Local damage detection using the two-dimensional gapped smoothing method

This paper presents a procedure for locating variability in structural stiffness. For some types of structure, this variability is directly related to manufacturing defects and/or in-service damage. Unlike many published damage detection methods, the procedure presented here uses only data obtained from the damaged structure. Baseline data and theoretical models of the undamaged structure are not used during the analysis presented here. The procedure locates regions in a structure where the stiffness varies. Providing it is known that the structure, in its undamaged state, is homogeneous with respect to stiffness, the procedure will detect the areas of inhomogeneity that are caused by the incipient damage. For non-homogeneous structures, some knowledge of the structural details (for example, engineering drawings or a baseline test) is required in order to discriminate damage. The procedure is a two-dimensional generalization of a previously published one-dimensional gapped smoothing method, whereby local features in vibration curvature shapes are extracted using a localized curve fit (i.e., smoothing). A variability index is generated for each test point on the structure. Increased variability is due either to structural stiffness features or damage. A statistical treatment of the indices enables discrimination of areas with significant stiffness variability. Providing the damaged areas are sufficiently small compared to the total surface area, their indices will be statistical outliers. The procedure can either analyze mode shape data, or frequency dependent operating displacement shape data. ocedure is demonstrated with a finite element model of a plate, and experiments on composite plates with deliberately induced multiple delaminations. Finally, the method is demonstrated on data taken from a large composite hull structure. In all cases the procedure successfully located the damaged regions.