即用即质：利用对比深度学习对光学和声学特征进行传感器融合，以监测激光粉末床融合工艺中的多种材料成分

IF 10.2 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Virtual and Physical Prototyping Pub Date : 2024-05-27 DOI:10.1080/17452759.2024.2356080

Vigneashwara Pandiyan, Antonios Baganis, Roland Axel Richter, Rafał Wróbel, Christian Leinenbach

引用次数: 0

摘要

对多材料激光粉末床融合（LPBF）的需求日益增长，这面临着工艺控制和质量监控方面的挑战，尤其是在确保精确的材料成分方面。本研究探讨了...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Qualify-as-you-go: sensor fusion of optical and acoustic signatures with contrastive deep learning for multi-material composition monitoring in laser powder bed fusion process

Growing demand for multi-material Laser Powder Bed Fusion (LPBF) faces process control and quality monitoring challenges, particularly in ensuring precise material composition. This study explores ...

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来源期刊

Virtual and Physical Prototyping Engineering-Industrial and Manufacturing Engineering

CiteScore

13.60

自引率

6.60%

发文量

期刊介绍： Virtual and Physical Prototyping (VPP) offers an international platform for professionals and academics to exchange innovative concepts and disseminate knowledge across the broad spectrum of virtual and rapid prototyping. The journal is exclusively online and encourages authors to submit supplementary materials such as data sets, color images, animations, and videos to enrich the content experience. Scope: The scope of VPP encompasses various facets of virtual and rapid prototyping. All research articles published in VPP undergo a rigorous peer review process, which includes initial editor screening and anonymous refereeing by independent expert referees. This ensures the high quality and credibility of published work.