数字图像相关
微尺度化学
材料科学
数字图像
流离失所(心理学)
计算机科学
机械工程
结构工程
工程类
计算机视觉
图像处理
图像(数学)
复合材料
数学
心理治疗师
数学教育
心理学
作者
J.A. HEBERT,M. M. Khonsari
摘要
Abstract In recent years, the use of digital image correlation (DIC) in fatigue experiments has become widespread. It is estimated that ~1000 published works exist that outline fatigue experiments in which DIC is employed for displacement and strain measurement. Of these, ~900 were published in the last 10 years. DIC is a noncontact method that uses a series of digital images to calculate full‐field strains on the surface of an object, planer or curved. Typical commercial DIC systems compute strains at resolutions high enough to trace hysteresis loops in metals. Properly operated open‐source systems can do the same. The DIC method is applied not only on optically based digital images but also on digital images from ultra‐high resolution (ultra‐HR) microscopes like a scanning electron microscope (SEM) or on volumetric images from computed tomography (CT) scans. In fatigue analysis, DIC provides much more information than that of an extensometer. Full‐field strains from DIC can be acquired at different scales (i.e., microscale, macroscale, and nanoscale) and can be related to items such as microstructural features, interacting surfaces (e.g., fretting), fatigue crack growth phenomenon, and distinct forms of energy. Because fatigue is a highly complex, strain‐induced process, the DIC method is and will be an important tool for current and future research in fatigue. This review begins with an overview of the history and fundamentals of DIC including an evaluation of the overall performance and accuracy of the method. Publications selected for review are then presented and discussed. Remarks about the present state‐of‐the‐art and an outlook for future work to be done are then provided.
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