航空航天
同质性(统计学)
机械工程
沉积(地质)
材料科学
过程(计算)
计算机科学
工程类
航空航天工程
沉积物
生物
操作系统
机器学习
古生物学
作者
Felicity Freeman,Lova Chechik,Ben Thomas,Iain Todd
标识
DOI:10.1016/j.jmatprotec.2022.117823
摘要
Directed energy deposition (DED) is an emerging technology with significant industrial potential in the repair of critical aerospace components, however its adoption has been limited by concerns about geometry-driven microstructural and mechanical property variation. These could be resolved by controlling the local temperature field, which would result in a consistent and predictable cooling profile. Closed-loop control approaches have been investigated previously, but with limited assessment of mechanical properties and only on small builds. In this work, we confirm that using fixed build parameters results in a statistically significant, geometry-driven variation in the bulk mechanical properties of DED-built 316 L steel. To address this issue, we have developed an industrially-suitable control algorithm using a low-cost coaxial camera, applying statistical process control techniques to identify representative melt pool images from the livestream. This has been tested on long builds, maintaining a control adjustment frequency of 1 Hz on build durations of > 1 h. Performance has been quantified through bulk mechanical testing, which confirmed that the control algorithm successfully eliminated the component-scale trends in melt pool size, and achieved a geometry-agnostic process with improved mechanical homogeneity.
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