High frequency mode shapes characterisation using Digital Image Correlation and phase-based motion magnification

High speed video cameras provide valuable information in dynamic events. Mechanical characterisation has been improved by the interpretation of the behaviour in slow-motion visualisations. In modal analysis, videos contribute to the evaluation of mode shapes but, generally, the motion is too subtle to be interpreted. In latest years, image treatment algorithms have been developed to generate a magnified version of the motion that could be interpreted by naked eye. Nevertheless, optical techniques such as Digital Image Correlation (DIC) are able to provide quantitative information of the motion with higher sensitivity than naked eye. For vibration analysis, mode shapes characterisation is one of the most interesting DIC performances. Full-field measurements provide higher spatial density than classical instrumentations or Scanning Laser Doppler Vibrometry. However, the accurateness of DIC is reduced at high frequencies as a consequence of the low displacements and hence it is habitually employed in low frequency spectra. In the current work, the combination of DIC and motion magnification is explored in order to provide numerical information in magnified videos and perform DIC mode shapes characterisation at unprecedented high frequencies through increasing the amplitude of displacements. (C) 2017 Elsevier Ltd. All rights reserved.