Fault Detection in 3D-Printing with Deep Learning
Author:
Affiliation:
1. Institute for Automation and Applied Informatics (IAI) Karlsruhe Institute of Technology (KIT) Hermann-von-Helmholtz-Platz 1,Eggenstein-Leopoldshafen,76344
Funder
Helmholtz Association
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10444098/10444131/10444198.pdf?arnumber=10444198
Reference16 articles.
1. Current status and future directions of fused filament fabrication
2. 3D Printing for the Rapid Prototyping of Structural Electronics
3. RepRap – the replicating rapid prototyper
4. Deep Hybrid State Network With Feature Reinforcement for Intelligent Fault Diagnosis of Delta 3-D Printers
5. 3D Printing Fault Detection Based on Process Data
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An overview of traditional and advanced methods to detect part defects in additive manufacturing processes;Journal of Intelligent Manufacturing;2024-09-02
2. Real-time defect detection for FDM 3D printing using lightweight model deployment;2024-05-24
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