摘要
增材制造技术能够突破传统制造瓶颈,实现复杂几何结构的一体化设计制造,同时有助于提高产品零部件的可靠性,在空天制造领域有着广泛的应用前景。聚焦于航空发动机增材制造中的激光选区熔化技术(SLM),针对工艺端/性能端的共性问题,首先从技术优化(大幅面多光束技术、能场辅助技术)的角度回顾了各类实验参数对材料组织性能的调控;然后通过前沿技术手段(质量在线监测技术、智能化机器学习调控)的研究综述,探讨了监测/预测在成形过程前中端的优化作用;随后对SLM成形关键航空发动机材料进行了系统性总结,以更好地指导选材及性能调控;最后对现有SLM的技术方案和航空发动机材料种类进行了问题总结,并展望了未来的发展前景,旨在为航空发动机制造领域提供有价值的意见。
Additive manufacturing technology has the capability of breaking through traditional manufacturing constraints,thus enabling the integrated design and manufacturing of complex geometric structures.Simultaneously,this technology contributes to enhancing the reliability of product components with extensive potential applications in the aerospace industry.To address the common issues related to the process and performance,this study,focusing on the Selective Laser Melting(SLM)technique within additive manufacturing for aircraft engines,initially revisits the regulation of material structure and properties through a perspective of technical optimization,including large-area multi-beam technology and field-assisted techniques.Subsequently,by delving into cutting-edge techniques such as quality online monitoring and intelligent machine learning control,the optimization role of monitoring and predicting in the early and middle stages of the forming process is discussed.Then,aiming at providing better guidance for material selection and performance control,the key aerospace engine materials for SLM formation is systematically summarized.Lastly,a review of current SLM technology solutions and types of aerospace engine materials is concluded,along with an outlook on future development prospects so as to provide valuable insights for the field of aerospace engine manufacturing.
作者
周运龙
马毅
管迎春
Yunlong ZHOU;Yi MA;Yingchun GUAN(School of Mechanical Engineering and Automation,Beihang University,Beijing100191,China;National Engineering Laboratory of Additive Manufacturing for Large Metallic Components,Beihang University,Beijing100191,China)
出处
《航空学报》
EI
CAS
CSCD
北大核心
2024年第13期43-80,共38页
Acta Aeronautica et Astronautica Sinica
基金
宁波市重点研发计划(2023Z012)。
关键词
航空发动机
激光选区熔化
能场辅助
机器学习
在线监测
航空航天材料
aero-engine
selective laser melting
energy field assistance
machine learning
online monitoring
aerospace materials
