Fast and high-resolution laser-ultrasonic imaging for visualizing subsurface defects in additive manufacturing components

材料科学 光栅扫描 超声波传感器 激光器 可视化 光学 制作 光栅图形 声学 超声波检测 计算机科学 人工智能 医学 物理 病理 替代医学
作者
Gaolong Lv,Zhijun Yao,Dan Chen,Yehai Li,Huanqing Cao,Anmin Yin,Yanjun Liu,Shifeng Guo
出处
期刊:Materials & Design [Elsevier]
卷期号:225: 111454-111454 被引量:27
标识
DOI:10.1016/j.matdes.2022.111454
摘要

Additive manufacturing (AM) is an emerging technique for efficient fabrication of individually tailored and complex geometry parts. The fabrication process is prone to induce various defects that can have detrimental effects on the AM components. Therefore, a reliable technique that enables monitoring the integrity of AM components and in return helping to optimize the fabrication parameters in mission-critical structures is highly demanded. This work presents a fast and high-resolution damage visualization method using laser-ultrasonic (LU) imaging technique for accurately detecting and quantifying the subsurface defects in printed AM components. Specifically, a fully noncontact LU scanning system is implemented to generate and detect high signal-to-noise ratio laser ultrasonic waves using a pulsed laser and laser Doppler vibrometer, respectively. A strategy for fast defect localization using Rayleigh waves with circular scans is firstly proposed. The high-resolution 3D synthetic aperture focusing technique (SAFT) imaging with raster scans is subsequently performed focusing around the located damage areas to stereoscopically visualize and quantify the subsurface defects. The reconstructed images are further processed and improved using Gaussian filter algorithm to obtain accurate defect shapes, sizes, and positions. The feasibility of the proposed method is eventually verified on AlSi10Mg and stainless steel (316L) components containing subsurface defects with various types and dimensions. The measured sizes are well consistent with the designed values, suggesting that it is a reliable inspection method for AM parts to ensure quality control and feedback.

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
墨琼琼应助科研通管家采纳,获得10
刚刚
酷波er应助科研通管家采纳,获得10
刚刚
刚刚
科目三应助lmr采纳,获得10
刚刚
刚刚
情怀应助科研通管家采纳,获得10
1秒前
1秒前
深情安青应助科研通管家采纳,获得10
1秒前
爆米花应助科研通管家采纳,获得10
1秒前
量子星尘发布了新的文献求助10
1秒前
小蘑菇应助科研通管家采纳,获得10
1秒前
科研通AI2S应助科研通管家采纳,获得10
1秒前
1秒前
成就的咖啡完成签到,获得积分10
1秒前
1秒前
1秒前
在水一方应助科研通管家采纳,获得10
2秒前
情怀应助科研通管家采纳,获得10
2秒前
2秒前
科研通AI6应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
深情安青应助科研通管家采纳,获得30
2秒前
2秒前
HLS应助科研通管家采纳,获得10
3秒前
zhonglv7应助科研通管家采纳,获得10
3秒前
lizishu应助1212采纳,获得20
3秒前
杨杨应助科研通管家采纳,获得10
3秒前
天天快乐应助科研通管家采纳,获得10
3秒前
墨琼琼应助科研通管家采纳,获得10
3秒前
俏皮晓曼完成签到,获得积分10
3秒前
酷波er应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
3秒前
情怀应助科研通管家采纳,获得10
3秒前
在水一方应助科研通管家采纳,获得10
3秒前
3秒前
深情安青应助科研通管家采纳,获得10
3秒前
爆米花应助科研通管家采纳,获得10
3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
Encyclopedia of Forensic and Legal Medicine Third Edition 5000
Introduction to strong mixing conditions volume 1-3 5000
Aerospace Engineering Education During the First Century of Flight 3000
Agyptische Geschichte der 21.30. Dynastie 3000
Les Mantodea de guyane 2000
从k到英国情人 1700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5776350
求助须知:如何正确求助?哪些是违规求助? 5628713
关于积分的说明 15442059
捐赠科研通 4908468
什么是DOI,文献DOI怎么找? 2641217
邀请新用户注册赠送积分活动 1589167
关于科研通互助平台的介绍 1543851