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 Application of digital image correlation at the microscale in fiber-reinforced composites

2012 ◽  
Vol 43 (10) ◽  
pp. 1630-1638 ◽  
Author(s):  
L.P. Canal ◽  
C. González ◽  
J.M. Molina-Aldareguía ◽  
J. Segurado ◽  
J. LLorca
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Image Correlation ◽  
Fiber Reinforced Composites ◽  
Reinforced Composites ◽  
Fiber Reinforced

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

Measurement of full-field strain incell phone dropping test by high-speed 3D digital image correlation method

2018 ◽  
Vol 26 (9) ◽  
pp. 2174-2180
Author(s):  
王立忠 WANG Li-zhong ◽  
汪 耀 WANG Yao ◽  
梁 晋 LIANG Jin ◽  
戴晨光 DAI Chen-guang
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
High Speed ◽  
Correlation Method ◽  
Image Correlation ◽  
Field Strain ◽  
Digital Image Correlation Method ◽  
Full Field ◽  
3D Digital Image Correlation

scholarly journals A Method for Calibrating a Digital Image Correlation System for Full-Field Strain Measurements during Large Deformations

2019 ◽  
Vol 9 (14) ◽  
pp. 2828 ◽  
Author(s):  
Robert Blenkinsopp ◽  
Jon Roberts ◽  
Andy Harland ◽  
Paul Sherratt ◽  
Paul Smith ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Large Deformations ◽  
Speckle Pattern ◽  
Field Measurements ◽  
Image Correlation ◽  
Field Strain ◽  
Full Field ◽  
Error Distributions ◽  
Multiple Deformation

Numerous variables can introduce errors into the measurement chain of a digital image correlation (DIC) system. These can be grouped into two categories: measurement quality and the correlation principle. Although previous studies have attempted to investigate each error source in isolation, there are still no comprehensive, standardized procedures for calibrating DIC systems for full-field strain measurement. The aim of this study, therefore, was to develop an applied experimental method that would enable a DIC practitioner to perform a traceable full-field measurement calibration to evaluate the accuracy of a particular system setup in a real-world environment related to their specific application. A sequence of Speckle Pattern Boards (SPB) that included artificial deformations of the speckle pattern were created, allowing for the calibration of in-plane deformations. Multiple deformation stages (from 10% to 50%) were created and measured using the GOM ARAMIS system; the results were analysed and statistical techniques were used to determine the accuracy. The measured strain was found to be slightly over-estimated (nominally by 0.02%), with a typical measurement error range of 0.34% strain at a 95% confidence interval. Location within the measurement volume did not have a significant effect on error distributions. It was concluded that the methods developed could be used to calibrate a DIC system in-situ for full-field measurements of large deformations. The approach could also be used to benchmark different DIC systems against each other or allow operators to better understand the influence of particular measurement variables on the measurement accuracy.

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