Abstract
This work proposes an alternative procedure to smooth and differentiate experimental full-field displacement measurements to get strain fields. This one, the penalized least squares method, relies on the balance between the fidelity to original raw data and the smoothness of the reconstructed ones. To characterize its performance, a comparative study between this algorithm and two other commonly implemented strategies (the ‘diffuse approximation’ and the Savitzky-Golay filter) is achieved. The results obtained by the penalized least squares method are comparable in terms of quality of the reconstruction to those produced by the two other algorithms, while the proposed technique is the fastest as its computation time is totally independent from the asked amount of smoothing. Moreover, unlike both other considered methods, it is possible with this technique to perform the derivation to obtain strain maps before smoothing them (while the smoothing is normally applied to displacement maps before the differentiation) which can lead in some cases to a more effective reconstruction of the strain fields.
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Acknowledgments
The authors would like to thank Pr. Paul Eilers for some useful exchanges on the principles and developments of the penalized least squares algorithm. They also would like to thank Dr. Marco Rossi for providing the 2D Savitzky-Golay algorithm used in this study. Finally, they would like to thank their colleagues at Arts et Métiers ParisTech (especially, Mr. Alain Prévot, Ms. Virginie Jamar and Mr. Jeremy Blanks) for their help at different stages of the work.
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Moulart, R., Rotinat, R. (2016). Evaluation of the Penalized Least Squares Method for Strain Computation. In: Sciammarella, C., Considine, J., Gloeckner, P. (eds) Experimental and Applied Mechanics, Volume 4. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-22449-7_5
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DOI: https://doi.org/10.1007/978-3-319-22449-7_5
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