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Digital Image Correlation Technique as a Tool for Kinematics Assessment of Structural Components Cover

Digital Image Correlation Technique as a Tool for Kinematics Assessment of Structural Components

Open Access
|Jul 2018

References

  1. 1. Baqersada J., Carra J., Lundstroma T., Niezrecki Ch., Avitabilea P., Slattery M., (2012), Dynamic characteristics of a wind turbine blade using 3D digital image correlation, Health Monitoring of Structural and Biological Systems 2012, edited by Tribikram Kundu, Proc. of SPIE, 8348.10.1117/12.915377
  2. 2. Berger H., Klein M., Lambert F., Levadoux B., (2010), Optical Vibration Measurement and Frequency Response Analysis on Large Structures under Multiple Excitation Load Conditions, Proceedings of ISMA2010 including USD2010, 1693–1702.
  3. 3. Bornert M., Brémand F., Doumalin P., Dupré J.-C., Fazzini M., Grédiac M., Hild F., Mistou S., Molimard J., Orteu J.-J., Robert L., Surrel Y., Vacher P., Wattrisse B., (2009), Assessment of Digital Image Correlation Measurement Errors: Methodology and Results, Experimental Mechanics, 49, 353–370.10.1007/s11340-008-9204-7
  4. 4. Brinkmann Ch., Haberland J., Böttinger S., Erne O., Sanow G., (2007), Optical 3D Measuring System for Investigating Tyre Deformations, Tractor Technology, 62(5), 326–327.
  5. 5. Chu T.C., Ranson W.F., Sutton M.A., Peters W.H., (1985), Applications of digital-image-correlation techniques to experimental mechanics, Experimental Mechanics, 232–244.10.1007/BF02325092
  6. 6. Creager C., Johnson K., Plant M., Moreland S., Skonieczny K., (2015), Push–pull locomotion for vehicle extrication, Journal of Terramechanics, 57, 71–80.10.1016/j.jterra.2014.12.001
  7. 7. Gower M.R., Shaw R.M., (2006), Towards a planar cruciform specimen for biaxial characterization of polymer matrix composites, Applied Mechanics and Materials, 24–25, 115–120.10.4028/www.scientific.net/AMM.24-25.115
  8. 8. Kamaya M., Kawakubo M., (2011), A procedure for determining the true stress–strain curve over a large range of strains using digital image correlation and finite element analysis, Mechanics of Materials, 43, 243–253.10.1016/j.mechmat.2011.02.007
  9. 9. Long X., Fu S., Qi Z., Yang X., Yu Q., (2012), Digital image correlation using stochastic parallel-gradient-descent algorithm, Experimental Mechanics, DOI 10.1007/s11340-012-9667-4.10.1007/s11340-012-9667-4
  10. 10. Szymczak T., Kowalewski Z.L., Brodecki A., (2016a), Determination of artificial defects in material under monotonic tension by the use of FEM and DIC methods, Materials Today: Proceedings, 3, 1171–1176.10.1016/j.matpr.2016.03.011
  11. 11. Szymczak T., Kowalewski Z.L., Brodecki A., (2016b), Digital Image Correlation method for investigations of materials and engineering structures, Technical Suspervision (Dozór Techniczny), 4, 22–3 (in Polish).
  12. 12. Toussaint F., Tabourot I., Vacher P., (2008), Experimental study with a Digital Image Correlation (DIC) method and numerical simulation of an anisotropic elastic-plastic commercially pure titanium, Archives of Civil and Mechanical Engineering, VIII, 3, 131–143.10.1016/S1644-9665(12)60168-X
  13. 13. Regulation No 55 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of mechanical coupling components of combinations of vehicles, 28.08.2010.
  14. 14. www.gom.com
DOI: https://doi.org/10.2478/ama-2018-0016 | Journal eISSN: 2300-5319 | Journal ISSN: 1898-4088
Language: English
Page range: 101 - 104
Submitted on: May 24, 2017
Accepted on: May 30, 2018
Published on: Jul 17, 2018
Published by: Bialystok University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Adam Brodecki, Tadeusz Szymczak, Zbigniew Kowalewski, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.