Assisted defect detection by in-process monitoring of additive manufacturing using optical imaging and infrared thermography
Assisted defect detection by in-process monitoring of additive manufacturing using optical imaging and infrared thermography
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DOI：
10.1016/j.addma.2023.103483
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发表时间：
2023-03-14
影响因子：
11
通讯作者：
Gupta, Nikhil
中科院分区：
文献类型：
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作者：
AbouelNour, Youssef;Gupta, Nikhil
熔丝制造(FFF)3D打印中的分层在线监控有助于检测制造过程中引入的缺陷。在这项工作中，光学成像和红外(IR)热像仪同时用于检测埋入缺陷，如点缺陷和线缺陷。光学图像有助于识别必要的变量，这些变量可以通过图像相关性实现实时缺陷检测。通过温度监测和热像分析，与基线进行比对，完成缺陷检测。研究发现，随着试件中埋入缺陷数目的增加，试件的平均温度(T)高于试件(试件)。缺陷数量增加2倍和5倍，导致(T)比波纹(试件)增加，接近相对标准误差的18倍和37倍。全球平均热点温度(T)与样品中埋入缺陷的总数之间也存在正相关关系。这项研究表明，可以使用光学和热成像系统来完成现场缺陷检测。
Layer-wise in-process monitoring in Fused Filament Fabrication (FFF) 3D printing can facilitate the detection of defects introduced during manufacturing. In this work, optical imaging and infrared (IR) thermography were used simultaneously for the detection of embedded defects, such as point and line defects. The optical images helped in identifying the necessary variables that can lead to real-time defect detection through image correlation. Through temperature monitoring and thermal image analysis, defect detection was accomplished by comparing to a baseline. It was found that as the number of embedded defects increased in a specimen, the average specimen temperature, (T) over tilde (specimen), increased. An increase in the number of defects by 2X and 5X led to an increase in (T) over tilde (specimen) that is similar to 18X and 37X the relative standard error. There was also a positive correlation between the global average hotspot temperature, (T) over tilde (hotspot), and the total number of embedded defects in the specimen. This study demonstrates that in-situ defect detection can be accomplished using optical and thermal imaging systems.