Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors

Su, Yong; Zhang, Qingchuan; Xu, Xiaoyu; Gao, Zeren

doi:10.1016/j.optlaseng.2016.05.019

Cited by 102 publications

(44 citation statements)

References 75 publications

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“…Previous studies have shown that the elastic modulus of enamel is 40-80 GPa, while it is around 30 GPa in peritubular dentin and 16-21 GPa in inter-tubular dentin. It may be even lower (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19) GPa) in regions as close as 500 μm from the pulp [28,29]. Chan et al found that enamel had an elastic modulus of ∼95 GPa, whereas dentin had an elastic modulus of ∼19 GPa from nano-indentation tests [30].…”

Section: Discussionmentioning

confidence: 99%

“…In general, the speckle will be prefabricated on the specimen surface to enhance the intensity variance before stereo-DIC measurement. The randomly distributed speckle is essential for obtaining accurate and efficient deformations [13][14][15]. Previous fabrications of the speckle patterns on biological materials have been reported in the measurement of deformations of relatively rigid tissues, such as the cartilage and the hoof horn [5,16], or soft stiff tissues such as the arteries [17] and skins [18], or very soft tissues like the liver tissue [19].…”

Section: Introductionmentioning

confidence: 99%

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Measurement of biomechanical behavior of dentin hard tissue in response to unbound water loss using stereo-digital image correlation

Chen

Shao

2020

Mater. Res. Express

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Understanding the biomechanical behavior of dentin hard tissue with fluid-filled dentin tubules and hydrated matrices is essential for studying this functionally graded biological composite. The stereodigital image correlation technique with an adaptive high-magnification field of view (FOV) for fully hydrated biological tissue measurement was investigated. The adaptive magnification is controlled by the length of extension tubes. To determine both the unbound water loss induced and load-induced three-dimensional (3D) deformation of dentin hard tissue from a fully hydrated state to a nonhydrated condition, samples of dentin blocks and half teeth in sagittal sections were studied for a period of 2 h in situ over varied speckle patterns. The effects of speckles on water evaporation, camera pre-heating, and measurement accuracy in the wet, curved and long-term measurement were analyzed. The elastic modulus and Poisson's ratio of both dentin and pulp in response to unbound water evaporation were measured. With the unbound water loss, the mean values of the elastic modulus generally increased from ∼8 GPa to ∼10 GPa in pulp region and from ∼10 GPa to ∼12 GPa in dentin region. The mean values of the Poisson's ratio increased both in pulp and in dentin. Poisson's ratio in the dentin regions (∼0.3) were generally smaller than those in the pulp regions (even can reach 0.6), irrespective of the partial dehydration time. Further analysis of the full-field deformation results provided insight into the unbound water-induced regional deformations and mechanical changes in human dentin. It's found that the unbound water loss induced deformations were more prominent when compared to load induced deformations.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measurement of biomechanical behavior of dentin hard tissue in response to unbound water loss using stereo-digital image correlation

Chen

Shao

2020

Mater. Res. Express

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“…In addition, for the use of DIC, the cross-correlation calculation requires detailed information of randomly scattered speckles on the surfaces of studied objects. As such, when natural speckles are of insufficient utility, extra speckles can be artificially created by painting the targeted surfaces in either black or white [25].…”

Section: Working Principle Of the Dic Techniquementioning

confidence: 99%

Prediction of Fracture Damage of Sandstone Using Digital Image Correlation

et al. 2020

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Featured Application: A non-contact digital image correlation technique is used to predict sandstone failure. Failure strain for the tested sandstone is estimated to be around 0.004. Finite element analysis verifies the accuracy of prediction results based on experiments.Abstract: Investigation on the deformation mechanism of sandstone is crucial to understanding the life cycle patterns of pertinent infrastructure systems considering the extensive adoption of sandstone in infrastructure construction of various engineering systems, e.g., agricultural engineering systems. In this study, the state-of-the-art digital image correlation (DIC) method, which uses classical digital photography, is employed to explore the detailed failure course of sandstone with physical uniaxial compression tests. Four typical points are specifically selected to characterize the global strain field by plotting their corresponding strain-time relationship curves. Thus, the targeted failure thresholds are identified. The Hill-Tsai failure criterion and finite element simulation are then used for the cross-check process of DIC predictions. The results show that, though errors exist between the experimental and the theoretical values, overall, they are sufficiently low to be ignored, indicating good agreement. From the results, near-linear relationships between strain and time are detected before failure at the four chosen points and the failure strain thresholds are almost the same; as low as 0.004. Failure thresholds of sandstone are reliably determined according to the strain variation curve, to forecast sandstone damage and failure. Consequently, the proposed technology and associated information generated from this study could be of assistance in the safety and health monitoring processes of relevant infrastructure system applications.

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“…Yaofeng and Pang 72 held that choosing the optimal subset size requires a tradeoff between random errors and systematic errors. Remarkably, the selection of subset is closely related to the speckles' quality and the studies on speckles' quality assessment [73][74][75][76][77][78][79] provide a reference. Moreover, Xu et al 64 studied the effects of various shape functions on the selection of subset size.…”

Section: The Effect Of Subset Sizementioning

confidence: 99%

The state of the art of two‐dimensional digital image correlation computational method

Zhao

Sang

Duan

2019

Engineering Reports

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After remarkable work over the last three decades, digital image correlation (DIC) computational technique has made incredible progress under the unremitting efforts of numerous researchers, and it has already grown into one of the most powerful and nondestructive surface deformations measuring methods used in various areas of experimental mechanics. DIC is done by tracking the regional variation of gray‐scale features between two succession images recorded before and after deformation. The objective of this paper is to report on the development of 2D‐DIC. In this paper, we first describe the basic principle of the DIC algorithm. The second part mainly focuses on some important progress and interesting problems of the algorithm in the term of computational efficiency and measurement accuracy. Moreover, the major error sources that may exist in practical DIC measurement are discussed in detail. Finally, some typical application domains of DIC method are listed. This paper intends to help preliminary researchers who are of interest in 2D‐DIC algorithms to improve their understanding of this measurement technique.

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Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors

Cited by 102 publications

References 75 publications

Measurement of biomechanical behavior of dentin hard tissue in response to unbound water loss using stereo-digital image correlation

Measurement of biomechanical behavior of dentin hard tissue in response to unbound water loss using stereo-digital image correlation

Prediction of Fracture Damage of Sandstone Using Digital Image Correlation

The state of the art of two‐dimensional digital image correlation computational method

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