对激光金属沉积工艺中熔池空间信息的离轴监测

Maria Grazia Guerra , Marco Mazzarisi , Marco Latte , Fulvio Lavecchia , Sabina Campanelli , Luigi Maria Galantucci
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引用次数: 0

摘要

激光金属沉积(LMD)是最有前途的增材制造(AM)技术之一,可用于金属部件的制造、涂层和修复。然而,由于影响工艺的因素较多,可能会出现缺陷,如几何和尺寸不准确、残余应力大和内部空洞等,从而影响生产部件的质量和机械性能。因此,需要能够及时发现缺陷和过程异常的过程监控系统。在这项工作中,介绍了一种适用于 LMD 的过程监控系统。该系统包括一台工业 CMOS 摄像机,放置在 LMD 机器腔体内,用于采集显示熔池区域的图像。通过使用适当开发的图像处理算法,监控系统能够在过程中提取熔池的二维空间坐标,并描绘出制造样品的几何形状。此外,还计算了与沉积高度相关的特定指标,以评估工艺/产品的质量。这种监测方法的潜力在于设备简单,更主要的是可以在不中断工艺的情况下监测熔池的空间演变,最终实现对 LMD 工艺的进一步控制。监测系统在两个 316L 薄壁部件上进行了测试,并通过将监测获得的数据与综合后处理三维扫描方法进行比较,对结果进行了验证。
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Off-axis monitoring of the melt pool spatial information in Laser Metal Deposition process

Laser Metal Deposition (LMD) is one of the most promising Additive Manufacturing (AM) technologies for the fabrication, coating and repair of metal components. Although, due to the high number of factors influencing the process, defects may arise, as geometrical and dimensional inaccuracies, high residual stresses and internal voids, with effects on the quality and the mechanical performances of the produced parts. Thus, the need for in-process monitoring systems capable of timely detecting the onset of defects and process anomalies emerged.

In this work, an in-process monitoring system suitable for LMD was presented. It consisted of an industrial CMOS camera placed in the LMD machine chamber and set for the acquisition of images showing the melt pool area. Through the use of properly developed image processing algorithms, the monitoring system was capable to extract in-process the melt pool 2D spatial coordinates and to depict the geometry of the fabricated samples. Moreover, specific indexes related to the deposited height were computed in order to evaluate the quality of the process/product. The potentiality of such monitoring method lies in the simplicity of the equipment, and, mostly, in the possibility of monitoring the spatial evolution of the melt pool without interrupting the process and enabling, eventually, a further control of the LMD process. The monitoring system was tested on two 316L thin-walled components and results were validated by comparing the data obtained from the monitoring with a consolidated post-process 3D scanning method.

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Editorial Preface Off-axis monitoring of the melt pool spatial information in Laser Metal Deposition process Machine learning-assisted collection of reduced sensor data for improved analytics pipeline Demand-Oriented Optimization of Machine Tools: a Closed Loop Approach for Safe Exploration in Series Production
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