热成像
材料科学
过程(计算)
热的
融合
再现性
原位
工艺工程
红外线的
计算机科学
光学
热力学
操作系统
物理
工程类
哲学
气象学
统计
语言学
数学
作者
Joseph Hofman,Katrin Wudy
标识
DOI:10.1007/s00170-022-10169-4
摘要
Abstract Despite extensive research, new plastic powders must still be qualified for laser-based powder bed fusion using trial and error. Furthermore, part properties such as mechanical properties, surface roughness, or density exhibit a comparatively low reproducibility. Recent progress in the field of process monitoring, however, indicates that infrared thermography can be used to correlate melt pool temperatures with the resulting part properties. The analysis of the influence of process parameters on the resulting melt pool temperatures has up until now been limited to the evaluation of the maximum temperature during exposure and the mean temperature at arbitrary moments after exposure. However, the cooling rate of the polymer melt is also essential. To prove this hypothesis, a continuous data stream, which enables an automated calculation of characteristic processing times and temperatures, is introduced within the scope of this work. Single-layer specimens are manufactured with various energy inputs, while the resulting temperature of the melt is recorded using thermal imaging. The peak temperatures are combined with the characteristics that describe the temperature decay after exposure, such as a decay time determined at a specific cooling rate. These metrics quantify the cooling behavior of melt pools in a systematic and reproducible way. Furthermore, the sequence of decay values at different cooling rates can potentially be combined with existing process knowledge to differentiate process regimes. The presented approach can be used to create a more in-depth process understanding in later works, thereby enabling applications such as in-situ quality assurance.
科研通智能强力驱动
Strongly Powered by AbleSci AI