the Lead Zirconate Titanate (PZT) EM admittance (the inverse of the impedance). Although this method has been successfully applied for various engineering structures for damage detection, it is unable to specify the effect of damage on structural properties. The direct indicator of the structural properties is the structural mechanical impedance which can be extracted from the PZT EM admittance signatures. To model the structural impedance, this paper presents a multiple-degrees-of-freedom system consisting of a number of one-degree-of-freedom elements with mass, spring and damper components. Genetic algorithms (GAs) are employed to search for the optimal solution of the unknown dynamic system parameters by minimizing an objective function. Experiment has been carried on a two-storey concrete frame subjected to base vibrations that simulate earthquake. A number of PZT transducers are regularly arrayed and bonded to the frame structure to acquire PZT EM admittance signatures. The changes of the structural parameters in the model system are quantified using GAs. The relation between the distance of the PZT transducer away from the damage and the changes of the structural parameters identified by the PZT transducer is studied. Finally, the sensitivity of the PZT transducers is discussed.