Narrow Results

This paper considers a vibration-based damage assessment approach which is based on the general idea for signal cross-correlation. Here the method is demonstrated and validated on a composite laminate beam and it is applied for the purposes of delamination assessment in composite structures. The method uses two measures of cross-correlation between two vibration signals measured in different points on the structure in order to diagnose the delamination. The linear cross-correlation as well as a new measure for nonlinear cross-correlation, the mutual information, are introduced and applied for the purposes of delamination assessment. The delamination assessment is based on the comparison of the measures for the healthy and the damaged state of the structure. In this study, the method is applied using the free decay responses of the beam. Two delamination indices are introduced and they are used for the purposes of delamination detection and localization.

This chapter studies the application of data-driven methods and specifically principal component analysis (PCA) and singular spectrum analysis (SSA) for purposes of damage assessment in structures and machinery. In this study, data analysis methods PCA and SSA are applied to the measured vibration signals in order to extract information about the state of the structure/machinery and the presence of a fault in it. Two applications are offered, one for damage assessment on a wind turbine blade and another one for fault diagnosis in rolling element bearings. The results demonstrate strong capabilities of the investigated methodology for both structural damage detection and rolling element fault diagnosis. Eventually, a discussion about the capabilities of the studied methodology and the way forward regarding extending its capabilities and applications is offered.