Identification of Damage in Beams by Modal Curvatures Using Acoustic Beamformers

This paper presents an approach to damage identification in beams by modal curvatures based on the use of beamforming algorithms. These processors have been successfully used in acoustics for the last thirty years to solve the inverse problems encountered in source recognition and image reconstruction, based on ultrasonic waves. In addition, beamformers apply to a broader range of problems in which the forward solutions are computable and measurable. This especially concerns the field of structural vibrations, where the use of such estimators has not received attention to date. In this paper, modal curvatures will play the role of replica vectors of the imaging field. The choice to use modal curvatures is motivated by means of numerical studies and experimental tests on a steel beam. Furthermore, we compare the performance of the Bartlett and minimum variance distortionless response (MVDR) beamformers with an estimator based on the simple minimization of the difference between model and measured data. The results suggest that the application of the MVDR beamformer is highly effective, especially in cases of slight damage between two sensors. MVDR enables both damage localization and quantification.