Experimental design of dynamic model-based damage identification in piezoelectric ceramics
A model-based inverse problem strategy is proposed for damage characterization, starting from the electromechanical response measurement as input data, and incorporating a numerical model that simulates the piezoelectric response. Furthermore, a sensitivity analysis is developed to provide a rational basis to correctly design the excitation/measurement system. The model-based inverse problem is solved by minimizing a cost functional using genetic algorithms. The cost functional or discrepancy is defined as the L-2 norm of the difference between experimental and simulated measurements. The latter are obtained by solving the forward problem, using a novel 2D dynamic piezoelectric finite element. The effects of measurement noise and model uncertainties are studied in detail through a sensitivity analysis, where a sensitivity factor is defined and implemented. The proposed inverse problem strategy reconstructs the defect characteristics with sufficient precision, under realistic levels of noise.
damage identification piezoelectrics inverse problem genetic algorithms finite element method