High accuracy digital image correlation powered by GPU-based parallel computing

Zhang, Lingqi; Wang, Tianyi; Jiang, Zhenyu; Kemao, Qian; Liu, Yiping; Liu, Zejia; Tang, Liqun; Dong, Shoubin

doi:10.1016/j.optlaseng.2015.01.012

Cited by 93 publications

(51 citation statements)

References 18 publications

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“…In this case, information about specimen deformation is given by motion analysis of a large number of points (speckle) spreading over the surface of the specimen gauge length [14,15]. A random speckle pattern is generated by a spraying black paint and a white base layer directly onto the surface of the specimen.…”

Section: Strain Measuring Accuracy With Splitting-beam Lasermentioning

confidence: 99%

Strain measuring accuracy with splitting-beam laser extensometer technique at split Hopkinson compression bar experiment

Panowicz¹,

Janiszewski²,

Traczyk³

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. An accuracy problem of strain measurement at compression split Hopkinson compression bar experiments with a splitting-beam laser extensometer was considered. The splitting-beam laser extensometer technique was developed by Nie et al. to measure strain of a specimen during its tension under a high strain rate loading condition. This novel concept was an inspiration for the authors to develop own laser extensometer system, which allows for simultaneous and independent measurement of displacement of bar ends between which a compressed material specimen is placed. In order to assess a metrological property of this measuring system, a wide range of high strain rate experiments were performed, including tests with various sample materials (Al 5251, Cu OFE) with different rate of strain, and with the use of two bars material. A high accuracy of the developed laser extensometer was found in measurement of specimen strain, for which uncertainty is not greater than 0.1% and, for a typical specimen dimension, the maximum permissible error is 4.5 μm.Key words: SHPB test, strain rates, non-contact strain measurement, laser extensometer. The simplest approach is to use a high speed digital camera to photograph the specimen deformation [10,11]. The camera is focused on the entire gauge section and part of the nongauge section at both ends to achieve a sufficient image with the highest resolution possible. Due to motion analysis of the selected characteristic points, defining the strain gage length, a strain-time relationship can be determined. However, due to the limited frame rate and its corresponding resolution of a contemporary high speed camera, the obtained results did not provide sufficient data points to construct a full stress-strain curve [8]. Strain measuring accuracy with splitting-beam laserThe high-rate digital image correlation (DIC) is a further development of the above described techniques [12,13]. In this case, information about specimen deformation is given by motion analysis of a large number of points (speckle) spreading over the surface of the specimen gauge length [14,15]. A random speckle pattern is generated by a spraying black paint and a white base layer directly onto the surface of the specimen. Thus, DIC provides highly valuable information on dynamic full-field strain measurements in the specimen, however, the above-mentioned limitations resulting from the usage of a contemporary high speed camera and an extreme difficulty in acquiring a large quantity of high-resolution images at very high frame rates do not allow for constructing a precise stressstrain curve [8].Another strain measuring technique is the interferometric-strain-gauge method, which is one of the first diagnostic techniques applied to straightforward non-contact measurement of specimen strain in SHPB testing. Sharpe et al. [16] used this method for evaluation of strain uniformity in the compressed specimen by comparison of surface strain at the specimen midpoint to the average strain calculated from the conventional Kolsk...

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Section: Strain Measuring Accuracy With Splitting-beam Lasermentioning

confidence: 99%

Strain measuring accuracy with splitting-beam laser extensometer technique at split Hopkinson compression bar experiment

Panowicz¹,

Janiszewski²,

Traczyk³

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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“…Due to high execution time, this measurement technique is primarily used as a post‐processing image analysis tool. Recent works in literature focus on DIC's performance improvement using graphics processing unit (GPU) (which comprises multiple in‐built processor cores [of the order of thousands] within a single IC). While a computation exhibiting high level of parallelism is expected to achieve good speedup on a GPU, parallelizing two‐dimensional DIC (2D‐DIC) on GPUs is not straightforward.…”

Section: Introductionmentioning

confidence: 99%

“…Due to its dependency in propagating

{boldp}^{'}

values between subsets, RGDT is not well‐suited for GPU‐assisted DIC. The FFT‐CC using GPU is a popular path‐independent approach used to estimate initial guess values at integer pixels. Even though recent works based on feature‐assisted method are proposed, they have limitations.…”

Section: Introductionmentioning

confidence: 99%

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High‐speed, two‐dimensional digital image correlation algorithm using heterogeneous (CPU‐GPU) framework

Thiagu

Subramanian²,

Nasre

2020

Strain

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Two-dimensional digital image correlation (2D-DIC) is an experimental technique used to measure in-plane displacement of a test specimen. Real-time measurement of full-field displacement data is challenging due to enormous computational load of the algorithm. In order to improve the computational speed, the focus of recent research works has been on the approach of parallelization across subsets within image pairs using graphics processing unit (GPU). But alternate GPU-based parallelization approaches to improve the performance of this algorithm as per the order of data processing have not been explored.To address this research gap, our method utilizes parallelism within a subset as well as across subsets for each computation step in an iteration cycle. A heterogeneous (CPU-GPU) framework in combination with a pyramid-based initial values estimation for subsets (in parallel) is proposed in this work. The precompute steps of the proposed framework are implemented using CPU, whereas the main iterative steps are realized using GPU. It is demonstrated that the overall computational speed of the proposed heterogeneous framework improves by ≈ 9× compared to a sequential CPU-based implementation for a pair of gray-scale images with a resolution of 588 × 2, 048 pixels. As an important milestone, feasibility to measure deformations in real time (≤1 s) is manifested in this study.

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“…Elimination of pathdependency allows the application of parallel computing technology to the proposed DIC method. It was found that the parallel computing-powered DIC (paDIC) method, implemented on NVIDIA compute unified device architecture (CUDA) for graphics processing unit (GPU) devices, can reach a speedup of nearly two orders of magnitude without sacrificing high accuracy and precision [18].…”

Section: Introductionmentioning

confidence: 99%

GPU Accelerated Digital Volume Correlation

et al. 2015

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A sub-voxel digital volume correlation (DVC) method combining the 3D inverse compositional GaussNewton (ICGN) algorithm with the 3D fast Fourier transform-based cross correlation (FFT-CC) algorithm is proposed to eliminate path-dependence in current iterative DVC methods caused by the initial guess transfer scheme. The proposed path-independent DVC method is implemented on NVIDIA compute unified device architecture (CUDA) for GPU devices. Powered by parallel computing technology, the proposed DVC method achieves a significant improvement in computation speed on a common desktop computer equipped with a low-end graphics card containing 1536 CUDA cores, i.e., up to 23.3 times faster than the sequential implementation and 3.7 times faster than the multithreaded implementation of the same DVC method running on a 6-core CPU. This speedup, which has no compromise with resolution, accuracy and precision, benefits from the coarsegrained parallelism that the points of interest (POIs) are processed simultaneously and also from the fine-grained parallelism that the calculation at each POI is performed with multiple threads in GPU. The experimental study demonstrates the superiority of the GPU-based parallel computing for acceleration of DVC over the multi-core CPU-based one, in particular on a PC level computer.

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High accuracy digital image correlation powered by GPU-based parallel computing

Cited by 93 publications

References 18 publications

Strain measuring accuracy with splitting-beam laser extensometer technique at split Hopkinson compression bar experiment

Strain measuring accuracy with splitting-beam laser extensometer technique at split Hopkinson compression bar experiment

High‐speed, two‐dimensional digital image correlation algorithm using heterogeneous (CPU‐GPU) framework

GPU Accelerated Digital Volume Correlation

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