Affiliations: Graduate Program in Computational Modeling,
Polytechnic Institute, State University of Rio de Janeiro, Rua Alberto Rangel
S/N, Vila Nova, Nova Friburgo, RJ, Brazil
Abstract: The formulation and solution of the inverse problem of damage
identification based on wave propagation approach are presented. Different
damage scenarios for a bar are considered. Time history responses, obtained
from pulse-echo synthetic experiments, are used to identify damage position,
severity and shape. In order to account for noise corrupted data, different
levels of signal to noise ratio – varying from 30 to 0 dB – are
introduced. In the identification process, different optimization methods are
investigated: the deterministic Levenberg-Marquardt; the stochastic Particle
Swarm Optimization; and a hybrid technique combining the aforementioned
methods. It is shown that the damage identification procedure built on the wave
propagation approach was successful, even for highly corrupted noisy data. Test
case results are presented and a few comments on the advantages of
deterministic and stochastic methods and their combination are also reported.
Finally, an experimental validation of the sequential algebraic algorithm, used
for modeling the direct problem, is presented.
