An increasing number of selective laser sintering and selective laser melting machines use off-axis infrared cameras to improve online monitoring and data-driven control capabilities. However, there is still a severe lack of algorithmic solutions to properly process the infrared images from these cameras that has led to several key limitations: a lack of online monitoring capabilities for the laser tracks, insufficient pre-processing of the infrared images for data-driven methods, and large memory requirements for storing the infrared images. To address these limitations, we study over 30 segmentation algorithms that segment each infrared image into a foreground and background. By evaluating each algorithm based on its segmentation accuracy, computational speed, and robustness against spatter detection, we identify promising algorithmic solutions. The identified algorithms can be readily applied to the selective laser sintering and selective laser melting machines to address each of the above limitations and thus, significantly improve process control.
翻译:越来越多的选择性激光交接和选择性激光熔化机使用离轴红外红外摄像头来改进在线监测和数据驱动控制能力,然而,仍然严重缺乏适当处理这些照相机提供的红外图像的算法解决办法,导致若干主要限制:激光轨迹缺乏在线监测能力,为数据驱动的方法对红外图像的预处理不足,以及存储红外图像需要大量记忆。为了解决这些限制,我们研究了30多个分离算法,将每个红外图像分成成一个前台和背景。我们根据其分解精度、计算速度和对飞溅探测的稳健性,对每种算法进行评估,从而确定有希望的算法解决办法。所查明的算法可以很容易地应用于选择性激光交接和选择性激光熔化机,以解决上述每项限制,从而大大改进进程控制。