摘要
选区激光熔化技术(SLM)被认为是极有前途的增材制造技术之一,但不可逆的溅射行为严重限制了SLM技术的应用。从粉末熔池演变、加工工艺优化和飞溅颗粒动态特征监测等方面,总结了SLM过程中飞溅行为的研究现状,分析了飞溅行为的产生机制,探讨了激光-粉末-熔池相互作用下的熔池演变情况,表明金属蒸气、Marangoni效应和伯努利效应是诱发飞溅的主要因素;讨论了加工工艺与飞溅行为的相互关系,表明通过优化工艺参数和改善打印环境以抑制飞溅是行之有效的方法;阐述了飞溅诱导缺陷的机理,并讨论了SLM过程的监测方法,表明单一信号的局限性会导致监测结果失准,多信号融合监测是提升精准性的重要方法之一。最后,针对飞溅行为存在的关键科学问题和技术难题,展望了SLM加工中飞溅行为的研究方向。
Selective Laser Melting(SLM)is considered one of the most promising additive manufacturing(AM)technologies,but the irreversible sputtering behavior severely limits the application of SLM.The work summarized the research status of splashing behavior in SLM from the aspects of powder melt pool evolution,processing process optimization,and dynamic monitoring of splashed particles.The mechanism of splashing behavior was analyzed,and the evolution of melt pool under the interaction of the laser powder molten pool was explored.It showed that metal vapor,Marangoni effect,and Bernoulli effect were the main factors inducing splashing.The interaction between processing technology and splashing behavior was discussed,indicating that optimizing process parameters and improving the printing environment were effective methods to suppress splashing.The mechanism of splash-induced defects was elaborated,and the monitoring methods of SLM process were discussed.It showed that the limitations of a single signal could lead to inaccurate detection results.Multi signal fusion monitoring was an important method to improve accuracy.Finally,in response to the key scientific and technical challenges in studying splashing phenomena,the research direction of splashing behavior in SLM machining was prospected.
作者
袁美霞
柳校可
华明
YUAN Mei-xia;LIU Xiao-ke;HUA Ming(School of Mechanical-electronic and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)
出处
《精密成形工程》
北大核心
2023年第6期163-173,共11页
Journal of Netshape Forming Engineering
基金
国家重点研发项目(2022YFC2406004)
北京建筑大学研究生创新项目(PG2022134)。
关键词
SLM技术
增材制造
飞溅机制
内部缺陷
飞溅监测
selective laser melting
additive manufacturing
splashing mechanism
internal defects
splashing detection
