Finite element model updating from full-field vibration measurement using digital image correlation

Abstract

The comparison of structural responses, e.g. natural frequencies and mode shapes, between predictions and measurements is an important step in finite element (FE) model updating. Full-field measurement techniques such as high speed cameras with digital image correlation (DIC) algorithms provide detailed, global displacement data. It is necessary to compress huge amounts of full-field data before implementing the comparison procedures. Image processing and pattern recognition techniques offer effective ways of doing this. Image decomposition using integral transformation is one of the most common procedures. It is found that appropriate selection or construction of the transformation kernels usually generates succinct and effective shape feature terms. Thus, the discrepancies between the geometric mode shapes may be assessed by using distance measures between the shape feature vectors. In the present study, vibration mode shapes of a composite panel are measured by a DIC system and predicted by a FE model. Succinct and effective shape features of the full-field mode shapes were obtained by employing the Tchebichef moment descriptor. Mode shape discrepancies are clearly indicated by the resultant Tchebichef features. The FE model was then modified and updated. Results show that including only the shape features results in a better updated model than when natural frequencies only are used. The most improved model was obtained when both natural frequencies and shape features are included in the updating routine.