In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks
Ye, Dongsen1,2,3; Fuh, Jerry Ying Hsi2; Zhang, Yingjie2; Hong, Geok Soon2; Zhu, Kunpeng3
2018-10-01
Source PublicationISA TRANSACTIONS
ISSN0019-0578
Volume81Pages:96-104
Corresponding AuthorZhu, Kunpeng(zhukp@iamt.ac.cn)
AbstractCritical quality issues such as high porosity, cracks, and delamination are common in current selective laser melting (SLM) manufactured components. This study provides a flexible and integrated method for in situ process monitoring and melted state recognition during the SLM process, and it is useful for process optimization to decrease part quality issues. The part qualities are captured by images obtained from an off-axis setup with a near-infrared (NIR) camera. Plume and spatter signatures are closely related to the melted states and laser energy density, and they are employed for the SLM process monitoring in an adapted deep belief network (DBN) framework. The melted state recognition with the improved DBN and original NIR images requires little signal preprocessing, less parameter selection and feature extraction, obtaining the classification rate 83.40% for five melted states. Compared to the other methods of neural network (NN) and convolutional neural networks (CNN), the proposed DBN approach is identified to be accurate, convenient, and suitable for the SLM process monitoring and part quality recognition.
KeywordDeep belief network Selective laser melting Melted state recognition Plume and patter Process monitoring
Funding OrganizationChina Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore
DOI10.1016/j.isatra.2018.07.021
WOS KeywordPOWDER-BED FUSION ; STAINLESS-STEEL ; FAULT-DIAGNOSIS ; NEURAL-NETWORK ; SPECTROSCOPY ; BEHAVIOR
Indexed BySCI
Language英语
Funding ProjectChina Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore
Funding OrganizationChina Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; China Scholarship Council ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; Chinese Academy of Sciences 100 Talents Program ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National University of Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore ; National Additive Manufacturing Innovation Cluster, Singapore
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Multidisciplinary ; Instruments & Instrumentation
WOS IDWOS:000449897700010
PublisherELSEVIER SCIENCE INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.hfcas.ac.cn:8080/handle/334002/34158
Collection中科院合肥物质科学研究院先进制造技术研究所
Corresponding AuthorZhu, Kunpeng
Affiliation1.Univ Sci & Technol China, Dept Automat, Hefei 230026, Anhui, Peoples R China
2.Natl Univ Singapore, Dept Mech Engn, Singapore 117575, Singapore
3.Chinese Acad Sci, Inst Adv Mfg Technol, Changzhou 213164, Peoples R China
Recommended Citation
GB/T 7714
Ye, Dongsen,Fuh, Jerry Ying Hsi,Zhang, Yingjie,et al. In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks[J]. ISA TRANSACTIONS,2018,81:96-104.
APA Ye, Dongsen,Fuh, Jerry Ying Hsi,Zhang, Yingjie,Hong, Geok Soon,&Zhu, Kunpeng.(2018).In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks.ISA TRANSACTIONS,81,96-104.
MLA Ye, Dongsen,et al."In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks".ISA TRANSACTIONS 81(2018):96-104.
Files in This Item: Download All
File Name/Size DocType Version Access License
In situ monitoring o(2147KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ye, Dongsen]'s Articles
[Fuh, Jerry Ying Hsi]'s Articles
[Zhang, Yingjie]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ye, Dongsen]'s Articles
[Fuh, Jerry Ying Hsi]'s Articles
[Zhang, Yingjie]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ye, Dongsen]'s Articles
[Fuh, Jerry Ying Hsi]'s Articles
[Zhang, Yingjie]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.