In-Situ Systematic Error Correction for Digital Volume Correlation Using a Reference Sample

Wang, B.; Pan, B.; Lubineau, Gilles

In-Situ Systematic Error Correction for Digital Volume Correlation Using a Reference Sample

Type

Article

Authors

Wang, B.
Pan, B.
Lubineau, Gilles

KAUST Department

Composite and Heterogeneous Material Analysis and Simulation Laboratory (COHMAS)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division

Online Publication Date

2017-11-27

Print Publication Date

2018-03

Date

2017-11-27

Abstract

The self-heating effect of a laboratory X-ray computed tomography (CT) scanner causes slight change in its imaging geometry, which induces translation and dilatation (i.e., artificial displacement and strain) in reconstructed volume images recorded at different times. To realize high-accuracy internal full-field deformation measurements using digital volume correlation (DVC), these artificial displacements and strains associated with unstable CT imaging must be eliminated. In this work, an effective and easily implemented reference sample compensation (RSC) method is proposed for in-situ systematic error correction in DVC. The proposed method utilizes a stationary reference sample, which is placed beside the test sample to record the artificial displacement fields caused by the self-heating effect of CT scanners. The detected displacement fields are then fitted by a parametric polynomial model, which is used to remove the unwanted artificial deformations in the test sample. Rescan tests of a stationary sample and real uniaxial compression tests performed on copper foam specimens demonstrate the accuracy, efficacy, and practicality of the presented RSC method.

Citation

Wang B, Pan B, Lubineau G (2017) In-Situ Systematic Error Correction for Digital Volume Correlation Using a Reference Sample. Experimental Mechanics. Available: http://dx.doi.org/10.1007/s11340-017-0356-1.

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant nos. 11427802, and 11632010), the Aeronautical Science Foundation of China (2016ZD51034), the Beijing Nova Program (xx2014B034), and the Academic Excellence Foundation of BUAA for PhD Students. We also thank King Abdullah University of Science and Technology (KAUST) for its support.