机构

• 合肥物质科学研究院 [5]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [5]

发表日期

• 2020 [1]
• 2019 [1]
• 2018 [3]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks 期刊论文  OAI收割 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16 作者:  Zhang, Yingjie;  Soon, Hong Geok;  Ye, Dongsen;  Fuh, Jerry Ying Hsi;  Zhu, Kunpeng   |  收藏  |  浏览/下载：80/0  |  提交时间：2020/10/26 Feature extraction  Cameras  Fiber lasers  Laser modes  Convolutional neural nets  Additive manufacturing  condition monitoring  convolutional neural networks (CNNs)  melt-pool-affected zone  powder-bed fusion (PBF)   The investigation of plume and spatter signatures on melted states in selective laser melting 期刊论文  OAI收割 OPTICS AND LASER TECHNOLOGY, 2019, 卷号: 111, 页码: 395-406 作者:  Ye, Dongsen;  Zhu, Kunpeng;  Fuh, Jerry Ying Hsi;  Zhang, Yingjie;  Soon, Hong Geok   |  收藏  |  浏览/下载：114/0  |  提交时间：2019/12/25 Plume  Spatter  Selective laser melting  Monitoring  Melted state detection   Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring 期刊论文  OAI收割 MATERIALS & DESIGN, 2018, 卷号: 156, 页码: 458-469 作者:  Zhang, Yingjie;  Hong, Geok Soon;  Ye, Dongsen;  Zhu, Kunpeng;  Fuh, Jerry Y. H.   |  收藏  |  浏览/下载：89/0  |  提交时间：2019/11/11 Additive manufacturing (AM)  Powder-bed fusion  Melt pool, plume and spatter  Statistical process monitoring  Support vector machines (SVM)  Convolutional neural network (CNN)   In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks 期刊论文  OAI收割 ISA TRANSACTIONS, 2018, 卷号: 81, 页码: 96-104 作者:  Ye, Dongsen;  Fuh, Jerry Ying Hsi;  Zhang, Yingjie;  Hong, Geok Soon;  Zhu, Kunpeng   |  收藏  |  浏览/下载：71/0  |  提交时间：2019/01/11 Deep belief network  Selective laser melting  Melted state recognition  Plume and patter  Process monitoring   Defect detection in selective laser melting technology by acoustic signals with deep belief networks 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 卷号: 96, 期号: 5-8, 页码: 2791-2801 作者:  Ye, Dongsen;  Hong, Geok Soon;  Zhang, Yingjie;  Zhu, Kunpeng;  Fuh, Jerry Ying Hsi   |  收藏  |  浏览/下载：34/0  |  提交时间：2019/06/03 Additive manufacturing  Deep belief networks  Fast Fourier transform  Defect detection