KEYWORDS: Damage detection, Digital image correlation, 3D image processing, 3D metrology, Aluminum, Finite element methods, Data modeling, Model-based design, Systems modeling, Global system for mobile communications
Analytical models have shown that local damage in a structure can be detected by studying changes in the curvature of
the structure's displaced shape while under an applied load. In order for damage to be detected, located, and
quantified using curvature methods, a spatially dense set of measurement points is required on the structure of interest
and the change in curvature must be measurable. Experimental testing done to validate the theory is often plagued by
sparse data sets and experimental noise. Furthermore, the type of load, the location and severity of the damage, and
the mechanical properties (material and geometry) of the structure have a significant effect on how much the curvature
will change. Within this paper, three-dimensional (3D) Digital Image Correlation (DIC) as one possible method for
detecting damage through curvature methods is investigated. 3D DIC is a non-contacting full-field measurement
technique which uses a stereo pair of digital cameras to capture surface shape. This approach allows for an extremely
dense data set across the entire visible surface of an object. A test is performed to validate the approach on an
aluminum cantilever beam. A dynamic load is applied to the beam which allows for measurements to be made of the
beam's response at each of its first three resonant frequencies, corresponding to the first three bending modes of the
structure. DIC measurements are used with damage detection algorithms to predict damage location with varying
levels of damage inflicted in the form of a crack with a prescribed depth. The testing demonstrated that this technique
will likely only work with structures where a large displaced shape is easily achieved and in cases where the damage is
relatively severe. Practical applications and limitations of the technique are discussed.
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