Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion

作者：Yu‐Chen Sun, Sanam Gorgannejad, Aiden A. Martin, Jenny Wang Nicolino, Maria Strantza, Jean‐Baptiste Forien, Vivek Thampy, Sen Liu, Peiyu Quan, Christopher J. Tassone, Manyalibo J. Matthews, Nicholas P. Calta · 发表于：Applied Physics Letters · 年份：2024 · DOI：10.1063/5.0205663 · 被引用次数：13 · 研究领域：Additive Manufacturing Materials and Processes、Welding Techniques and Residual Stresses、Thermography and Photoacoustic Techniques

Various nondestructive diagnostic techniques have been proposed for in situ process monitoring of laser powder bed fusion (LPBF), including melt pool pyrometry, whole-layer optical imaging, acoustic emission, atomic emission spectroscopy, high speed melt pool imaging, and thermionic emission. Correlations between these in situ monitoring signals and defect formation have been demonstrated with acoustic signals having been shown to predict pore formation with especially high confidence in recent machine learning studies. In this work, time-resolved acoustic data are collected in both the conduction and keyhole welding regimes of LPBF-processed Ti-6Al-4V alloy. A non-dimensionalized Strouhal number analysis, used in whistle aeroacoustics, is applied to demonstrate that the acoustic signals recorded in the keyhole regimes can be directly associated with the vapor depression morphology. This mechanistic understanding developed from whistle aeroacoustics shows that acoustic monitoring during the LPBF process can provide a direct probe into the vapor depression dynamics and defect occurrence, especially in the keyhole regimes relevant to printing and defect formation.