Real-time anomaly detection using convolutional neural network in wire arc additive manufacturing: Molybdenum material
出版年份 2022 全文链接
标题
Real-time anomaly detection using convolutional neural network in wire arc additive manufacturing: Molybdenum material
作者
关键词
Wire arc additive manufacturing, Anomaly detection, Machine learning, Convolutional neural network, In situ quality monitoring
出版物
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
Volume 302, Issue -, Pages 117495
出版商
Elsevier BV
发表日期
2022-01-11
DOI
10.1016/j.jmatprotec.2022.117495
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Wire and arc additive manufacturing: Opportunities and challenges to control the quality and accuracy of manufactured parts
- (2021) Davoud Jafari et al. MATERIALS & DESIGN
- Real-time Detection of Clustered Events in Video-imaging data with Applications to Additive Manufacturing
- (2021) Hao Yan et al. IISE Transactions
- Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning
- (2021) Zackary Snow et al. JOURNAL OF MANUFACTURING SYSTEMS
- Thermal field prediction for welding paths in multi-layer gas metal arc welding-based additive manufacturing: A machine learning approach
- (2021) Zeyu Zhou et al. Journal of Manufacturing Processes
- Crystallographic texture evolution in electron beam melting additive manufacturing of pure Molybdenum
- (2021) Patxi Fernandez-Zelaia et al. MATERIALS & DESIGN
- Online Convolutional Neural Network-based anomaly detection and quality control for Fused Filament Fabrication process
- (2021) Jiaqi Lyu et al. Virtual and Physical Prototyping
- Balling phenomenon and cracks in alumina ceramics prepared by direct selective laser melting assisted with pressure treatment
- (2020) Yu-Di Qiu et al. CERAMICS INTERNATIONAL
- A survey of the recent architectures of deep convolutional neural networks
- (2020) Asifullah Khan et al. ARTIFICIAL INTELLIGENCE REVIEW
- Wire and arc additive manufacturing of metal components: a review of recent research developments
- (2020) Jienan Liu et al. The International Journal of Advanced Manufacturing Technology
- A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect
- (2019) Chao Liu et al. JOURNAL OF MANUFACTURING SYSTEMS
- Layer-Wise Modeling and Anomaly Detection for Laser-Based Additive Manufacturing
- (2019) Seyyed Hadi Seifi et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives
- (2019) Xinbo Qi et al. Engineering
- Weld image deep learning-based on-line defects detection using convolutional neural networks for Al alloy in robotic arc welding
- (2019) Zhifen Zhang et al. Journal of Manufacturing Processes
- Effects of defects on mechanical properties in metal additive manufacturing: A review focusing on X-ray tomography insights
- (2019) Anton du Plessis et al. MATERIALS & DESIGN
- Hierarchical spatial-temporal modeling and monitoring of melt pool evolution in laser-based additive manufacturing
- (2019) Shenghan Guo et al. IISE Transactions
- Additive manufacturing of metallic components – Process, structure and properties
- (2018) T. DebRoy et al. PROGRESS IN MATERIALS SCIENCE
- Anisotropy and heterogeneity of microstructure and mechanical properties in metal additive manufacturing: A critical review
- (2018) Y. Kok et al. MATERIALS & DESIGN
- Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring
- (2018) Yingjie Zhang et al. MATERIALS & DESIGN
- In-situ monitoring of melt pool images for porosity prediction in directed energy deposition processes
- (2018) Mojtaba Khanzadeh et al. IISE Transactions
- A review of the wire arc additive manufacturing of metals: properties, defects and quality improvement
- (2018) Bintao Wu et al. Journal of Manufacturing Processes
- Layerwise Anomaly Detection in Laser Powder-Bed Fusion Metal Additive Manufacturing
- (2018) Mohamad Mahmoudi et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes
- (2016) Mahesh Mani et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing
- (2016) Sarah K. Everton et al. MATERIALS & DESIGN
- In situ quality control of the selective laser melting process using a high-speed, real-time melt pool monitoring system
- (2014) S. Clijsters et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started