Model Updating Using Shape Descriptors from Full-Field Images

Abstract

The comparison of structural responses (natural frequencies, mode shapes or strain maps) between predictions and measurements is an important step in finite element (FE) model updating. Full-field measurement techniques such as digital image correlation (DIC) provide detailed, global displacement data. It is necessary to compress huge amounts of full-field data before implementing the comparison procedures. Image decomposition using orthogonal kernel functions is one of the most common approaches. Appropriate selection or construction of the kernels generates shape feature terms capable of accurate image reproduction. Thus, the discrepancies between data and FE predictions may be assessed by using distance measures between the shape feature vectors. Two examples of model updating using shape features are described. In the first example vibration mode shapes of a composite panel from a structure to be deployed in outer space are measured by a DIC system. FE model updating is carried out using natural frequencies and Tchebichef moment descriptors. In the second example a square plate with a circular hole subject to a uniaxial tensile load is considered. Model updating of nonlinear elasto-plastic material properties is carried out using modified Zernike moment descriptors.