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:91
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
心情发布了新的文献求助10
1秒前
1秒前
1秒前
乐空思应助sunjinkang采纳,获得100
2秒前
科研通AI6.4应助mxy126354采纳,获得10
2秒前
2秒前
没得发布了新的文献求助10
3秒前
帅到被人打完成签到,获得积分10
3秒前
博修发布了新的文献求助30
3秒前
道尔顿分压关注了科研通微信公众号
5秒前
5秒前
monica发布了新的文献求助10
5秒前
5秒前
5秒前
Ukey发布了新的文献求助10
6秒前
拉瓦锡不爱化学完成签到,获得积分10
7秒前
传奇3应助TIWOSS采纳,获得10
7秒前
7秒前
8秒前
Easton完成签到,获得积分10
9秒前
chao完成签到,获得积分10
11秒前
我爱科研完成签到,获得积分10
12秒前
光亮的盼完成签到 ,获得积分10
13秒前
13秒前
小蘑菇应助leo采纳,获得10
13秒前
暖阳发布了新的文献求助10
14秒前
14秒前
15秒前
orixero应助博修采纳,获得10
15秒前
DW应助哈哈哈采纳,获得10
15秒前
一一完成签到 ,获得积分10
15秒前
15秒前
mxy126354发布了新的文献求助10
16秒前
Ukey完成签到,获得积分10
16秒前
璃鱼发布了新的文献求助10
16秒前
17秒前
JABBA完成签到,获得积分10
17秒前
17秒前
沈米米完成签到,获得积分10
17秒前
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764382
求助须知:如何正确求助?哪些是违规求助? 9308581
关于积分的说明 20306689
捐赠科研通 7348987
什么是DOI,文献DOI怎么找? 3314361
关于科研通互助平台的介绍 2463914
邀请新用户注册赠送积分活动 2328488