Systematic errors in digital image correlation due to undermatched subset shape functions

2002 ◽  
Vol 42 (3) ◽  
pp. 303-310 ◽  
Author(s):  
Hubert W. Schreier ◽  
Michael A. Sutton
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Systematic Errors ◽  
Image Correlation ◽  
Shape Functions

Development of the Shape Functions for Fatigue Test Using Digital Image Correlation

2013 ◽  
Vol 465-466 ◽  
pp. 862-866
Author(s):  
Khoo Sze Wei ◽  
Saravanan Karuppanan ◽  
Azmi Abdul Wahab
Keyword(s):  
Digital Image Correlation ◽  
Fatigue Test ◽  
Digital Image ◽  
Strain Measurement ◽  
Measurement Method ◽  
Measurement Methods ◽  
Image Correlation ◽  
Shape Functions ◽  
First Order ◽  
Advantages And Disadvantages

Mechanical failure of a structure or a machine during the regular working conditions are often related to the fatigue damage. As a consequence, the structural integrity monitoring of a system has always been a laborious task in the field of engineering. Since the strain measurement is one of the most important predictors of fatigue life, a precise strain measurement method is therefore required. There are many strain measurement methods in fatigue analysis; namely strain gauge, brittle coating method, photoelastic-coating and other optical strain measurement methods. However, various advantages and disadvantages have been found in each of the method mentioned above. Hence, there is always a need to develop a precise and yet informative strain measurement method in mechanical testing. The objective of this study is to develop the first-order shape functions for fatigue test using the Digital Image Correlation technique. In this study, sub-pixel accuracy image correlation algorithm was developed by using MATLAB whereby the positions of the points were precisely selected by using the fine-tuned function. As a result, the first-order shape functions were determined by retrieving the information that is stored in the affine transformation matrix. The works presented in this paper were mainly focused on the development of the algorithms, together with the results and the discussions for the validation exercises. In conclusion, a good agreement was achieved and the newly developed algorithm was proven to be accurate.

scholarly journals Testing System for the Mechanical Properties of Small-Scale Specimens Based on 3D Microscopic Digital Image Correlation

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3530
Author(s):  
Xu Liu ◽  
Rongsheng Lu
Keyword(s):  
Mechanical Properties ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Three Dimensional ◽  
Image Correlation ◽  
Field Strain ◽  
Small Scale ◽  
Testing System ◽  
Shape Functions ◽  
Full Field

The testing of the mechanical properties of materials on a small scale is difficult because of the small specimen size and the difficulty of measuring the full-field strain. To tackle this problem, a testing system for investigating the mechanical properties of small-scale specimens based on the three-dimensional (3D) microscopic digital image correlation (DIC) combined with a micro tensile machine is proposed. Firstly, the testing system is described in detail, including the design of the micro tensile machine and the 3D microscopic DIC method. Then, the effects of different shape functions on the matching accuracy obtained by the inverse compositional Gauss–Newton (IC-GN) algorithm are investigated and the numerical experiment results verify that the error due to under matched shape functions is far larger than that of overmatched shape functions. The reprojection error is shown to be smaller than before when employing the modified iteratively weighted radial alignment constraint method. Both displacement and uniaxial measurements were performed to demonstrate the 3D microscopic DIC method and the testing system built. The experimental results confirm that the testing system built can accurately measure the full-field strain and mechanical properties of small-scale specimens.

scholarly journals Author Correction: Modeling of systematic errors in stereo-digital image correlation due to camera self-heating

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Liping Yu ◽  
Gilles Lubineau
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Systematic Errors ◽  
Image Correlation ◽  
Self Heating ◽  
Stereo Digital Image Correlation

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Sign in / Sign up

Export Citation Format

Share Document