The application of digital image correlation (DIC) in fatigue experimentation: A review

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
出处
期刊:Fatigue & Fracture of Engineering Materials & Structures [Wiley]
卷期号:46 (4): 1256-1299 被引量:75
标识
DOI:10.1111/ffe.13931
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
科研通AI6.4应助tian采纳,获得30
1秒前
高高行云完成签到,获得积分10
1秒前
Orange应助当当当采纳,获得10
1秒前
1秒前
123发布了新的文献求助10
1秒前
2秒前
2秒前
朴素的曼荷完成签到 ,获得积分10
2秒前
Ann发布了新的文献求助10
2秒前
111关闭了111文献求助
3秒前
十年负一生完成签到,获得积分10
3秒前
蜗牛完成签到,获得积分10
3秒前
Jobs应助阿辉采纳,获得10
3秒前
小牛发布了新的文献求助10
3秒前
3秒前
缥缈诗柳发布了新的文献求助10
4秒前
caiwenwen发布了新的文献求助10
4秒前
hfhfhf完成签到,获得积分10
4秒前
4秒前
qy发布了新的文献求助10
5秒前
5秒前
乔科利发布了新的文献求助20
5秒前
呵呵完成签到,获得积分10
6秒前
不想读研发布了新的文献求助10
6秒前
6秒前
美梦成真福禄寿完成签到 ,获得积分10
7秒前
汪金发布了新的文献求助10
7秒前
溪风发布了新的文献求助20
7秒前
hfhfhf发布了新的文献求助10
8秒前
你不懂完成签到,获得积分10
8秒前
luyang发布了新的文献求助20
9秒前
neversay4ever发布了新的文献求助10
9秒前
烙饼发布了新的文献求助10
9秒前
幸识完成签到 ,获得积分10
10秒前
totoro完成签到,获得积分10
10秒前
Xulyun完成签到 ,获得积分10
10秒前
Yon完成签到,获得积分10
10秒前
10秒前
10秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
Burger's Medicinal Chemistry and Drug Discovery 400
A Step-by-Step Guide to Qualitative Data Coding 2nd Edition 400
Impact of Storage Orientation and Duration on Prefilled Syringe Performance: Break-Loose and Glide Forces, and Injection Time Across Multiple Time Points 360
Programming for Chemical Engineers Using C, C++, and MATLAB 300
Upland Kenya wild flowers and ferns: a flora of the flowers, ferns, grasses, and sedges of highland Kenya 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6666440
求助须知:如何正确求助?哪些是违规求助? 8416039
关于积分的说明 17990260
捐赠科研通 5873263
什么是DOI,文献DOI怎么找? 2976175
邀请新用户注册赠送积分活动 1952008
关于科研通互助平台的介绍 1879300