Baseline-free adaptive damage localization of plate-type structures by using robust PCA and Gaussian smoothing

Damage localization in plate-type structures has been widely investigated by exploring the structural characteristic deflection shapes (CDS's) or their spatial derivatives. Despite the substantial advances in this kind of methods, several key issues still need to be addressed to boost their efficiency for practical applications. This study considers three essential problems: susceptibility to measurement noise, absence of baseline-data on pristine structures, and selection of measurement sampling interval and that of the parameters to be used in the de-noising techniques for more accurate damage localization. To tackle these problems, a novel baseline-free adaptive damage localization approach is proposed, which combines the robust Principal Component Analysis (PCA) with Gaussian smoothing. A damage localization evaluator is defined to determine both the spatial sampling interval of the CDS's and the scale parameter of Gaussian smoothing to warrant a better damage localization. Moreover, effects of the measurement noise and numerical errors due to the use of the finite difference scheme on the estimate of the CDS derivatives are quantified. Finally, the feasibility and the effectiveness of the proposed method are verified both numerically and experimentally by using a cantilever plate with a small damage zone. It is found that the second-order spatial derivative of the CDS's is able to provide the best damage localization results among the first four order spatial derivatives of the CDS's.