GPU-based digital image correlation system for real-time strain-controlled fatigue and strain field measurement

This article reports a novel GPU-based 2D digital image correlation system (2D-DIC) overcoming two major limitations of this technique: It measures marker-free, i.e. without sample preparation, and the sampling rate meets the recommendations of ASTM E606. The GPU implementation enables zero-normalized cross correlation (ZNCC) calculation rates of up to 25 kHz for 256 × 256 pixel ROIs. This high-speed image processing system is combined with a high-resolution telecentric lens observing a 10 mm field-of-view, coaxial LED illumination, and a camera acquiring 2040 × 256 pixel images with 1.2 kHz. The optics resolve the microstructure of the surface even of polished cylindrical steel specimen. The displacement uncertainty is below 0.5 μm and the reproducibility in zero-strain tests approximately 10-5 (1 σ) of the field-of-view. For strain-controlled testing, a minimum of two displacement subsets per image are evaluated for average strain with a sampling rate of 1.2 kHz. Similar to mechanical extensometers, an analogue 0-10V displacement signal serves as a feedback for standard PID controllers. The average latency is below 2 ms allowing for cycle frequencies up to 10 Hz. For strain-field measurement, the number of ROIs limits the frame rate, e.g., the correlation rate of 25 kHz is sufficient to evaluate 10 images per second with 2500 ROIs each. This frame rate is still sufficient to compare the maximum and minimum strain fields within a cycle in real-time, e.g. for crack detection. The result is a marker-free and non-contact DIC sensor suitable for both strain-controlled fatigue testing and real-time full-field strain evaluation.

[1]  Dwayne Arola,et al.  Characterization of the strain-life fatigue properties of thin sheet metal using an optical extensometer , 2014 .

[2]  John Lambros,et al.  Ultraviolet digital image correlation (UV-DIC) for high temperature applications. , 2014, The Review of scientific instruments.

[3]  Ákos Zarándy,et al.  Focal-Plane Sensor-Processor Chips , 2014 .

[4]  Long Tian,et al.  Superfast robust digital image correlation analysis with parallel computing , 2015 .

[5]  Armand Joseph Beaudoin,et al.  Strain rate jump induced negative strain rate sensitivity (NSRS) in aluminum alloy 2024: Experiments and constitutive modeling , 2017 .

[6]  Yong Xia,et al.  High-temperature digital image correlation method for full-field deformation measurement at 1200 °C , 2010 .

[7]  Zhenyu Jiang,et al.  High accuracy digital image correlation powered by GPU-based parallel computing , 2015 .

[8]  J. Goodman Introduction to Fourier optics , 1969 .

[9]  Markus G. R. Sause,et al.  Digital Image Correlation , 2016 .

[10]  H. Unbehauen,et al.  Regelungs- und Steuerungstechnik , 2012 .

[11]  Yoshiharu Mutoh,et al.  Low cycle fatigue test for solders using non-contact digital image measurement system , 2002 .

[12]  Gregory E. Chamitoff,et al.  Orders-of-magnitude performance increases in GPU-accelerated correlation of images from the International Space Station , 2010, Journal of Real-Time Image Processing.

[13]  M. Kawakubo,et al.  Mean stress effect on fatigue strength of stainless steel , 2015 .

[14]  M. Higham,et al.  Application of strain-controlled fatigue testing methods to polymer matrix composites , 2016 .

[15]  Christoph Schweizer,et al.  Characterization of fatigue crack growth, damage mechanisms and damage evolution of the nickel-based superalloys MAR-M247 CC (HIP) and CM-247 LC under thermomechanical fatigue loading using in situ optical microscopy , 2017 .

[16]  Horst Czichos,et al.  HÜTTE - Das Ingenieurwissen , 2004 .

[17]  Ronald Tetzlaff,et al.  The full penetration hole as a stochastic process: controlling penetration depth in keyhole laser-welding processes , 2012 .

[18]  Hock Soon Seah,et al.  A flexible heterogeneous real-time digital image correlation system , 2018, Optics and Lasers in Engineering.

[19]  Michael A. Sutton,et al.  The effect of out-of-plane motion on 2D and 3D digital image correlation measurements , 2008 .

[20]  Long Tian,et al.  Advanced video extensometer for non-contact, real-time, high-accuracy strain measurement. , 2016, Optics express.

[21]  A. Blug,et al.  Real-Time GPU-Based Digital Image Correlation Sensor for Marker-Free Strain-Controlled Fatigue Testing , 2019, Applied Sciences.

[22]  Bård Nyhus,et al.  Experimental and numerical investigation of strain distribution of notched lead fatigue test specimen , 2018 .

[23]  Ronald Tetzlaff,et al.  Real-Time Control of Laser Beam Welding Processes: Reality , 2011 .

[24]  Anand Asundi,et al.  Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review , 2009 .