Real-time detection of powder bed defects in laser powder bed fusion using deep learning on 3D point clouds

Powder bed defects are critical factors affecting the print quality and stability in Laser Powder Bed Fusion (LPBF). However, traditional 2D image-based powder bed defect monitoring methods are limited by sensitivity to lighting conditions and insufficient data capture. This study proposes a real-ti...

תיאור מלא

מידע ביבליוגרפי
Main Authors: Junlai Zhao, Zihan Yang, Qingpeng Chen, Chen Zhang, Jianhui Zhao, Guoqing Zhang, Fang Dong, Sheng Liu
פורמט: Article
שפה:English
יצא לאור: Taylor & Francis Group 2025-12-01
סדרה:Virtual and Physical Prototyping
נושאים:
גישה מקוונת:https://www.tandfonline.com/doi/10.1080/17452759.2024.2449171