Abstract
Modal identification is carried out in the shape-feature domain using full-field data from a DIC system. The methodology is illustrated using a car bonnet of 3D irregular shape typical of many engineering structures. The full-field measured data are highly redundant, but the application of image processing using functional transformation enables the extraction of a small number of shape features without any significant loss of information from the raw DIC data. Surface parameterization is applied to ‘flatten’ the 3D surface to form a 2D planar domain. An adaptive geometric moment descriptor (AGMD), defined on surface parametric space, is used to extract shape features from a series of full-field transient responses under pseudo-random excitation. Approximately 14 thousand data points of raw DIC measurement are represented by 20 shape features terms at each time step. Shape-descriptor frequency response functions (SD-FRFs) of the response field and the loading field are derived. The usual modal identification procedure is applied to determine the natural frequencies, damping factors and Eigen-shape-feature vectors from the SD-FRF. Natural frequencies and mode shapes from a finite element (FE) model are correlated with the experimental data using the cosine distance between the shape feature vectors with 20 terms.
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Acknowledgements
The authors wish to acknowledge the support of EU FP7 through project ADVISE (Advanced Dynamic Validations using Integrated Simulation and Experimentation); grant no. 218595
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© 2013 The Society for Experimental Mechanics, Inc.
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Mottershead, J.E., Wang, W., Siebert, T., Pipino, A. (2013). Shape-Descriptor Frequency Response Functions and Modal Analysis. In: Allemang, R., De Clerck, J., Niezrecki, C., Wicks, A. (eds) Special Topics in Structural Dynamics, Volume 6. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6546-1_47
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DOI: https://doi.org/10.1007/978-1-4614-6546-1_47
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