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Snapshot hyperspectral imaging for quality assurance in Laser Powder Bed Fusion

机译:激光粉床融合中质量保证的快照高光谱成像

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Laser Powder Bed Fusion (LPBF) is widely considered a key enabling technology of the future. In order to realize its full potential, however, reproducibility and in-process quality inspection capabilities have to meet industrial requirements. The application of novel sensor technologies such as hyperspectral cameras and intelligent data evaluation methods like machine learning models will allow more reliable manufacturing processes.This article discusses the value of snapshot hyperspectral imaging as a means to predict process states and defects with the help of machine learning algorithms. The imaging technology is presented and its characteristic advantage of providing spectral as well as spatial resolution is weighed against the drawbacks of low temporal resolution and reduced spatial resolution. Besides, different methods and configurations for in- process data acquisition and subsequent data labeling are explained. Finally, the utilization of this monitoring approach to the LPBF-processing of magnesium alloys is discussed and results are presented.
机译:激光粉床融合(LPBF)被广泛认为是未来的关键能够实现技术。然而,为了实现其全部潜力,可重复性和过程质量检测能力必须满足工业需求。像机器学习模型一样的新型传感器技术(如高光谱相机和智能数据评估方法)的应用将允许更可靠的制造过程。本文讨论了快照高光谱成像的价值作为预测机器学习的帮助下的过程状态和缺陷算法。提出了成像技术,并且提供了提供光谱以及空间分辨率的特征优势,以抵抗时间分辨率低的缺点和减少空间分辨率。此外,还解释了用于进程数据采集和后续数据标签的不同方法和配置。最后,讨论了利用这种监测方法在镁合金的LPBF加工中,并提出了结果。

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