Intra-layer and inter-layer monitoring of laser powder bed fusion defects based on airborne acoustic and gⁿ-Res model: pore and deformation

Macroscopic deformation and microscopic pores are the main defects affecting the comprehensive performance of laser powder bed fusion (LPBF) parts. The LPBF process involves highly coupled multiple physical mechanisms over a wide time scale, making it difficult to obtain strongly correlated defect characteristics and achieve online monitoring. Thus, this study proposes an acoustic-based macro–micro defect synchronous monitoring technology. It enables monitoring by analysing process information progressively from intra-layer to inter-layer. The research identifies that high energy density leads to deformation defects, with helical scan strategy energy fluctuations exacerbating deformation. A correlation between keyhole pores and high-frequency signal components allows quantitative pore analysis directly from acoustic signals. Furthermore, an intelligent diagnosis model (gⁿ-Res_SC) is proposed, incorporating high-order information interaction and residual structure for in-depth process analysis. The model demonstrates superior performance with accuracy (90.70%), recall (90.70%) and F1-score (90.40%) in LPBF acoustic monitoring signal evaluation.