Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation

2007 ◽  
Vol 46 (3) ◽  
pp. 033601 ◽  
Author(s):  
Bing Pan
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Strain Measurement ◽  
Image Correlation ◽  
Field Strain ◽  
Two Dimensional ◽  
Full Field ◽  
Digital Differentiator

scholarly journals A Review of Surface Deformation and Strain Measurement Using Two-Dimensional Digital Image Correlation

2016 ◽  
Vol 23 (3) ◽  
pp. 461-480 ◽  
Author(s):  
Sze-Wei Khoo ◽  
Saravanan Karuppanan ◽  
Ching-Seong Tan
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Strain Measurement ◽  
Surface Deformation ◽  
Optical Measurement ◽  
Image Correlation ◽  
Two Dimensional ◽  
Full Field ◽  
Computation Efficiency ◽  
Dimensional Measurements

Abstract Among the full-field optical measurement methods, the Digital Image Correlation (DIC) is one of the techniques which has been given particular attention. Technically, the DIC technique refers to a non-contact strain measurement method that mathematically compares the grey intensity changes of the images captured at two different states: before and after deformation. The measurement can be performed by numerically calculating the displacement of speckles which are deposited on the top of object’s surface. In this paper, the Two-Dimensional Digital Image Correlation (2D-DIC) is presented and its fundamental concepts are discussed. Next, the development of the 2D-DIC algorithms in the past 33 years is reviewed systematically. The improvement of 2DDIC algorithms is presented with respect to two distinct aspects: their computation efficiency and measurement accuracy. Furthermore, analysis of the 2D-DIC accuracy is included, followed by a review of the DIC applications for two-dimensional measurements.

Full-Field Strain Measurement of Rotating Object Using Digital Image Correlation

2020 ◽  
Vol 40 (13) ◽  
pp. 1312005
Author(s):  
吴荣 Wu Rong ◽  
刘依 Liu Yi ◽  
周建民 Zhou Jianmin ◽  
张水强 Zhang Shuiqiang
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Strain Measurement ◽  
Image Correlation ◽  
Field Strain ◽  
Full Field

Full-field strain measurements at the micro-scale in fiber-reinforced composites using digital image correlation

2016 ◽  
Vol 140 ◽  
pp. 192-201 ◽  
Author(s):  
Mahoor Mehdikhani ◽  
Mohammadali Aravand ◽  
Baris Sabuncuoglu ◽  
Michaël G. Callens ◽  
Stepan V. Lomov ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Image Correlation ◽  
Fiber Reinforced Composites ◽  
Field Strain ◽  
Reinforced Composites ◽  
Fiber Reinforced ◽  
Full Field ◽  
Strain Measurements ◽  
Micro Scale

scholarly journals Robust Filtering Options for Higher-Order Strain Fields Generated by Digital Image Correlation

2020 ◽  
Vol 1 (4) ◽  
pp. 174-192
Author(s):  
Nedaa Amraish ◽  
Andreas Reisinger ◽  
Dieter H. Pahr
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Tensile Tests ◽  
Image Correlation ◽  
Field Strain ◽  
Strain Fields ◽  
Full Field ◽  
Low Pass ◽  
Discrete Measurement ◽  
Mean Filtering

Digital image correlation (DIC) systems have been used in many engineering fields to obtain surface full-field strain distribution. However, noise affects the accuracy and precision of the measurements due to many factors. The aim of this study was to find out how different filtering options; namely, simple mean filtering, Gaussian mean filtering and Gaussian low-pass filtering (LPF), reduce noise while maintaining the full-field information based on constant, linear and quadratic strain fields. Investigations are done in two steps. First, linear and quadratic strain fields with and without noise are simulated and projected to discrete measurement points which build up strain window sizes consisting of 6×5, 12×11, and 26×17 points. Optimal filter sizes are computed for each filter strategy, strain field type, and strain windows size, with minimal impairment of the signal information. Second, these filter sizes are used to filter full-field strain distributions of steel samples under tensile tests by using an ARAMIS DIC system to show their practical applicability. Results for the first part show that for a typical 12×11 strain window, simple mean filtering achieves an error reduction of 66–69%, Gaussian mean filtering of 72–75%, and Gaussian LPF of 66–69%. If optimized filters are used for DIC measurements on steel samples, the total strain error can be reduced from initial 240−300 μstrain to 100–150 μstrain. In conclusion, the noise-floor of DIC signals is considerable and the preferable filters were a simple mean with s*¯ = 2, a Gaussian mean with σ*¯ = 1.7, and a Gaussian LPF with D0*¯ = 2.5 in the examined cases.

Measurement of high temperature full-field strain up to 2000 °C using digital image correlation

2017 ◽  
Vol 28 (3) ◽  
pp. 035007 ◽  
Author(s):  
Wei Wang ◽  
Chenghai Xu ◽  
Hua Jin ◽  
Songhe Meng ◽  
Yumin Zhang ◽  
...  
Keyword(s):  
High Temperature ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Image Correlation ◽  
Field Strain ◽  
Full Field
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