Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation

2129 Views
2320 Downloads
Export citation: ABNT
WANG, Dezhi ;MOTTERSHEAD, John E..
Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 62, n.7-8, p. 419-429, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/>. Date accessed: 19 apr. 2024. 
doi:http://dx.doi.org/10.5545/sv-jme.2016.3736.
Wang, D., & Mottershead, J.
(2016).
Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation.
Strojniški vestnik - Journal of Mechanical Engineering, 62(7-8), 419-429.
doi:http://dx.doi.org/10.5545/sv-jme.2016.3736
@article{sv-jmesv-jme.2016.3736,
	author = {Dezhi  Wang and John E. Mottershead},
	title = {Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {62},
	number = {7-8},
	year = {2016},
	keywords = {digital image correlation; Kriging regression; measurement precision; spatial resolution},
	abstract = {The performance of a new global Digital Image Correlation (DIC) approach known as Kriging DIC is assessed by comparison with the classical subset-based DIC through a standard evaluation procedure. This procedure employs synthetic images with imposed planar sinusoidal displacement fields of various spatial frequencies to quantify both the displacement measurement precision and the spatial resolution of DIC algorithms. The displacement precision and spatial resolution are re-defined in terms of two measures of discrepancy that have not been used before but are considered to give a better comparative assessment than was previously possible. The results are presented in graphical form to finally produce an evaluation of the relative performance of the different DIC approaches. These show that the Kriging DIC approach is robust to the measurement noise and has superior performance to the classical subset-based DIC in terms of both displacement measurement precision and spatial resolution. Furthermore, it is found that the best results are obtained when the discrepancy is measured in the normal direction, as opposed to the Y-direction for the quantification DIC performance.},
	issn = {0039-2480},	pages = {419-429},	doi = {10.5545/sv-jme.2016.3736},
	url = {https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/}
}
Wang, D.,Mottershead, J.
2016 June 62. Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 62:7-8
%A Wang, Dezhi 
%A Mottershead, John E.
%D 2016
%T Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation
%B 2016
%9 digital image correlation; Kriging regression; measurement precision; spatial resolution
%! Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation
%K digital image correlation; Kriging regression; measurement precision; spatial resolution
%X The performance of a new global Digital Image Correlation (DIC) approach known as Kriging DIC is assessed by comparison with the classical subset-based DIC through a standard evaluation procedure. This procedure employs synthetic images with imposed planar sinusoidal displacement fields of various spatial frequencies to quantify both the displacement measurement precision and the spatial resolution of DIC algorithms. The displacement precision and spatial resolution are re-defined in terms of two measures of discrepancy that have not been used before but are considered to give a better comparative assessment than was previously possible. The results are presented in graphical form to finally produce an evaluation of the relative performance of the different DIC approaches. These show that the Kriging DIC approach is robust to the measurement noise and has superior performance to the classical subset-based DIC in terms of both displacement measurement precision and spatial resolution. Furthermore, it is found that the best results are obtained when the discrepancy is measured in the normal direction, as opposed to the Y-direction for the quantification DIC performance.
%U https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/
%0 Journal Article
%R 10.5545/sv-jme.2016.3736
%& 419
%P 11
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 62
%N 7-8
%@ 0039-2480
%8 2018-06-27
%7 2018-06-27
Wang, Dezhi, & John E. Mottershead.
"Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation." Strojniški vestnik - Journal of Mechanical Engineering [Online], 62.7-8 (2016): 419-429. Web.  19 Apr. 2024
TY  - JOUR
AU  - Wang, Dezhi 
AU  - Mottershead, John E.
PY  - 2016
TI  - Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2016.3736
KW  - digital image correlation; Kriging regression; measurement precision; spatial resolution
N2  - The performance of a new global Digital Image Correlation (DIC) approach known as Kriging DIC is assessed by comparison with the classical subset-based DIC through a standard evaluation procedure. This procedure employs synthetic images with imposed planar sinusoidal displacement fields of various spatial frequencies to quantify both the displacement measurement precision and the spatial resolution of DIC algorithms. The displacement precision and spatial resolution are re-defined in terms of two measures of discrepancy that have not been used before but are considered to give a better comparative assessment than was previously possible. The results are presented in graphical form to finally produce an evaluation of the relative performance of the different DIC approaches. These show that the Kriging DIC approach is robust to the measurement noise and has superior performance to the classical subset-based DIC in terms of both displacement measurement precision and spatial resolution. Furthermore, it is found that the best results are obtained when the discrepancy is measured in the normal direction, as opposed to the Y-direction for the quantification DIC performance.
UR  - https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/
@article{{sv-jme}{sv-jme.2016.3736},
	author = {Wang, D., Mottershead, J.},
	title = {Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {62},
	number = {7-8},
	year = {2016},
	doi = {10.5545/sv-jme.2016.3736},
	url = {https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/}
}
TY  - JOUR
AU  - Wang, Dezhi 
AU  - Mottershead, John E.
PY  - 2018/06/27
TI  - Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 62, No 7-8 (2016): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2016.3736
KW  - digital image correlation, Kriging regression, measurement precision, spatial resolution
N2  - The performance of a new global Digital Image Correlation (DIC) approach known as Kriging DIC is assessed by comparison with the classical subset-based DIC through a standard evaluation procedure. This procedure employs synthetic images with imposed planar sinusoidal displacement fields of various spatial frequencies to quantify both the displacement measurement precision and the spatial resolution of DIC algorithms. The displacement precision and spatial resolution are re-defined in terms of two measures of discrepancy that have not been used before but are considered to give a better comparative assessment than was previously possible. The results are presented in graphical form to finally produce an evaluation of the relative performance of the different DIC approaches. These show that the Kriging DIC approach is robust to the measurement noise and has superior performance to the classical subset-based DIC in terms of both displacement measurement precision and spatial resolution. Furthermore, it is found that the best results are obtained when the discrepancy is measured in the normal direction, as opposed to the Y-direction for the quantification DIC performance.
UR  - https://www.sv-jme.eu/article/measurement-precision-and-spatial-resolution-with-kriging-digital-image-correlation/
Wang, Dezhi, AND Mottershead, John.
"Measurement Precision and Spatial Resolution with Kriging Digital Image Correlation" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 62 Number 7-8 (27 June 2018)

Authors

Affiliations

  • University of Liverpool, Centre for Engineering Dynamics, Liverpool, UK 1
  • University of Liverpool, Institute for Risk and Uncertainty, Liverpool, UK 2

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 62(2016)7-8, 419-429
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.

https://doi.org/10.5545/sv-jme.2016.3736

The performance of a new global Digital Image Correlation (DIC) approach known as Kriging DIC is assessed by comparison with the classical subset-based DIC through a standard evaluation procedure. This procedure employs synthetic images with imposed planar sinusoidal displacement fields of various spatial frequencies to quantify both the displacement measurement precision and the spatial resolution of DIC algorithms. The displacement precision and spatial resolution are re-defined in terms of two measures of discrepancy that have not been used before but are considered to give a better comparative assessment than was previously possible. The results are presented in graphical form to finally produce an evaluation of the relative performance of the different DIC approaches. These show that the Kriging DIC approach is robust to the measurement noise and has superior performance to the classical subset-based DIC in terms of both displacement measurement precision and spatial resolution. Furthermore, it is found that the best results are obtained when the discrepancy is measured in the normal direction, as opposed to the Y-direction for the quantification DIC performance.

digital image correlation; Kriging regression; measurement precision; spatial resolution