基于多传感器和深度学习的al6000合金激光堆焊凝固裂纹识别

IF 1.7 4区 工程技术 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY
Jeonghun Shin, Sanghoon Kang, Cheolhee Kim, Sukjoon Hong, Minjung Kang
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引用次数: 0

摘要

凝固裂纹是Al - 6000合金激光焊接中最严重的焊接缺陷之一,它发生在凝固的最后阶段,由于焊缝金属的收缩而导致接头的强度和完整性下降。填充金属可以控制焊缝金属的化学成分,从而减轻凝固开裂。然而,在自激光焊接中,化学成分是难以控制的。由于焊缝形貌是影响凝固裂纹萌生和扩展的因素之一,因此引入了时空激光束调制来控制自激光焊接中的凝固裂纹。凝固裂纹在焊头表面产生热不连续和视觉缺陷。采用高速红外相机和同轴电荷耦合器件相机及辅助照明激光器(808 nm)对激光焊接过程中的凝固裂纹进行了识别。深度学习模型利用两张固化磁珠的传感器图像开发,提供了裂缝形成的位置信息。基于多传感器的卷积神经网络模型在预测裂纹位置方面达到了令人印象深刻的99.31%的准确率。因此,应用深度学习模型扩展了预测凝固裂纹的能力,包括以前无法检测到的内部裂纹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of solidification cracking using multiple sensors and deep learning in laser overlap welded Al 6000 alloy
Solidification cracking, one of the most critical weld defects in laser welding of Al 6000 alloys, occurs at the final stage of solidification owing to shrinkage of the weld metal and deteriorates the joint strength and integrity. The filler metal can control the chemical composition of the weld metal, which mitigates solidification cracking. However, the chemical composition is difficult to control in autogenous laser welding. Temporal and spatial laser beam modulations have been introduced to control solidification cracking in autogenous laser welding because weld morphology is one of the factors that influences the initiation and propagation of solidification cracking. Solidification cracks generate thermal discontinuities and visual flaws on the bead surface. In this study, a high-speed infrared camera and a coaxial charge-coupled device camera with an auxiliary illumination laser (808 nm) were employed to identify solidification cracking during laser welding. Deep learning models, developed using two sensor images of a solidified bead, provided location-wise crack formation information. The multisensor-based convolutional neural network models achieved an impressive accuracy of 99.31% in predicting the crack locations. Thus, applying deep learning models expands the capability of predicting solidification cracking, including previously undetectable internal cracks.
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来源期刊
CiteScore
3.60
自引率
9.50%
发文量
125
审稿时长
>12 weeks
期刊介绍: The Journal of Laser Applications (JLA) is the scientific platform of the Laser Institute of America (LIA) and is published in cooperation with AIP Publishing. The high-quality articles cover a broad range from fundamental and applied research and development to industrial applications. Therefore, JLA is a reflection of the state-of-R&D in photonic production, sensing and measurement as well as Laser safety. The following international and well known first-class scientists serve as allocated Editors in 9 new categories: High Precision Materials Processing with Ultrafast Lasers Laser Additive Manufacturing High Power Materials Processing with High Brightness Lasers Emerging Applications of Laser Technologies in High-performance/Multi-function Materials and Structures Surface Modification Lasers in Nanomanufacturing / Nanophotonics & Thin Film Technology Spectroscopy / Imaging / Diagnostics / Measurements Laser Systems and Markets Medical Applications & Safety Thermal Transportation Nanomaterials and Nanoprocessing Laser applications in Microelectronics.
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