Identifying structural damage with data driven impedance response calibration
Jiong Tang, Pei Cao · 2018
The impedance/admittance measurements of a piezoelectric transducer circuit bonded to or embedded in a host structure can be used as damage indicator, since damage will introduce notable impedance shifts. When a credible model of the healthy structure, such as the finite element model, is available, using the impedance/admittance change information as input, it is possible to identify both the location and severity of damage. In this research we cast the damage identification problem into a many-objective optimization framework through impedance response calibration using Gaussian Process. With damage location and severity as unknown variables, the objective functions are response surfaces calibrated using emulated damaged scenarios assisted by Gaussian Process. Subsequently, a ε - dominance enabled many-objective algorithm based on multi-objective Simulated Annealing is devised to facilitate the many-objective optimization. The proposed approach yields high-quality results that can be further investigated for model updating.